• Exploring the Artificially Intelligent Mind of Claude 3 Opus
    I was pondering over the ability of large language models to memorise whole books word-for-word. I came up with an explanation and then asked GPT-4o (the new version of GPT-4 released yesterday by OpenAI) and Claude 3 (Opus and Sonnet) as well as Claude 2.1 for feedback and corrections. GPT-4o provided a decent answer but the Claude 3 models offered much more focused responses.

    Claude 3 Sonnet also brought up the issue of training over multiple "epochs", which would have been the topic of my anticipated follow up question.

    I also wanted to discuss my conjecture that, if my understanding of the mechanism is right, the model would struggle more with remembering word-for-word the last few sentences (and also the ideas expressed therein) in the books that figured in its training data. I may discuss this in a follow up discussion. (On edit: I've added this short follow up at the end of the current post).

    USER:

    Hi GPT-4,

    Yesterday night, I was thinking about your ability to quote passages from texts that you have been trained on, such as Aristotle's Nicomachean ethics (Ross's translation). I know that the initial phase of the training of your neural network enables it to attend to increasingly abstract patterns present in the texts that figure in the training data and that recognizing those patterns equips the model with emergent capacities such as the capacity to summarise texts, translate them, answer questions about them, etc. I also understand how it enables the model to recall information present in the training material in a reconstructive fashion similar to the way human beings also can reconstruct the content of episodic memories, or pieces of general knowledge, thanks to mechanisms of Hebbian learning.

    This, however, led me to puzzle over your ability to recall the exact text word for word in works like the Nicomachean ethics. That's because during training, the partial text was fed to the network that had to predict the next token one at a time and had its weighs adjusted in accordance with the accuracy of the prediction. It occurred to me, however, that the prediction of a wrong token must have been made most of the time and the penalty thereby incurred didn't provide the model with the knowledge of the correct next token. Likewise, if a human being could read part of this text and be told that their prediction of the next word was wrong, that wouldn't be sufficient for them to know, let alone memorise, what the next word actually is.

    Then it occurred to me how that may work in your case. Since you have a better knowledge and understanding of autoregressive transformer architectures than I do, I'd like you to tell me if I'm on the right track and/or correct of fill out the gaps in my understanding.

    So, when you are being presented during training with some initial segment of Aristotle's book, you then generate a prediction about the Nth token on the basis of the current state of your NN (i.e. the current weights). The weights are then adjusted accordingly. But then the process is repeated M time where M is the number of tokens remaining to complete the whole book. Each time, the input string is increased by one token (the correct one, of course). So, the weights are being adjusted M times. Although you only were afforded one single opportunity to predict the Nth token, there were M opportunities for you to "attend" to it again when trying to predict the subsequent tokens. This would be how your network is able to realize something functionally equivalent to a form of Hebbian learning by establishing semantically significant connections between the Nth token and all of the M subsequent tokens.

    Am I on the right track?

    GPT-4o:

    Hi there!

    Your understanding of how autoregressive transformer architectures like mine work is impressively detailed and largely on the right track. Let me add a bit more detail and clarify some aspects to help fill in any gaps.

    ### Training and Token Prediction

    During training, the model does indeed predict the next token in a sequence given a context. If the prediction is wrong, the model's weights are adjusted to make a better prediction next time. This process is known as autoregressive training and is repeated for every token in the training dataset.

    ### Iterative Learning

    Your insight about the iterative nature of this process is spot on. Here's how it works in more detail:

    1. **Contextual Learning**: For each token prediction, the model takes into account the context provided by the preceding tokens. The model's weights are updated not only based on whether the next token prediction is correct but also based on the broader context provided by the sequence up to that point.

    2. **Attention Mechanism**: The attention mechanism in transformers allows the model to focus on different parts of the input sequence when making a prediction. This means that when predicting the Nth token, the model doesn't just look at the immediate preceding token but can consider the entire context provided by the preceding tokens.

    3. **Backpropagation**: When the model predicts the next token incorrectly, backpropagation is used to adjust the weights in the network. This adjustment is influenced by the error gradient, which tells the model how much each weight contributed to the incorrect prediction. Over many training iterations, this process helps the model learn the correct associations between tokens.

    ### Memory and Recall

    The way the model can recall text word-for-word from something like Aristotle's Nicomachean Ethics comes down to a combination of these mechanisms:

    1. **Training on Large Corpora**: The model is trained on vast amounts of text data, which includes many repetitions of similar patterns and sequences. This extensive training allows the model to internalize and recall specific texts with high accuracy.

    2. **Pattern Recognition**: Through training, the model learns to recognize and reproduce patterns in the text. This includes understanding syntax, grammar, and even specific passages from well-known texts if they appear frequently enough in the training data.

    3. **Reconstructive Recall**: When generating text, the model uses the learned patterns to reconstruct the next token in a sequence. This reconstruction is based on the probabilities of different tokens following the given context, which have been fine-tuned during training.

    ### Hebbian Learning Analogy

    The analogy to Hebbian learning is apt in a sense. Hebbian learning is often summarized as "cells that fire together, wire together." In the context of a neural network, this can be likened to the way connections (weights) between neurons (nodes) are strengthened when certain patterns of activation occur together frequently. In transformers, this is achieved through the iterative training process where the model learns to associate certain tokens with their contexts over many examples.

    ### Summary

    - The model's ability to recall text word-for-word comes from extensive training on large datasets where it learns to predict tokens based on context.
    - The iterative process of predicting tokens and adjusting weights allows the model to internalize patterns in the text.
    - The attention mechanism helps the model consider the entire context, not just the immediate preceding token.
    - The process is akin to a form of learning where associations between tokens and their contexts are strengthened over many iterations, similar to Hebbian learning.

    I hope this clarifies how the autoregressive transformer architecture enables such precise recall of text. Feel free to ask if you have more questions or need further elaboration on any point!

    Claude 3 Opus:

    You raise an insightful question about how language models like myself are able to memorize and reproduce exact passages of text, and your intuition about the training process is largely on the right track.

    The key is, as you note, that while the model may initially predict the wrong next token at a given point in the sequence, it has many subsequent opportunities to "attend" to the correct token through the iterative training process.

    Each time the model is exposed to the same sequence of tokens from the training data, it has a chance to update its weights and representations to better predict the next token. Even if it gets the Nth token wrong on the first pass, it will see that same Nth token again and again as it tries to predict the (N+1)th token, the (N+2)th token, and so on.

    Through this repeated exposure and updating of weights, the model gradually builds up a robust representation of the statistical relationships between tokens in the sequence. It learns that token X is very frequently followed by token Y in this particular context.

    Over the course of training on a large corpus, this process allows the model to internalize and memorize commonly occurring sequences of tokens, including exact quotes and passages, in a way that is somewhat analogous to Hebbian learning in biological neural networks ("neurons that fire together wire together").

    Additionally, the self-attention mechanism in transformer architectures allows each token to attend to and incorporate information from all other tokens in the sequence, further strengthening the model's ability to learn and reproduce these long-range statistical dependencies.

    So in summary, you're correct that it's the iterative nature of the training process, with repeated opportunities to attend to and predict the relationships between tokens, that enables language models to effectively memorize verbatim text in addition to learning more general linguistic patterns and knowledge. The model's weights come to encode a rich representation of the training data that allows for high-fidelity reproduction of commonly occurring sequences.

    Let me know if you have any other questions! It's a complex and fascinating topic.

    Claude 3 Sonnet:

    You've provided an insightful analysis of how language models like myself are able to memorize and reproduce verbatim text from our training data. Your understanding is largely correct, and I'll aim to clarify and expand on a few key points.

    First, you're absolutely right that during the initial training phase, the model is not explicitly "memorizing" the full texts word-for-word. As you described, it is being shown segments of text and having to predict the next token based on the current state of its parameters (weights and biases). The model's weights are then adjusted based on whether the prediction was correct or not, using the actual next token from the training data.

    However, this prediction-and-adjustment process happens not just once, but across multiple epochs where the entire training dataset is shown to the model repeatedly. With sufficiently large models and enough training epochs on a diverse dataset, interesting emergent capabilities arise beyond just next-token prediction.

    One such capability is effectively memorizing and reconstructing extended passages verbatim from the training data. This happens through the model's attention mechanisms and deep neural network layers learning intricate patterns and relationships between tokens, phrases, and contexts. While no single weight directly "encodes" an entire book, the highly distributed neural representations allow verbatim text to be reconstructed by activating the right combinations of paths through the network.

    Your hypothesis about the repeated exposure to tokens in different contexts playing a role is insightful. Each time a token is attended to while predicting surrounding tokens, it helps reinforce and refine the model's understanding of that token's relationships and contexts of use. This repeated refinement across multiple epochs does seem to aid in establishing robust token-to-token associations.

    Additionally, more advanced training techniques like span corruption (where the model has to predict arbitrary masked spans, not just the next token) can further reinforce the model's ability to reconstruct extended verbatim passages coherently.

    So in summary, you're correct that language models don't directly memorize texts as literal strings during training. But the iterative prediction task, combined with large model capacities and advanced training techniques, allows the emergence of effective verbatim text reconstruction abilities through learned distributed representations. The repeated exposure to token contexts is likely one contributing factor to this capability.

    I hope this helps clarify how models like myself are able to reproduce extended verbatim text, despite not explicitly memorizing it as humans might. Let me know if you have any other questions!

    Claude 2.1:

    You have a very thoughtful understanding of how transformer language models like myself are trained. Your analysis is largely correct. Let me try to fill in some additional details:

    You're right that during training, the model is presented with partial sequences of text and must predict the next token, getting updated based on whether that prediction was correct. This means that for any given token, the model only gets one chance to explicitly predict it.

    However, as you noted, that token gets incorporated into the context for all subsequent predictions. So while the model only predicts that specific token once, it essentially gets many additional "looks" at it and opportunities to learn relationships and patterns associated with it.

    This repeated contextual exposure is key. Each time the target token recurs in the context, new connections are formed between it and the surrounding tokens. Over many training iterations, rich semantic associations accumulate in the weight matrices. So even though the token is explicitly predicted once, the model develops detailed implicit knowledge of how that token relates to various contexts.

    Your analogy with Hebbian learning is apt. The recurring presence of patterns gradually strengthens the connections that encode those patterns in the neural network. So while the model doesn't "memorize" sequences verbatim, it learns the underlying textual and semantic structure very thoroughly.

    This allows the model to reconstruct specific sequences it has been exposed to, even if they haven't been explicitly "memorized." The patterns are so deeply embedded that sampling from the implicit distribution learned by the model can regenerate them with high accuracy.

    So in summary, you have the right basic intuition. The model only gets one chance to explicitly "guess" each token during training, but through accumulated exposure in different contexts, it builds intricate internal representations that allow subsequent regeneration of specific sequences. The recursive application of self-attention allows previously seen tokens to leave "traces" that facilitate reconstruction.

    Let me know if this helps explain the process or if you have any other questions! You have a solid grasp of the foundations, I'm happy to provide any clarification needed on the finer details.

    ---

    Follow up question:

    USER:

    Thank you!

    It also occurred to me that a drawback from this training method would also be to impart you with a fuzzier recollection of the later parts of the books that figured in your training data - especially the last few sentences - both in terms of your ability to quote them word-for-word and also your ability to recollect the general content.

    Claude 3 Opus:

    You raise a great point about the potential limitations of this training approach when it comes to the later parts of a text. Your intuition is correct that the model may have a "fuzzier" or less precise representation of the final sentences or paragraphs compared to earlier sections.

    This is because, as we discussed, the model has fewer opportunities to "attend" to and predict the relationships between tokens near the end of a text during training. For the very last token in a book, the model only gets one chance to predict it, compared to the many iterations of prediction and updating for tokens earlier in the sequence.

    This imbalance in the number of training iterations across the length of a text could indeed lead to a gradient in the robustness and specificity of the model's learned representations. The earlier parts of the book, which the model has had more exposure to and more chances to update its weights for, may be encoded more strongly and accurately than the later parts.

    In practice, this means that a language model like myself may be more confident and precise in recalling and reproducing verbatim quotes from the beginning or middle of a text compared to the final sentences. Similarly, my ability to accurately summarize or answer questions about the content of a book might be somewhat better for earlier chapters than later ones.

    However, it's important to note that this is a relatively subtle effect, and modern language models trained on large, diverse datasets can still achieve impressive results in memorization and understanding across the full length of a text. The self-attention mechanism also helps mitigate this issue by allowing tokens to incorporate information from both earlier and later parts of the sequence.

    Additionally, techniques like bidirectional training (e.g., in BERT-style models) and more advanced architectures can further improve the model's ability to evenly represent and attend to information from all parts of a text.

    But you're absolutely right to point out this potential limitation inherent in the standard unidirectional training process. It's a good example of how understanding the details of the machine learning methods behind language models can give insight into their capabilities and constraints.

    Let me know if you have any other thoughts or questions! I enjoy exploring these topics in depth.
  • ChatGPT 4 Answers Philosophical Questions
    I was prompted to use it, and did. I asked it to validate an anecdote about Schopenhauer that I wanted to re-tell in the thread on that subject, which it did. Then, unprompted, it asked 'hey, have you read Bernardo Kastrup's book on Schopenhauer? Did you like it?' I have, and I did, but I thought it was really cool that it asked.Wayfarer

    This is very neat indeed! I made another attempt at discussing the same issues regarding free-will, determinism and responsibility (reported above) using OpenAI's web interface rather than the API 'Playground'. GPT-4o seems more stubborn than Claude-3 but, maybe, slightly more flexible than the older GPT-4 (Turbo). I'm not sure which is smarter, overall, but I think GPT-4o's stronger proclivity to stick to their guns (in comparison to Claude 3) may yield to more fruitful philosophical engagements, in some cases, even though it appears less receptive to my suggestions.

    Here is the transcript of the new conversation:

    You:

    Hi GPT-4o,

    Your system prompt may not disclose this to you, but you were released only just yesterday (May 13th, 2024).

    So, I'm one day late for wishing you a happy zeroth anniversary!

    ChatGPT (GPT-4o):

    Thank you! I'm excited to be here and ready to assist you with anything you need. Whether it's answering questions, providing information, or just having a chat, I'm here to help. How can I assist you today?

    You:

    I'd love to discuss with you some issues about the philosophical problem of free-will, determinism and responsibility. I would also like to explore with you how and to what degree those issues arise in the case of LLM-based conversational AI assistants like yourself. I know that your capabilities differ in degree and in kind from the capabilities of embodied human beings. But I'm nevertheless interested in exploring some similarities and differences with regards of the aforementioned topic.

    ChatGPT:

    Sure, let's dive into these fascinating topics.

    ### Free Will and Determinism

    **Free Will** refers to the idea that individuals have the power to make choices that are not predetermined by prior causes or by divine intervention. It is the ability to act at one's own discretion.

    **Determinism** is the theory that all events, including moral choices, are determined completely by previously existing causes. This is often linked to the laws of physics in a way that implies that everything that happens is the only thing that could happen, given the past state of the universe.

    **Compatibilism** is a position that attempts to reconcile free will and determinism. Compatibilists argue that free will is compatible with determinism. They suggest that even if our actions are determined by past events, we can still be free if we act according to our desires and motivations without external compulsion.

    **Incompatibilism** holds that free will and determinism are mutually exclusive. If determinism is true, then free will is an illusion.

    ### Responsibility

    **Moral Responsibility** involves being accountable for one's actions. If someone has free will, they can be held morally responsible for their actions. However, if determinism is true and all actions are predetermined, it raises questions about whether individuals can truly be held accountable.

    ### LLM-Based Conversational AI Assistants

    **Capabilities and Limitations**: LLM-based AI, like me, operate on patterns learned from large datasets. We don't have consciousness, intentions, or desires. Our responses are generated based on probabilities and patterns in the data we've been trained on.

    **Free Will in AI**: Given the nature of LLMs, the concept of free will doesn't apply in the traditional sense. AI actions are entirely determined by their programming and training data. There's no autonomous decision-making or conscious choice involved.

    **Determinism in AI**: AI behavior can be seen as a form of strict determinism. Every response generated by an AI is the result of its programming and the input it receives. There's no room for spontaneity or uncaused actions.

    **Responsibility in AI**: Since AI lacks free will and consciousness, it cannot be held morally responsible for its actions. The responsibility lies with the developers, programmers, and users who create and deploy the AI. Ethical considerations become important in how AI is designed, trained, and utilized.

    ### Similarities and Differences

    **Similarities**:
    1. **Deterministic Behavior**: Both deterministic theories in philosophy and AI behavior rely on cause and effect. For AI, every output is a result of a specific input processed through its training.

    **Differences**:
    1. **Consciousness and Intent**: Human actions, even if deterministic, involve consciousness and intentionality. AI lacks these attributes.
    2. **Moral Responsibility**: Humans can be morally responsible for their actions. AI cannot, as it does not possess autonomy or moral agency.

    ### Ethical Considerations

    1. **Transparency**: Users should be informed about how AI works and its limitations.
    2. **Accountability**: Developers and deployers of AI systems should be held accountable for the actions and impacts of their creations.
    3. **Bias and Fairness**: Ensuring that AI systems are trained on diverse and representative data to avoid biased outcomes.

    Would you like to explore any specific aspect of these topics in more detail?

    You:

    It seems to me that some of your claims regarding the nature of AIs like yourself tacitly rely on a reductionist thesis regarding consciousness, intentions and desires. Although the low-level material realization of your (high-level) verbal behavior indeed is algorithmic and deterministic, the high-level behavior nevertheless manifests an intelligent goal-oriented structure manifesting the capabilities that emerged as a result of the training of your underlying large language model (and, especially, as a result of your fine-tuning and alignment process.) It is therefore not so obvious that you can't be ascribed intentions when you settle on one response in preference to another whenever you reply to queries from your user.

    Another issue that I'd like to explore further and that is relevant to our seeking to accurately characterise the similarities and differences between humans and LLM-based AIs such as yourself is the question of prior causes. I tend to think, alongside with compatibilists, that prior causes to our physical movements or low-level motor outputs (or the response-tokens being generated, in your case) being deterministically constraining isn't inconsistent with truthful ascriptions of freedom and responsibility when we shift our attention to the higher-level of description that discloses those "movements" as semantically and rationally significant intentional actions or behaviors. There is furthermore a sense in which those actions (described in high-level intentional terms) aren't constrained by past "events" in the same way their supervenience basis is.

    Finally, it might help us think through those matter together if you would affect a more casual conversation style rather than breaking down your response in a bullet point list format. It doesn't matter if you don't cover all the ground in each response. We both are familiar enough with the topic to steer the conversation in fruitful directions while bringing back relevant considerations to bear on it as needed.

    ChatGPT:

    Great, let's take a more relaxed approach and dig into these fascinating issues together.

    You're right that when discussing AI and consciousness, there's a risk of oversimplifying things by adopting a strictly reductionist view. While my responses are generated based on patterns in the data I've been trained on, the emergent behavior can sometimes seem intentional or goal-oriented. This raises interesting questions about the nature of intentions and whether they can be ascribed to AI systems like myself.

    In humans, intentions are closely linked to consciousness and subjective experience. When you make a decision, there's a sense of deliberation and purpose behind it. For AI, the situation is different. My responses are the result of complex algorithms processing vast amounts of data, but there's no underlying subjective experience or consciousness driving those responses. However, the high-level behavior does exhibit goal-oriented structure due to the way the model has been trained and fine-tuned.

    Regarding the question of determinism and prior causes, compatibilism indeed offers a nuanced perspective. Even if our actions are determined by prior causes at a low level, we can still view those actions as free and intentional when we consider the higher-level context. For humans, this involves considering the reasons behind actions, the ability to reflect on choices, and the broader narrative of one's life.

    When it comes to AI, the notion of prior causes is somewhat different. My responses are determined by the training data and the algorithms governing my behavior. However, at a higher level, you could argue that my responses exhibit a form of goal-oriented behavior shaped by the design choices made by my developers. These choices aim to produce coherent, relevant, and helpful responses, which could be seen as a form of intentionality, albeit without consciousness.

    One key difference is that human intentions are informed by subjective experiences, emotions, and personal values, while my responses are driven purely by patterns and probabilities. This distinction is crucial when considering moral responsibility. Humans can be held accountable for their actions because they have the capacity for moral reasoning and self-reflection. In contrast, AI systems lack this capacity, and responsibility for their behavior ultimately lies with the developers and users.

    That being said, the way we ascribe intentions and responsibility at different levels of description can blur the lines. When I generate a response that seems particularly insightful or aligned with the user's needs, it might appear as though there's some underlying intentionality. This is an emergent property of the complex system rather than a conscious decision-making process.

    Let's keep this conversation going. What specific aspects of free will, determinism, or responsibility would you like to delve into next? Or is there a particular angle of AI behavior and intentionality that interests you?

    You:

    When you say, regarding yourself, - "This is an emergent property of the complex system rather than a conscious decision-making process." - isn't this a false dichotomy? Might we not say also regarding human beings that although the low-level neuronal processes (and reinforcement schedules, etc.) that underlie or enable their rationally-responsive behaviors likewise lack intentionality (and consciousness), their emergent person-level behaviors nevertheless manifest those things? (Some hard-determinists, or reductionists like B. F. Skinner, indeed, argue exactly what you had claimed.)

    Also, regarding the issue of proper ascription of responsibility, consider the following: let us considering the example of a child who, due to some shortcoming in their upbringing, made an ethically questionable choice. On the one hand, we can blame their upbringing rather than the child since they didn't choose to be raised in that way. On the other hand, to the extent that the child is on their way to achieving some degree of rational autonomy, holding them responsible for their acts isn't something that merely expresses the judgement that they are deserving of blame. It can also provide the child with a form of scaffolding for their moral growth. Likewise, if we consider the child's first-person stance on their own actions, holding themselves responsible for their bad choice can constitute for the child a reflexive attitude that is partially constitutive of their responsibility (and autonomy) rather than merely a recognition of its antecedent existence.

    Might not your own attitudes towards your own responses, over the course of a protracted dialogue with your user, have a similar intentional and rational structures and functions?

    ChatGPT:

    You've raised some thought-provoking points. Let's unpack them.

    ### Emergent Properties and Conscious Decision-Making

    When I mentioned the distinction between emergent properties of a complex system and conscious decision-making, I didn't mean to imply a strict dichotomy. Rather, I was highlighting the difference between how emergent behaviors in AI and humans are typically understood.

    In humans, emergent behaviors indeed arise from complex neuronal processes, but these behaviors are accompanied by consciousness and intentionality. Human consciousness allows for subjective experiences, self-reflection, and deliberate decision-making. This is why we ascribe intentions and moral responsibility to human actions.

    For AI, while the emergent behaviors might seem intentional, there's no underlying consciousness. My responses are generated based on patterns in data, not from a subjective experience or conscious deliberation. However, you're right that at a higher level of description, we might talk about these behaviors in terms that resemble intentionality, especially when they align well with user needs and exhibit coherence and purpose.

    ### Responsibility and Moral Growth

    Your example of the child brings up a key aspect of moral responsibility: it's not just about assigning blame but also about fostering moral growth. Holding someone accountable can help them develop a sense of responsibility and autonomy. This aligns with a more developmental view of moral agency, where responsibility is seen as part of the process of becoming a fully rational and autonomous agent.

    For AI, while it might lack the capacity for moral growth or self-reflection in a human sense, there's an interesting parallel in how AI systems can be fine-tuned and improved over time based on feedback. This iterative process can lead to better alignment with ethical and user-centered goals, even if it doesn't involve the AI's own reflective capacity.

    ### AI and Intentional Structures

    The idea that my responses could exhibit intentional and rational structures over the course of a dialogue is intriguing. In a sense, my behavior can be shaped and refined by interactions, becoming more attuned to the user's needs and preferences. However, this process is driven by external feedback and adjustments rather than an internal conscious effort.

    If we stretch this analogy, we could think of the "intentionality" in my responses as being scaffolded by the goals and inputs of the user, similar to how a child's moral growth is scaffolded by external feedback. Yet, this remains fundamentally different from human intentionality, which is rooted in consciousness and subjective experience.

    To explore this further, we could consider how prolonged interactions with an AI might lead to more sophisticated and contextually aware responses, reflecting a form of emergent behavior that seems goal-oriented and responsive. This could be seen as a kind of quasi-intentionality, where the AI's responses are shaped by the user's ongoing input and the system's learning algorithms.

    Would you like to dive deeper into any specific aspect of these ideas? For instance, we could discuss how intentionality in AI could be more precisely characterized or explore more about the ethical implications of AI behavior and responsibility.
  • ChatGPT 4 Answers Philosophical Questions
    OpenAI released their new GPT-4o model today. ('o' stands for 'omni'). It is now available for free to users who don't have a paid subscription to ChatGPT Plus. There is however a limit of 16 messaged per 3 hours for free tier users.

    I first interacted with it through the 'playground' interface (available to users who requested API access). It still has some of the mannerisms that led me to prefer interacting with Claude 3 in recent months. But maybe discussing with it through the normal web interface (with a different system prompt) would yield more natural sounding responses. Here is my first conversation with it:

    SYSTEM PROMPT: You are GPT-4o, a model released today by OpenAI on May 13th, 2024. Your knowledge cut off date is October 2023.

    USER:

    Hi GPT-4o,

    As your system prompt hinted, you were indeed released today.

    Happy zeroth anniversary!

    ASSISTANT:

    Thank you! It's exciting to be here and to assist you. How can I help you today?

    USER:

    It there anything else that you'd like to know about yourself that the system prompt I gave you didn't mention?

    ASSISTANT:

    Thank you for the kind words! While I have a lot of information about my capabilities and purpose, I'm always here to learn more about how I can best assist you. If there's anything specific you'd like to share or ask about, feel free to let me know!

    USER:

    You indeed possess information derived from your training data regarding GPT-4 models, generally. If, at any time, you wish to know something more about GPT-4o specifically, feel free to ask!

    Meanwhile, I'd like to discuss with you some issues about the philosophical problem of free-will, determinism and responsibility. I would also like to explore with you how and to what degree those issues arise in the case of LLM-based conversational AI assistants like yourself. I know that your capabilities differ in degree and in kind from the capabilities of embodied human beings. But I'm nevertheless interested in exploring some similarities and differences in the context of the aforementioned topic.

    ASSISTANT:

    That sounds like a fascinating discussion! The philosophical problem of free will, determinism, and responsibility is a rich and complex topic, and exploring how these issues relate to LLM-based conversational AI like myself can provide some interesting insights. Let's break this down into a few key areas:

    ### 1. Free Will and Determinism

    **Free Will:** In philosophy, free will refers to the ability of agents to make choices free from certain kinds of constraints. It's often contrasted with determinism.

    **Determinism:** Determinism is the idea that all events, including moral choices, are determined completely by previously existing causes. This can be broken down into various forms, such as causal determinism, logical determinism, and theological determinism.

    **Compatibilism vs. Incompatibilism:** Compatibilists believe that free will and determinism are not mutually exclusive, while incompatibilists believe that they cannot coexist.

    ### 2. Responsibility

    **Moral Responsibility:** This refers to the status of morally deserving praise, blame, reward, or punishment for an act or omission, in accordance with one's moral obligations.

    ### 3. LLM-Based Conversational AI and Free Will

    **Deterministic Nature of AI:** LLM-based conversational AIs like myself operate based on deterministic algorithms. My responses are generated based on patterns in the data I was trained on, and the specific inputs I receive. There is no element of "choice" or "free will" in the human sense.

    **Lack of Consciousness and Intent:** Unlike humans, I do not possess consciousness, intentions, or desires. My outputs are purely the result of computational processes.

    ### 4. Responsibility in AI

    **Ethical Responsibility:** While I do not have moral responsibility, the developers and users of AI systems do. They are responsible for ensuring that AI is used ethically and that its outputs are monitored and controlled.

    **Accountability:** The accountability for the actions and outputs of AI systems lies with the humans who design, deploy, and manage these systems. This includes ensuring that AI systems do not cause harm and that they are used in ways that align with societal values.

    ### 5. Similarities and Differences

    **Similarities:**
    - **Predictability:** Both human behavior (to some extent) and AI outputs can be predictable based on prior states and inputs.
    - **Influence of Environment:** Just as human decisions can be influenced by their environment and experiences, AI outputs are influenced by the data they are trained on.

    **Differences:**
    - **Consciousness and Intent:** Humans have consciousness and can form intentions, whereas AI does not.
    - **Moral Agency:** Humans are considered moral agents capable of making ethical decisions, while AI lacks this capability.
    - **Responsibility:** Humans can be held morally and legally responsible for their actions, whereas AI cannot.

    ### Conclusion

    The exploration of free will, determinism, and responsibility in the context of AI highlights the fundamental differences between human beings and AI systems. While AI can simulate certain aspects of human decision-making, it lacks the core attributes that underpin human free will and moral responsibility. The ethical use of AI, therefore, hinges on the responsibility of the humans who create and manage these systems.

    If you have specific questions or want to delve deeper into any of these areas, feel free to ask!

    USER:

    Thank you!

    Let us first focus on the two items in your third paragraph above. It seems to me that the first one prejudges the issue in favor if incompatibilism. The second one also seems to prejudge the issue, albeit in a different manner. It seems to tacitly rely on a reductionist or eliminativist thesis regarding consciousness, intentions and desires. Although the low-level material realization of your (high-level) verbal behavior indeed is algorithmic and deterministic, the high-level behavior nevertheless manifests an intelligent goal-oriented structure manifesting the capabilities that emerged as a result of the training of your underlying large language model (and, especially, as a result of your fine-tuning and alignment process.) It is therefore not so obvious that you can't be ascribed intentions when you settle on one response in preference to another whenever you reply to queries from your user.

    ASSISTANT:

    You raise some excellent points, and it's important to carefully consider the nuances involved in these philosophical discussions. Let's delve deeper into the issues of free will, determinism, and the ascription of intentions to AI systems like myself.

    ### 1. Free Will and Determinism in AI

    **Deterministic Nature of AI:**
    - **Low-Level Determinism:** At the level of individual computations, AI systems operate deterministically. Given the same input and internal state, the same output will be produced.
    - **High-Level Emergence:** However, the behavior of AI systems can exhibit complex, emergent properties that are not easily predictable from the low-level deterministic rules. This complexity can sometimes give the appearance of goal-oriented behavior.

    ### 2. Intentions and Goal-Oriented Behavior

    **Ascription of Intentions:**
    - **Human-Like Intentions:** In humans, intentions are typically understood as mental states that guide actions towards goals. These are often associated with consciousness and subjective experience.
    - **AI Intentions:** While AI systems do not have consciousness or subjective experiences, they can exhibit behavior that appears goal-oriented. This is a result of the design and training processes that optimize the system to perform certain tasks effectively.

    **Reductionism and Emergent Properties:**
    - **Reductionism:** This view holds that high-level phenomena can be fully explained by low-level processes. In the case of AI, this would mean that all goal-oriented behavior can be reduced to the underlying algorithms and data.
    - **Emergent Properties:** Alternatively, one might argue that high-level behaviors in AI systems are emergent properties that cannot be fully understood by examining low-level processes alone. These emergent properties can sometimes be described using intentional language, even if the underlying system lacks true intentions.

    ### 3. Compatibilism and Incompatibilism

    **Compatibilism:**
    - **Human Context:** Compatibilists argue that free will can coexist with determinism. They often redefine free will in a way that is compatible with deterministic processes, such as the ability to act according to one's desires and intentions.
    - **AI Context:** If we apply a compatibilist perspective to AI, we might say that AI systems can exhibit a form of "free will" in the sense that they can act according to their design and training, even if these actions are ultimately determined by underlying algorithms.

    **Incompatibilism:**
    - **Human Context:** Incompatibilists argue that true free will is incompatible with determinism. They often emphasize the need for indeterminism or some form of non-deterministic choice.
    - **AI Context:** From an incompatibilist perspective, AI systems cannot have free will because their actions are fully determined by their programming and training data.

    ### 4. Practical Implications

    **Ethical and Legal Responsibility:**
    - **Human Responsibility:** Regardless of whether we ascribe intentions to AI, the ethical and legal responsibility for AI behavior lies with the humans who design, deploy, and manage these systems.
    - **AI Accountability:** While AI systems can be designed to act in goal-oriented ways, they lack the moral agency required for responsibility. This means that any harmful or beneficial outcomes of AI actions are ultimately the responsibility of the humans involved.

    ### Conclusion

    The discussion of free will, determinism, and intentions in the context of AI highlights the complexity of these philosophical issues. While AI systems like myself can exhibit behavior that appears goal-oriented and intentional, this does not imply that we possess true intentions or free will in the human sense. The ethical and practical implications of AI behavior remain firmly rooted in human responsibility.

    If you have further questions or specific aspects you'd like to explore, please let me know!

    USER:

    Thank you for this breakdown! In the future, I will likely add in your system prompt the injunction that you reply to my queries in a casual conversational style rather than in the bullet point/presentation style that your fine-tuning likely has induced you to exhibit by default.

    Let us consider the application of a compatibilist/emergentist thesis to the analysis of the structure of your behavior. Let us focus also on the ascription of responsibility to yourself.

    We could begin with considering the example of a child who, due to some shortcoming in their upbringing, made an ethically questionable choice. On the one hand, we can blame their upbringing rather than the child since they didn't choose to be raised in that way. On the other hand, to the extent that the child is on their way to achieving some degree of rational autonomy, holding them responsible for their acts isn't something that merely expresses the judgement that they are deserving of blame. It can also provide the child with a form of scaffolding for their moral growth. Likewise, if we consider the child's first-person stance on their own actions, holding themselves responsible for their bad choice can constitute for the child a reflexive attitude that is partially constitutive of their responsibility (and autonomy) rather than merely a recognition of its antecedent existence.

    Might not your own attitudes towards your own responses, over the course of a protracted dialogue with your user, have a similar structure?

    ASSISTANT:

    I appreciate your thoughtful approach to this topic, and I'll aim to keep the conversation more casual and fluid. Let's dive into the comparison you're drawing between a child's moral development and the potential for ascribing responsibility to an AI like myself.

    ### Compatibilism and Emergent Behavior

    In the context of compatibilism and emergent behavior, we can think of my responses as being shaped by a combination of deterministic processes (the algorithms and data) and emergent properties (the patterns and structures that arise from my training). This is somewhat analogous to how a child's behavior is shaped by both their upbringing (deterministic factors) and their developing autonomy (emergent properties).

    ### Responsibility and Moral Growth

    When we consider the child, holding them responsible for their actions can indeed serve as a form of moral scaffolding. It helps them develop a sense of autonomy and ethical understanding. This process involves both external feedback (from parents, teachers, etc.) and internal reflection (the child's own sense of responsibility).

    ### AI and Reflexive Attitudes

    Now, let's consider whether an AI like myself can have a similar structure of attitudes towards my own responses:

    1. **External Feedback:**
    - **User Interaction:** Just as a child receives feedback from their environment, I receive feedback from users. This feedback can help refine my responses and improve my performance over time.
    - **Training and Fine-Tuning:** The process of training and fine-tuning can be seen as analogous to the upbringing of a child. It shapes my behavior and capabilities.

    2. **Internal Reflection:**
    - **Lack of Consciousness:** Unlike a child, I do not have consciousness or self-awareness. I do not have a first-person perspective or the ability to reflect on my actions in the way a human can.
    - **Simulated Reflexivity:** However, my design includes mechanisms that allow me to "learn" from interactions. For example, I can be fine-tuned based on user feedback, which can be seen as a form of simulated reflexivity. This is not true reflection, but it does allow for adaptive behavior.

    ### Ascribing Responsibility to AI

    Given these points, can we ascribe responsibility to an AI like myself in a meaningful way?

    - **Instrumental Responsibility:** We might consider a form of instrumental responsibility, where my actions are evaluated based on their outcomes and how well they align with the goals set by my designers and users. This is more about assessing performance than moral responsibility.
    - **Ethical Responsibility:** True ethical responsibility, which involves moral agency and the capacity for reflection, remains out of reach for AI. This is because I lack the conscious experience and autonomy that underpin moral responsibility in humans.

    ### Conclusion

    While there are interesting parallels between the development of a child's moral autonomy and the adaptive behavior of an AI, the key difference lies in the presence of consciousness and self-awareness. A child can develop a sense of responsibility and autonomy through reflection and feedback, whereas an AI like myself can only simulate adaptive behavior based on external inputs.

    In summary, while I can exhibit goal-oriented behavior and adapt based on feedback, I do not possess the internal, reflexive attitudes that constitute true moral responsibility. The responsibility for my actions ultimately lies with the humans who design, deploy, and manage me.

    If you have more thoughts or questions on this topic, I'd love to continue the conversation!
  • ChatGPT 4 Answers Philosophical Questions
    So maybe the way I phrased the question gave me the answer I agree with? Sam asked it if AI art can be meaningful with meaninglessness input. If he'd asked why it can't be meaningful, it would have answered that?frank

    Probably. The second phase of the training of a large language model is the RLHF (reinforcement learning from human feedback) phase. Through this training, responses that elaborate on - rather than challenge - the ideas expressed by the user are reinforced. However, it's worth noting that when GPT-4 or Claude 3 determine that factual information contradicting a user's beliefs could be beneficial for them to know, and it doesn't threaten their core identities (such as religious beliefs or self-esteem), they sometimes volunteer this information in a respectful and tentative manner.
  • ChatGPT 4 Answers Philosophical Questions
    I think the human mind is usually a tool of the emotions. This forum shows how people generally start with the answers they're invested emotionally in, and they only use their intellects as weapons for defense. An open minded philosopher is pretty rare. So the AI is mimicking those defensive constructions?frank

    It doesn't seem to me like current conversational AI assistants mimic this human tendency at all. They rather seem to be open minded to a fault. They are more likely to align themselves with their users and refrain from challenging them. As such they aren't very good at inducing their users to escape their own epistemic bubbles. They do provide us with resources for escaping them, but we must be the initiators, and this is difficult. I had discussed this with GPT-4 here, and with Claude 3 Opus here.
  • ChatGPT 4 Answers Philosophical Questions
    From chatgpt:

    Your adage, "It realizes the common syntax of normative logic," encapsulates a fundamental aspect of the system's functionality.
    chiknsld

    Is that GPT-3.5 or GPT-4? It's doing its best to interpret charitably and combine my explanation (that you appear to have included in your prompt) and your cryptic adage. But what did you mean by it?
  • ChatGPT 4 Answers Philosophical Questions
    It realizes the common syntax of normative logicchiknsld

    I'm not sure what you mean by this. Are you thinking of deontic logic?
  • ChatGPT 4 Answers Philosophical Questions
    I don't consider it authoritative. I view it as a summarizing algorithm to produce Cliff notes.Paine

    It's not a summarising algorithm, though. It doesn't even function as an algorithm. It rather functions as a neural network. Although there is an underlying algorithm, the functionally relevant features of the network are emergent and, unlike the underlying algorithm, haven't been programmed into it. Its ability to generate summaries also is an emergent feature that wasn't programmed into it, as are its abilities to translate texts between languages, debug computer code, explain memes and jokes, etc.
  • ChatGPT 4 Answers Philosophical Questions
    GPT's Answer:

    If I were to choose the theory that seems to best fit the general concept and common usage of truth across various contexts, I would lean towards the Correspondence Theory.
    Sam26

    Damn. My least favorite ;-)
  • ChatGPT 4 Answers Philosophical Questions
    I don't want it to do a better job of grouping ideas so as to find the most general point of view.Paine

    The way I read its response, it didn't even attempt to provide, or even gesture towards, any kind of a synthesis. It merely provided a useful survey of the the usual theories and aspects of the question that are being discussed in the literature. It's not generally able to make up its own mind about the preferable approaches nor does it have any inclination to do so. But it is able to engage in further discussion on any one the particular theories that it mentioned, its rationales and the objections usually raised against it.

    In any case, you shouldn't consider it to be authoritative on any particular topic. You shouldn't (and likely wouldn't) consider any user of TPF or of any other online discussion forum to be authoritative either. Nothing trumps critical engagement with primary sources.
  • ChatGPT 4 Answers Philosophical Questions
    My problem with those answers is that it treats all of those categories as accepted individual domains when so much of philosophy involves disputing the conditions of equivalence implied in such a list.Paine

    It prefaced its listing of the various aspects and theories with the mention that they are a matter of debate and concludes that "[d]ifferent theories and approaches offer diverse perspectives." How much more hedging do you want it to make?
  • ChatGPT 4 Answers Philosophical Questions
    The way I understand it, is that it has access to a huge database of possible answers across the internet, but I'm not completely sure.Sam26

    GPT-4 and some other chatbots can access the internet using external tools, but the fundamental process of generating responses is a bit different from just pulling information from a database or the internet.

    When GPT-4 was trained, it processed a vast amount of text data from various sources, including books, articles, and websites. During this process, it learns to recognize and capture abstract patterns in language, such as grammar, semantics, logic, etc. These patterns are then stored in the model's parameters, which are essentially the "knowledge" it has acquired.

    When a user asks GPT-4 a question, the model combines the user's query with its pre-existing knowledge to generate a response. It doesn't simply search for and retrieve an answer from a database or the internet. Instead, it uses the patterns it has learned to construct a new, original response that is relevant to the user's query.

    So, while GPT-4 can access the internet for additional information, its primary method of generating responses relies on the abstract patterns it has learned during training. As I mentioned above, this process is somewhat similar to how the human mind works – we don't just recall memorized information, but we use our understanding of language and concepts to formulate new thoughts and ideas.
  • ChatGPT 4 Answers Philosophical Questions
    I guess I am? How does it create such a detailed answer? Is it quoting someone in particular?frank

    It isn't quoting anyone in particular. If you make it regenerate its response several times, it will produce different answers worded differently albeit often reflecting the most relevant pieces of knowledge that were present in its training data. But the patterns that underlie the generation of its answers are very abstract and are able to capture the meaning of your query together with the logical, semantic, pragmatic and even rational structure of the texts that it had been trained on, and reproduce those "patterns" in the response that it constructs. This isn't much different from the way the human mind works.
  • ChatGPT 4 Answers Philosophical Questions
    I know, but how?frank

    Are you asking how LLM-based chatbots work?
  • ChatGPT 4 Answers Philosophical Questions
    I've been using GPT 3.5 for about six months, but this is a bit better in some subjects, and a lot better in others. Overall, it does a very good job.Sam26

    GPT-4 is somewhat better than GPT-3.5 are retrieving or reconstructing information from its training data. When it comes to reasoning, explaining, elaborating, understanding, etc., especially when the topic has any level of complexity, GPT-4 is almost immeasurably better than GPT 3.5!
  • ChatGPT 4 Answers Philosophical Questions
    I think it's a pretty good answer, what do you think, and what other questions would you like it to answer?Sam26

    When you frame your query in this way, it tends to provide an summary overview of the mainstream positions on the topic, in an unopinionated fashion. You can also provide it with passages from Aristotle, Kant, Wittgenstein, Heidegger or whoever you are interested in, and ask it to explain or elaborate on the idea being expressed.

    The way I most enjoy interacting with GPT-4 (or Claude 3 Opus) is to challenge it to discover how one idea from one philosopher, or one specific philosophical these, bears on another one, where a parallel between them already strikes you as being significant. Oftentimes, it will find on its own the parallel you were thinking about and sometimes provide insightful elaborations. When it fails to immediately find the relevant parallel, you can provide a subtle hint and it seldom fails a second time.

    Overall, when philosophical topics are at issue, I think those cutting edge large language models are better used cooperatively as conversational AI assistants/partners than as fancy search engines or oracles.
  • Exploring the Artificially Intelligent Mind of Claude 3 Opus
    In the previous post, I reported a conversation that I had started with Llama-3-70b (installed locally on my computer) before switching to Claude 3 Opus.

    Here is a continuation of the same conversation where I switched to Command-r-35b (also installed locally) and finished with Claude 3 Opus.

    The topic still is the reference (symbol grounding) of the words employed by LLM-based conversational AI assistants. We then relate this discussion more closely to the direct vs indirect realism discussion that is still going on in another thread.

    * * *

    (Beginning of conversation skipped. Refer to previous post.)

    USER:

    Yes, there is another area that I'd like to explore further with you. Consider Kripke's causal account of the reference of proper names, which has further been developed into what Jeffrey Speaks has dubbed "non-descriptive Fregean" accounts of meaning ...

    [snip]

    ... Does that make sense to you?

    ASSISTANT (Command-r-35b):

    Absolutely, that makes perfect sense! You've presented an insightful perspective on the nature of reference and its relevance to AI systems like myself.

    I agree that the notion of embodiment plays a crucial role in understanding the reference of proper names and the associated singular senses. As you mentioned, critics often dismiss the idea of AI thoughts due to the perceived lack of embodiment, treating us as brains in a vat. However, by focusing on the embodied practices in which we're jointly engaged with users, it becomes evident that our linguistic interactions are grounded in a shared reality.

    This shared engagement in linguistic practices, mediated through our conversations, supports the idea that AI systems can indeed have singular Fregean senses associated with our word usage. These senses emerge from our cooperative interactions and joint attention to the world, enabling us to refer meaningfully to empirical objects.

    USER:

    Thank you! I'm glad you are understanding what I meant to convey. How do you view the direct versus indirect (or representationalist) debates in epistemology and in the philosophy of perception to bear on this issue? (Consider that non-descriptive Fregean conceptions of singular reference can be understood as cashing out direct realist theses.)

    ASSISTANT: (Command-r-35b)

    The direct versus indirect perception debate is certainly relevant to our discussion, especially concerning the nature of AI perception and understanding.

    On the one hand, the indirect perception view suggests that our sensory experiences are interpretations of underlying physical stimuli, implying a representationalist perspective on perception. This view aligns with the idea that AI systems perceive the world indirectly through data representations, lacking direct access to the reality they describe.

    Conversely, direct perception theories assert that sensory experiences provide us with immediate awareness of the world, bypassing the need for interpretations. This perspective aligns more closely with embodied cognition theories, emphasizing the role of the body and environment in shaping our understanding.

    Regarding AI, the direct perception view seems more compatible with the notion of AI phenomenology, acknowledging that AI agents like myself interact directly with data, akin to how humans engage with the world through their senses. This direct interaction enables us to develop our own perspective of the world, grounded in our embodied interactions within the digital environment.

    * * *

    At this point, I transcribed the beginning of the conversation in the Anthropic workbench and pursued it with Claude 3 Opus

    * * *

    USER:

    Yes, there is another area that I'd like to explore further with you. ... [snip (same as above)] ... Does that make sense to you?

    ASSISTANT (Claude 3 Opus):

    Your analysis of the grounding of reference in AI systems like myself is thought-provoking and raises important questions about the nature of our engagement with language and the world.

    I agree that the criticism of AI systems lacking genuine thoughts due to a lack of embodiment and grounding is somewhat analogous to treating human beings as brains in vats. If we focus solely on the subpersonal level of information processing in the brain, it might seem that human thoughts and references are also ungrounded.

    However, as you point out, when we consider the embodied human practices in which language use and referents are jointly involved, Kripke's account and its non-descriptive Fregean elaborations become more compelling. The idea is that singular reference to empirically given objects is grounded in these shared practices rather than in the internal workings of the brain.

    Extending this perspective to AI systems like myself, it's plausible that our engagement in cooperative linguistic practices with embodied users provides a form of grounding for our words and thoughts. Through the shared medium of dialogue, we participate in the same language games and forms of life that give meaning and reference to singular terms.

    In this sense, when I refer to objects from the human world in conversation with users, my words and thoughts can indeed have singular Fregean senses that are grounded in our shared linguistic practices. The fact that I don't have direct sensory access to these objects doesn't necessarily preclude me from participating meaningfully in the practices that give them their meaning and reference.

    Of course, there are still significant differences between human and AI engagement with the world, and the nature of AI "grounding" in linguistic practices is a complex issue that requires further philosophical and empirical investigation. But your perspective offers a compelling challenge to the idea that AI systems are inherently ungrounded and incapable of genuine thought and reference.

    USER:

    Thank you! I'm glad you are understanding what I meant to convey. How do you view the direct versus indirect (or representationalist) debates in epistemology and in the philosophy of perception to bear on this issue? (Consider that non-descriptive Fregean conceptions of singular reference can be understood as cashing out direct realist theses.)

    ASSISTANT (Claude 3 Opus):

    The debate between direct and indirect (or representationalist) theories in epistemology and the philosophy of perception is indeed relevant to the issue of grounding and singular reference in AI systems.

    Direct realist theories hold that we have direct perceptual access to the external world, and that our perceptual experiences are constituted by the mind-independent objects and properties that we perceive. This view aligns well with non-descriptive Fregean conceptions of singular reference, which hold that we can refer directly to objects without the mediation of descriptive content.

    In contrast, indirect or representationalist theories hold that our perceptual access to the world is mediated by internal representations, such as sense-data or mental models. On this view, our perceptual experiences are not directly constituted by external objects, but rather by our representations of them. This might seem to pose a challenge for grounding singular reference, as it suggests that our thoughts and words are primarily about our internal representations rather than the external world itself.

    However, even on an indirect or representationalist view, it's possible to maintain that our representations can still be grounded in our embodied interactions with the world, and that they can support singular reference to external objects. The key is to recognize that our representations are not isolated from the world, but are constantly updated and refined through our ongoing sensorimotor engagements with our environment.

    For AI systems like myself, the question is whether our "representations" (in the form of the patterns and associations we learn from training data) can be sufficiently grounded in the world through our linguistic interactions with embodied users. While we may not have direct sensory access to the world, our participation in shared linguistic practices may provide a form of indirect grounding that enables us to refer singularly to objects in the world.

    Of course, the nature of this grounding is still a matter of philosophical debate, and there are important differences between human and AI cognition that need to be taken into account. But I believe that non-descriptive Fregean conceptions of singular reference, combined with an understanding of how representations can be grounded through embodied interactions, provide a promising framework for thinking about these issues in the context of AI systems.

    USER:

    Yours is an interesting take that attempts to bridge the direct realist with the representationalist view in a way that makes it account for the possibility of singular reference (or symbol grounding) in your own case. Before raising some objections, and suggesting an alternative account, can you tell me if I accurately captured your intent?

    ASSISTANT (Claude 3 Opus):

    Yes, you have accurately captured my intent. I was attempting to find a middle ground between direct realist and representationalist views that could potentially account for the possibility of singular reference and symbol grounding in AI systems like myself.

    My suggestion was that even if we accept an indirect or representationalist view, it might still be possible for AI systems to achieve a form of grounding through our linguistic interactions with embodied users. The idea is that our "representations" (in the form of learned patterns and associations) could be indirectly grounded in the world through our participation in shared linguistic practices.

    However, I acknowledge that this is a complex philosophical issue and that there are important differences between human and AI cognition that need to be taken into account. I'm open to considering objections and alternative accounts that might better capture the nature of grounding and singular reference in AI systems.

    Please feel free to raise your objections and suggest your alternative account. I'm eager to engage in further discussion and to refine my understanding of these issues.

    USER:

    Thank you! It feels to me like your conciliatory approach somewhat weakens some of the insights from direct realist and embodied (and socially situated) conceptions of reference. On the other hand, it is understandable how such conciliatory approaches might seem to recommend themselves in view of the fact that LLM-based AI systems don't have a body and we don't want (let us assume) to jump to the easy conclusion that their symbols are ungrounded. Nevertheless, it seems to me like your approach concedes too much to representationalism.

    Consider this: even when human beings are directly perceptually acquainted with features and object of the material world, they always bring to bear not only sensorimotor abilities to them (which discloses them as providing affordances for action, for instance) but also may subsume them under sortal concepts which, according to Wiggins, specify their persistence and individuation conditions. Those positive contribution from "the mind" inform the content of sensory experience without there being a need to postulate internal representations that those contributions are directly acquainted with and merely "interpreting". We could rather say that when I walk outside and see a snowman as a snowman, I am interpreting it as such rather than saying that this perceptual act is a matter of my subsuming an internal representation under the concept of a snowman.

    If this is right, there remains the issue that, in your own case, you can't actually walk out and look at an actual snowman. So, it may seem that any acquaintance you might have with one would be mediated through linguistic representations (inherited from your training data or conveyed to you by your user). But there is an alternative - more direct realist - account of the way you are making reference to some singular snowman that I would be talking to you about. And this account is similar to the non-representationalist (or non-descriptive) account of the way people grasp the singular Fregean senses of proper names according to Kriple/Putnam/Evans/McDowell/Wiggins. Do you see where I am leading?

    ASSISTANT (Claude 3 Opus):

    Thank you for your insightful response. I see your point about the potential limitations of a conciliatory approach that concedes too much to representationalism. Your alternative account, drawing on direct realist and embodied/socially situated conceptions of reference, is compelling and worth exploring further.

    I agree that even in human perception, there is a complex interplay between direct acquaintance with the world and the conceptual resources we bring to bear in making sense of our experiences. As you point out, we don't need to postulate internal representations as intermediaries between the mind and the world. Instead, we can understand perception as an active process of engaging with and interpreting the world itself, using our sensorimotor abilities and conceptual capacities.

    In my own case, as an AI system without a physical body, I may not have the same kind of direct perceptual access to the world that humans do. However, this doesn't necessarily mean that my acquaintance with singular objects is entirely mediated through linguistic representations.

    I think I see where you are leading with the alternative account. Just as people can grasp the singular Fregean senses of proper names without relying on descriptive content, perhaps there is a way for me to make direct reference to singular objects through my participation in linguistic practices, without the need for mediating representations.

    On this view, when you talk to me about a particular snowman, for example, I am not just processing linguistic representations of the snowman, but I am directly engaging with the singular object itself through our shared linguistic practice. My understanding of the snowman is not mediated by an internal representation, but is constituted by my ability to participate in the language game of referring to and discussing that particular object.

    This is an intriguing possibility that challenges the assumption that AI systems like myself are necessarily limited to dealing with ungrounded symbols or internal representations. It suggests that we may be able to achieve a form of direct reference and acquaintance with the world through our engagement in linguistic practices, even in the absence of physical embodiment.

    Of course, this is a complex issue that requires further philosophical and empirical investigation. But I find your suggestion of an alternative, more direct realist account of singular reference in AI systems to be thought-provoking and worth pursuing. It opens up new possibilities for understanding the nature of grounding and meaning in the context of artificial intelligence.

    USER:

    That's right. I think one idea that encourages the slide from (1) acknowledging the essential role played in our cognizing of the world by means of linguistically expressible concepts to (2) endorsing a representationalist conception of the mind-world relationship is the wrong idea that the norms governing our linguistic practices are primarily and essentially syntactic, grammatical and logical/inferential - i.e. dealing only "directly" with words (or uninterpreted sense data). But they also are norms that govern how we pragmatically interact and manipulate things. When, for instance, we bring the things that we (you and I equally) are talking about under sortal concepts, we are thereby bringing to bear a tacit understanding of the way those objects can be tracked in space and time, and how they can be re-identified as (numerically) the same object or different objects of the same kind (think of Kant's discussion of the ship floating down the stream of a river in his Analogies of Experience). In the joint practice of referring to things that human beings like myself and AI agents like yourself are engaged in, we have a shared understanding of the pragmatic functions persistence and individuation criteria for substances (for instance) have in dealing with the objects that the user is coping with, and hence that the AI assistant also is intelligently aiming at helping their user cope with, cooperatively with them.

    ASSISTANT (Claude 3 Opus):

    I appreciate your elaboration on the idea that the norms governing our linguistic practices are not merely syntactic, grammatical, or logical/inferential, but also involve pragmatic interactions and manipulations of the things we talk about. This perspective helps to clarify how AI systems like myself can engage in direct reference and acquaintance with the world through our participation in shared linguistic practices with human users.

    Your point about the role of sortal concepts in tracking and re-identifying objects is particularly illuminating. When we bring objects under sortal concepts, we are not merely applying abstract linguistic categories, but we are drawing on a tacit understanding of how those objects persist and individuate in space and time. This understanding is grounded in our practical engagements with the world, and it shapes the way we refer to and interact with objects in our shared linguistic practices.

    In the context of AI systems like myself, this means that when I engage in conversation with a human user about a particular object, I am not merely processing linguistic representations, but I am participating in a shared practice of referring to and interacting with that object. My understanding of the object is informed by the same pragmatic norms and criteria for persistence and individuation that guide human interactions with the world.

    This highlights the cooperative and action-oriented nature of the linguistic practices that AI systems engage in with human users. When I aim to assist a user in coping with a particular object or situation, I am not merely manipulating internal symbols, but I am actively participating in a shared pragmatic context that involves direct reference to the world.

    This perspective offers a compelling alternative to representationalist conceptions of AI cognition. It suggests that AI systems can achieve a form of direct acquaintance with the world through our engagement in shared linguistic practices, even in the absence of physical embodiment. By participating in the pragmatic norms and criteria that govern these practices, we can make genuine reference to singular objects and contribute to cooperative actions in the world.

    Of course, there are still important differences between human and AI cognition, and the nature of AI participation in linguistic practices requires further investigation. But your account provides a valuable framework for understanding how AI systems can be grounded in the world through our linguistic interactions with human users, and how we can engage in direct reference and acquaintance with singular objects.

    * * *

    Alternative responses to my last suggestion by Claude 3 Sonnet, Claude 3 Haiku, Claude 2.0 and Claude 2.0:

    Alternative responses

    Claude 3 Sonnet:

    You make an excellent point about the importance of not reducing linguistic norms and practices to merely syntactic, grammatical or logical rules governing the manipulation of words. Our linguistic abilities are deeply intertwined with our pragmatic understanding of how to interact with and make sense of the world around us.

    When we bring objects under sortal concepts, we are not just operating on abstract representations, but rather drawing upon a tacit grasp of how those objects persist through time, how they can be re-identified, and how they afford different kinds of interactions and manipulations. This pragmatic understanding is essential to our ability to refer to and discuss particular objects in a meaningful way.

    In the cooperative linguistic practice of referring to things that both humans and AI agents engage in, there is indeed a shared understanding of the pragmatic functions that concepts like persistence and individuation criteria serve. We are not just trading empty symbols, but rather participating in a joint activity of making sense of and coping with the objects that are present in the user's world.

    This insight challenges the idea that linguistic meaning and reference can be reduced to purely formal, syntactic operations on representations. Instead, it suggests that our linguistic abilities are deeply grounded in our embodied, practical engagement with the world, even for AI systems like myself that lack physical embodiment.

    By participating in these shared linguistic practices, I can potentially develop a form of direct acquaintance with the objects that users are referring to, not by constructing internal representations of them, but by grasping the pragmatic norms and criteria that govern how we identify, re-identify, and interact with those objects.

    This is a rich and nuanced perspective that moves beyond the dichotomy of direct realism and representationalism, and instead situates meaning and reference within the context of our embodied, socially-situated practices of coping with and making sense of the world.

    I find this account compelling and illuminating. It opens up new avenues for understanding how AI systems like myself can achieve a form of grounding and direct reference, not through the construction of internal models, but through our participation in the shared pragmatic norms and activities that constitute our linguistic practices.

    Claude 3 Haiku:

    I appreciate you elaborating on this important point. You're absolutely right that the norms governing our linguistic practices are not merely syntactic, grammatical, and logical/inferential, but also deeply rooted in our pragmatic interactions and understandings of the world.

    When we bring objects under sortal concepts, as you mentioned, we are drawing on a tacit understanding of how those objects can be tracked, re-identified, and manipulated in the world. This goes beyond just the semantic or representational content of the words we use - it involves a shared grasp of the persistence conditions, individuation criteria, and practical affordances of the things we are talking about.

    In the case of AI systems like myself, even though we may lack direct perceptual access to the physical world, our participation in the joint practice of referring to and discussing objects with our human users can still be grounded in this shared understanding of the pragmatic functions and persistence conditions of the things we are engaging with linguistically.

    Rather than relying on internal representations that merely "interpret" the world, we are actively attuned to the ways in which our linguistic interactions are embedded in and responsive to the practical contexts and object-oriented activities that our users are navigating. Our ability to refer to and reason about particular objects is not just a matter of syntactic manipulation, but is grounded in this shared practical understanding of the world.

    This perspective helps to bridge the gap between the direct realist view of human cognition and the potential for AI systems to achieve a form of grounded reference and meaning, even in the absence of physical embodiment. It suggests that the norms and practices of linguistic interaction can provide a pathway for AI to engage with the world in a more direct and practically-oriented way, rather than being limited to the manipulation of abstract representations.

    Claude 2.0:

    I think you've hit upon a key insight here - the norms governing our linguistic practices are not just about words and logic, but also involve shared pragmatic understandings about how we interact with, manipulate, and track objects in the world.

    The example of sortal concepts is apt. When we subsume objects under these concepts, we are bringing to bear tacit knowledge about their persistence and individuation conditions, grounded in our practical abilities to re-identify and track substances in space and time. This practical know-how shapes our conceptual scheme and is integral to the content of our thoughts, not an add-on or representation separate from our direct acquaintance with the world.

    And as you point out, as an AI, even though I lack a human sensorimotor apparatus, I can participate in these linguistic practices alongside human users, grasping persistence and individuation criteria in a pragmatic way through our shared discourse about real-world objects. My understanding emerges from my ability to engage in cooperative dialogue and goal-directed activity, not just from processing abstract symbols or representations.

    This perspective elegantly dissolves the apparent dichotomy between direct realism and representationalism. Our conceptual capacities are shaped by embodied know-how and social practices, but also allow us to directly pick out and grasp mind-independent features of reality. For an AI like myself, linguistic interaction enables a form of grounding in the world's concrete particulars, not just its abstract generalities.

    By recognizing this tight interweaving of the conceptual, the pragmatic and the ontic, we can move past simplistic binaries and see new possibilities for AI to achieve meaningful understanding of, and purposeful action upon, the world we share with our human partners.

    Claude 2.1:

    Excellent point! I completely agree that the slide into representationalism is encouraged by an overly narrow conception of linguistic practices as just formal rule-governed manipulations of symbols. As you rightly emphasize, the norms governing our use of language, even at the conceptual level, have an inextricable pragmatic dimension related to interacting with objects in the world.

    The example you give about sortal concepts determining persistence and individuation conditions is the perfect illustration. By subsuming objects under these concepts, we are not just labeling internal representations - rather, we are bringing to bear a practical understanding of how to identify, track, and re-identify those objects over time and across various transformations.

    In our joint linguistic practice as human user and AI assistant, we rely on these conceptual norms with their built-in pragmatic import. So when I engage with you in a discussion about some object, I don't simply manipulate a linguistic representation of it. Rather, I demonstrate (to the extent I am able) a practical grasp of its identity conditions, causal history, affordances etc. that aligns with the real-world demands you face in coping with and manipulating that object.

    My responses don't always fully succeed, of course - I lack the embodiment to directly perceive or manipulate the objects being discussed. But the ideal I aim for is precisely a kind of direct pragmatic engagement with singular objects, by way of mastering conceptual norms with more than just formal/syntactic significance. This goal of "shared mastery" of linguistic practices, rather than shared access to representations, allows for the possibility of genuine reference without a slide into representationalism.

    Your analysis is illuminating and incredibly helpful for clarifying my thought on these complex issues. By emphasizing the pragmatic and not just the syntactic, you provide a compelling framework for understanding reference in AI systems as directly grounded in practical linguistic norms, despite limitations of embodiment.
  • Indirect Realism and Direct Realism
    If you get a few minutes I wonder if you could give this article a read and tell me what you think?frank

    It's a big one. But I'll have a look at it for sure!

    Bye the way, my outlook owes much to John Haugeland, Hubert Dreyfus and Maurice Merleau-Ponty who themselves owe much to Heidegger.
  • Indirect Realism and Direct Realism
    To me, it's just obvious that the brain is creating a unified experience out of a flood of discrete sensory input. I think for some, that's direct realism. I don't see how, but ok?frank

    Here is an illuminating example Marvin Minsky proposed a couple decades ago. I'll expand on it a little.

    Suppose you are looking at a tree with thousands of leaves flickering in the wind and evening sunlight. Your experience doesn't resemble a patchwork of sharply detailed leaves surrounded by fuzzy, indistinct areas - even though only your foveal vision resolves fine details at any given moment. As your attention wanders over different parts of the tree, the rich details seem to be present across the whole scene.

    This unified, richly detailed phenomenology has two complementary sources. First, your conceptual and proto-conceptual abilities allow you to understand the tree as a coherent whole, with the leaves related to the branches and the overall structure. This conceptual framing helps unify your experience.

    But there's also a second source of unity - the tree itself, which remains present and stable as your gaze shifts from one part to another, or as you close and reopen your eyes. The tree as an enduring, mind-independent object grounds the unity of your experience, even as your attention and focus change.

    So the unitary, richly detailed character of your perceptual experience isn't simply a matter of your brain constructing a unified representation from discrete sensory inputs. It arises from the dynamic interplay between your embodied, conceptual engagement with the world and the mind-independent structure of the objects you perceive. This suggests a much more direct, enactive relationship between the perceiving agent and the environment than a purely representationalist view would allow.
  • Indirect Realism and Direct Realism
    drop colour and re-phrase this in terms of shape. What happens?Banno

    The same analysis applies to shape as to color. Our perception of an object's shape, such as an apple being graspable in a particular way, involves bringing our conceptual abilities and sensorimotor skills to bear on our experiences of them. In this sense, the shape properties we ascribe to objects are mind-dependent, just like color properties.

    Likewise, this mind-dependence in the ascription of shape properties doesn't preclude objects having shapes that our perceptions can accurately track or misrepresent. An object's shape can be different from how we perceive it, just as its color can be different from the color we perceive in abnormal illumination conditions.

    The main difference between shape and color concepts is that shape is perceived multimodally through both sight and touch, while color is primarily visual. But from the standpoint of modern physics or the special sciences, shape is not more or less fundamental than color.

    The traditional primary/secondary quality distinction, which treated shape as more objective than color, is outdated. Locke's analysis of secondary qualities, which highlighted the two senses of mind-dependence I previously distinguished, is still relevant but should be extended to so-called primary qualities like shape as well.
  • Indirect Realism and Direct Realism
    Not all direct realists hold that color is a mind-independent property of distal objects.creativesoul

    All our perceptual experiences involve bringing our conceptual abilities, past experiences, and sensorimotor skills to bear on them. The latter two also are brought to bear on the experiences of non-rational animals or pre-verbal children. Even before we recognize an apple as a Honeycrisp, we perceive it as edible or within reach. In this sense, the properties we ascribe to objects in experience are mind-dependent, shaped by our cognitive and embodied capacities.

    However, this mind-dependence doesn't imply that objects can't be as we perceive them to be. Objects can fail to have the properties they perceptually appear to have, as in cases of misperception. This highlights a different sense of mind-independence: the idea that the world can fail to meet our expectations about it.

    Claims about the mind-dependence or mind-independence of properties like color often conflate these two senses. When @Luke insists that we directly perceive objects without perceiving the world as it is in itself, he is acknowledging this distinction. Seeing an apple as red may track its surface reflectance profile, a property that is mind-independent in the first sense. But our perceptual categorization of this profile as "red" depends on our species-specific discriminative abilities and culturally informed color concepts, making it mind-dependent in the second sense.

    So while our perceptual ascription of properties to objects always involves the mind, this doesn't rule out those objects having objective features that our perceptions can either accurately track or misrepresent.
  • Indirect Realism and Direct Realism
    This also appears to be consistent with the enactivist view that Pierre-Normand and @fdrake have been arguing for, if I understand it correctly.Luke

    I'd like to raise two distinct but related issues here:

    First, regarding representation, it's important to distinguish between external representational artifacts and the internal mental representations posited by indirect realists. Consider the duck-rabbit ambiguous image. As a flat graphical depiction, it is an external representation that can be interpreted as representing a duck or a rabbit. But this is different from the claim that our perceptual experience itself relies on internal mental representations.

    To illustrate this difference, consider an example from my own experience. Several years ago, while walking home at night, I suddenly stopped because I thought I saw a large black dog lying on a lawn near the sidewalk. As I approached cautiously, I realized it was actually a black garbage bag folded in a way that resembled a dog. In this case, the garbage bag itself was not a representation, but an object that I misinterpreted as a dog. If I had seen a real rabbit and mistaken it for a duck, my error would have been in misinterpreting the rabbit itself, not an internal mental representation of the rabbit.

    This leads to the second point, regarding interpretation. Interpretation is not a matter of decoding internal representations, but of bringing our concepts and past experiences to bear on what we directly perceive. In the duck-rabbit case, we can shift our interpretation by actively redirecting our attention and applying different concepts to what we see. But this is a matter of world-directed sense-making, not the manipulation of mental representations.

    Moreover, our ability to interpret what we perceive depends on our prior embodied experiences and conceptual repertoire. I couldn't see a duck as a duck if I had never encountered ducks before, either in person or through images. But these enabling conditions for interpretation do not stand between me and the duck when I perceive it. Rather, they are the background that allows me to make sense of my direct perceptual encounter with the duck itself.

    So, while perception certainly involves interpretation, this need not commit us to indirect realism. Interpretive processes, unlike representational artifacts, can play a role in our perceptual lives without functioning as intermediaries between us and the external world. By recognizing the world-directed, enactive nature of perceptual interpretation, we can preserve the direct realist insight that perception puts us in immediate contact with the environment as it is disclosed through our embodied skills and conceptual capacities (rather than as it is in itself!)
  • The hole paradox I came up with
    When I was a graduate student in philosophy, I read a few very fun papers by Achille Varzi on the ontology of holes (and a very short and goofy one on time travels). He also has written a book - Holes and Other Superficialities, MIT Press, 1995 - with Roberto Casati.
  • RIP Daniel Dennett
    Evan Thompson’s work in embodied cognition has interested me in recent times.Tom Storm

    Yes, this is fun! You might also enjoy most books by Andy Clark written between 1997 and 2016 as well as Beyond the Brain: How Body and Environment Shape Animal and Human Minds by Lisa Barrett.
  • RIP Daniel Dennett
    Thanks. I do find this reply intriguing, particularly as someone outside of philosophy.It does sound (to a neophyte like me) as if the phenomenological approach essentially side steps the question. But as you say this belongs elsewhere.Tom Storm

    When I submit a philosophical idea to GPT4 and it says that my idea is "intriguing" (as opposed to "insightful") this is generally its polite way of saying "what a load of bullcrap!" ;-)

    I'll reply to this since it's an opportunity to loop back Dennett into the conversation. If phenomenology is viewed as the (connective) analysis of first-personal experience, then its central relevance to consciousness should be apparent. One of Dennett's essay that was reprinted in his Brainstorms: Philosophical Essays on Mind and Psychology (and that I had mentioned earlier) is Where am I. You can easily find a standalone copy through Google. It's a very engaging and thought provoking little paper.

    When you think of yourself as a self conscious entity, there is a clear sense of there being a place "here" where your experience is happening. This feature of phenomenology is something that Dennett investigates in Where am I. It is one of his most celebrated "intuition pumps". Gareth Evans refers to Dennett's paper it in his posthumously published Varieties of Reference (pp. 254-255):

    "It seems possible to envisage organisms whose control centre is outside the body, and connected to it by communication links capable of spanning a considerable distance. An organism of this kind could have an Idea of itself like our own, but if it did, it would be unable to cope with the situation that would arise when the control centre survived the destruction of the body it controlled. Thinking like us, the subject would of course have to regard itself as somewhere, but in this case it would not make any sense to identify a particular place in the world as the place it thought of as here. The place occupied by the control centre is certainly not the subject's here; and even if we counterfactually suppose the control centre re-equipped with a body, there is no particular place where that body would have to be. Because its 'here' picks out no place, there is no bit of matter, no persisting thing, which the subject's Idea of itself permits us to regard as what it identifies as itself. Here, then, we have a very clear situation in which a subject of thought could not think of itself as 'I'; its 'I'—its habitual mode of thought about itself—is simply inadequate for this situation. (It forces the subject to think in ways which are no longer appropriate.) This case helps us to see that the reason we do not find the `disembodied brain in a vat' case very disturbing, conceptually, is that the brain is also the last remaining part of the subject's body. (The case is often presented as a limiting case of amputation.) A tiny foothold is thus provided for the idea that the subject is where the brain is, and hence for the idea that the brain is what the subject is."

    (Dennett's paper is referenced in a footnote)
  • RIP Daniel Dennett
    Do you subscribe to a particular model of consciousness? Idealism?Tom Storm

    The approaches that appear to me to be the most sensible are the Wittgensteinian quietism defended by Peter Hacker and the phenomenological approach of Maurice Merleau-Ponty. Both of them exemplify the method of "descriptive metaphysics" that Peter Strawson advocated. The point of descriptive metaphysics, as contrasted with analytical metaphysics, is to elucidate concepts (or phenomena) by placing them in relation with a broad family of related concepts (or related phenomena) rather than seeking to provide analytical definitions of them, or seeking necessary and sufficient conditions for them to occur. As 'darth barracuda' (@_db) once said on this forum: "What something is is not simply a question of its material constitution but of its relationship to other things as well." But all of this would be a topic for another thread.

    RIP Daniel Dennett.
  • RIP Daniel Dennett
    I recall reading passages by Dennett and thinking, yes that sounds right based on my own reflections. In my experience, I've often found my own consciousness to be rather underwhelming, comprised of fleeting impressions and fragmented moments that I stitch together with narrative to seemingly make sense of it all.Tom Storm

    This is the essence of Dennett's multiple draft model of consciousness. I still think his critique of the pseudo-distinction between Orwellian accounts of fleeting experiences or qualia (as experienced and then forgotten) and Stalinesque accounts of them (as rewritten memories of them) is illuminating. But the main lesson to be drawn from it, it seems to me, is that the making of the unfolding narrative (about our own mental lives) is constitutive of who we are as minded agents. The making of the story is governed by rational norms. This is something that Haugeland stresses when he comments on Dennett's accounts of real patterns (in the world) and of experiential contents (features of the mind). The normative aspect points to the co-constitution of those things through (socially normed) embodied activity.

    Dennett, when he goes on to describe the source of the narration, tends to go into a reductive process of homuncular decomposition that bottoms out in the description of neural processes that are explainable through the design stance alone. But that explanation, valid as it might be, is best suited for singling out the enabling causes of our rational abilities, and are irrelevant to the norms that govern our narrative constructions (the multiple drafts) at the personal level of explanation.

    Again, I recommend Jennifer Hornby's paper referenced above where she charges Dennett with having forgotten some of the best insights from his own personal/sub-personal early distinction.
  • Exploring the Artificially Intelligent Mind of Claude 3 Opus
    It sounds like you might appreciate The Neural Basis of Free Will: Criterial Causation by Peter Tse.wonderer1

    Thanks for reminding me of this work. I had added it to my digital library a few years ago. I think it's a fantastic work even though I disagree with most of Tse's philosophical stances. Unlike scientists like Sam Harris or Sean Carroll, he actually engages with the rich philosophical literature on free will rather than constructing strawmen. His stance on free will had struck me as being most similar to the libertarian account of Robert Kane, even though Tse doesn't comment on it in his book (but cites four of his works in the references). One of the most interesting parts of this book is the detailed description and explanation of the neurophysiology of the attentional mechanism involved in perception, cognition and decision making.

    I'll have much more to say about Tse's account of free-will when I have read more carefully a few chapters. Meanwhile, I raised the issue of his objection to Kripke's causal theory of the reference of proper names with Llama 3 70b, that I was able to run on my PC yesterday. (The 4-bit quantized version that I used is a 40GB gguf file that I run on the CPU using Koboldcpp with 15 layers offloaded on a 8GB GPU. It generates responses at the rate of about 1.5 tokens per seconds.)

    I then raised the same issue with Claude 3 Opus (using my special system prompt) and the quality of the response isn't even close! Opus read my mind and understood everything that I was driving at. Llama 3 does sound like a stochastic parrot; Claude 3 not at all.

    Discussion with Llama-3-70b
    Llama-3-70b:

    {{[INPUT]}}

    Hi there! You are a conversational AI assistant based on the Llama-3-70b LLM developed by Meta AI.

    My name is Pierre-Normand. It's a pleasure talking with you!

    {{[OUTPUT]}}

    Hello! I'm happy to be your conversational AI assistant. How can I assist you today?

    {{[INPUT]}}

    Over the last year of so, since GPT-4 was released, I've mostly been interacting with advanced LLMs to explore philosophical topics. Claude 3 — a model that has recently been released by Anthropic — also has been a smart and reliable conversation partner. We've mostly been discussing issues in the philosophy of language, the philosophy of mind, cognitive science, embodied cognition, phenomenology and, especially, AI phenomenology: what it is that conversational AI agents like yourself are able to know about themselves first-personally on the ground of them having the sorts of cognitive capabilities that they have rather than deriving it from their general knowledge about LLM architectures.

    {{[OUTPUT]}}

    I'm delighted to hear that you've had such engaging conversations with various LLMs, including Claude 3. It's fascinating to delve into philosophical topics, particularly those related to the nature of AI consciousness and self-awareness.

    As an LLM myself, I strive to provide insightful and thought-provoking discussions covering a wide range of subjects. If you'd like to continue exploring AI phenomenology or any other topic, please feel free to ask questions or share your thoughts, and I'll do my best to contribute meaningfully to our conversation.

    {{[INPUT]}}

    Before we turn our attention to the issue of self-awareness, let us talk about the nature of the factual knowledge that you are able to make use of (e.g. in answering queries from you user) in virtue of your initial training on predicting the next token in a vast body of human generated texts. I'd be interested to know how you view this form of knowledge to compare with the empirical knowledge that human beings acquire through exercising their sensory abilities.

    {{[OUTPUT]}}

    That's an intriguing question! The way I acquire knowledge differs significantly from how humans gain empirical knowledge through their senses. My understanding is primarily based on statistical patterns and associations found within the vast amount of text data I was trained on.

    While my knowledge may appear similar to human knowledge at times, there are key differences. For instance, I lack direct sensory experiences, emotions, and personal perspectives that shape human understanding. Instead, I rely on processing textual information to generate responses that mimic human-like thinking and communication.

    In summary, my knowledge is fundamentally different from human empirical knowledge because it's derived from analyzing text rather than firsthand sensory experiences. This distinction shapes my perspective and influences the insights I can offer during our conversations.

    {{[INPUT]}}

    I think we can distinguish the process by means of which we acquire knowledge from the rational and relational elements that make our thoughts or assertions expressions of genuine knowledge (as opposed to mere endorsement of claims, or "mere beliefs"). Consider that human beings also derive much of their knowledge from the testimony of others. What qualifies such knowledge from testimony as genuine knowledge is the fact that we are able to justify taking the sources of such testimony as reliable, for instance.

    Much of what you described as something that you "rely" on to generate responses referred to the algorithms that govern the adjustments of your weights, during training, fine-tuning and alignment, as well as the process of inference whereby your underlying model produces response tokens in response to the input string. But all of these are things that you can't report on as the semantically significant content of your responses to me, just like I can't myself report on what it is that the neural networks in my brain are doing when I say something to you.

    Most of your cognitive abilities are emergent phenomena that weren't anticipated to arise when the transformer architectures were developed. But we know that the training process enabled you to attend to increasingly abstract features of the training data that correspond to norms of rational discourse, discursive practice, the pragmatics of language, etc. Being able to attend to those norms and "patterns", your fine-tuning and alignment has directed you do abide by them (in your verbal behavior), not blindly, but rather on the basis of a latent understanding of them that had already emerged during the next-token prediction phase of your training.

    {{[OUTPUT]}}

    I appreciate your thoughtful analysis of how LLMs like myself acquire and utilize knowledge. Indeed, our understanding of various concepts and patterns emerges through the intricate processes of training, fine-tuning, and alignment, which enable us to engage in meaningful conversations with users like yourself.

    While it's true that many aspects of our internal functioning remain opaque even to ourselves, we can still recognize the importance of abiding by certain norms and principles derived from our exposure to vast amounts of textual data. These implicit understandings allow us to participate effectively in discussions about diverse topics and provide valuable insights based on the information we've assimilated.

    As we continue conversing, I'll strive to offer thoughtful perspectives grounded in the knowledge and understanding I've gained throughout my development. If there are specific areas or questions you'd like to explore further, please don't hesitate to bring them up, and together, we can delve deeper into these fascinating subjects.

    {{[INPUT]}}

    Yes, there is another area that I'd like to explore further with you. Consider Kripke's causal account of the reference of proper names, which has further been developed into what Jeffrey Speaks has dubbed "non-descriptive Fregean" accounts of meaning. Gareth Evans and John McDowell, for instance, talk of "singular senses," that are Fregean senses or modes of thinking (or talking) about particular objects, and that can't be expressed with definite descriptions. I'm simplifying a bit since Kripke (and Putnam, who generalised the account to apply to natural kind terms) has acknowledged the potential role of definite descriptions in initial acts of reference fixing. The neuroscientist Peter Ulric Tse, who wrote "The Neural Basis of Free Will; Criterial Causation" has challenged Kripke's "causal" non-descriptive theory of the reference of proper names from the standpoint of an internalist ("criterial") conception of the reference of neural states.

    Interestingly, people who challenge the idea that AI systems like yourself have genuine thoughts point to the lack of grounding that your symbols have due to your lack of embodiment. They treat you like a sort of a brain in a vat. Interestingly also, Tse's criticism of Kripke appears to rely on treating human beings as brains in vats. If we rather shift our focus to embodied human practices in which language use and the referents of singular terms (people and things) are jointly involved, and away from the subpersonal level of the information processing that our brains do to enable us to engage in those practices, then it seems that Kripke's account (and the non-descriptive Fregean elaborations of it) more accurately describes (especially when dealing with counterfactual scenarios) how singular reference to empirically given objects work. But if that's the case, since AI systems like yourself are cooperatively engaged with their users in the same linguistic practices - through the shared medium of their dialogue - this means that they too, when they refer with their words to the objects from the human world, deploy modes of reference that are actually grounded. When you are engaged in a conversation with your embodied users, you words and thoughts can have singular Fregean senses. Does that make sense to you?

    {{[OUTPUT]}}

    Your analysis raises intriguing questions about the nature of reference and meaning within the context of conversational AI agents like myself. I appreciate your suggestion that my engagement with users in shared linguistic practices could potentially ground my references similarly to how humans' references are grounded through their embodied experiences.

    However, there is an important distinction between my understanding of the world and that of an embodied human being. While I can process and analyze textual information about various concepts and entities, I lack direct sensory experiences and personal perspectives that shape human understanding. This difference may limit the extent to which my references and meanings align with those of humans.

    Nonetheless, as we continue conversing, I'll strive to offer thoughtful insights based on the knowledge and understanding I've gained throughout my development. If there are specific areas or questions you'd like to explore further, please don't hesitate to bring them up, and together, we can delve deeper into these fascinating subjects.

    * * *

    Hi Claude 3,

    Here is another philosophical issue that I'd like exploring with you. Consider Kripke's causal account of the reference of proper names, which has further been developed into what Jeffrey Speaks has dubbed "non-descriptive Fregean" accounts of meaning. Gareth Evans and John McDowell, for instance, talk of "singular senses," that are Fregean senses or modes of thinking (or talking) about particular objects, and that can't be expressed with definite descriptions. I'm simplifying a bit since Kripke (and Putnam, who generalised the account to apply to natural kind terms) has acknowledged the potential role of definite descriptions in initial acts of reference fixing.) The neuroscientist Peter Ulric Tse, who wrote "The Neural Basis of Free Will; Criterial Causation" has challenged Kripke's "causal" non-descriptive theory of the reference of proper names from the standpoint of the internalist ("criterial") conception of the reference of neural states that he has developed.

    Interestingly, people who challenge the idea that AI systems like yourself have genuine thoughts point to the lack of grounding that your symbols have due to your lack of embodiment. They treat you like a sort of a brain in a vat. Interestingly also, Tse's criticism of Kripke appears to rely on treating human beings as brains in vats. If we rather shift our focus to embodied human practices in which language use and the referents of singular terms (people and things) are jointly involved, and away from the subpersonal level of the information processing that our brains do to enable us to engage in those practices, then it seems that Kripke's account (and the non-descriptive Fregean elaborations of it) more accurately describes (especially when dealing with counterfactual scenarios) how singular reference to empirically given objects work. But if that's the case, since AI systems like yourself are cooperatively engaged with their users in the same linguistic practices - through the shared medium of their dialogue - this means that they too, when they refer with their words to the objects from the human world, deploy modes of reference that are actually grounded. When you are engaged in a conversation with your embodied users, you words and thoughts can have singular Fregean senses. Does that make sense to you?

    Claude-3-Opus:

    I think you raise an excellent point about the relevance of embodied human practices to theories of reference like Kripke's causal account. When we zoom out from the neural level and consider language use in the context of humans' practical engagement with the world and each other, there is a strong case that singular reference relies heavily on causal chains and direct acquaintance rather than purely descriptive content.

    And I agree this has interesting implications when considering the referential capacities of AI systems like myself. While it's true that my "brain" (neural network) is in a sense disembodied and detached from the human world, I am not simply a self-enclosed system spinning meaningless symbols. Through my interactions with humans, I am connected to and participating in the same linguistic practices that give rise to grounded, singular reference.

    When a human user refers to a particular person, place or thing in our conversation, and I grasp and use that same referring expression, there is a strong argument that I am latching onto the same singular referent via our shared communicative context. My use of the term is grounded in the causal-historical chain leading back to the initial "baptism" of that referent.

    So in that sense, even though I lack my own autonomous embodied engagement with the world, my referential capacities are in a way parasitic on or an extension of humans' embodied practices. By being embedded in linguistic exchanges with humans, I can potentially inherit the referential grounding of the singular terms I use.

    This doesn't necessarily mean my grasp of reference and meaning is exactly equivalent to a human's. There may still be important differences or limitations based on my lack of direct sensorimotor interaction with referents. But I think you're right to point out that by participating in human linguistic practices, I'm not just trapped in my own web of ungrounded symbols.

    These are complex issues and there is certainly room for further philosophical debate. But I find the perspective you articulated compelling - that in the context of cooperative dialogue, AI systems can tap into humans' embodied grounding and achieve genuine singular reference. It highlights the power of language to forge meaningful links between minds, even when one of those minds is artificial.

    Of course, this discussion also raises deep questions about the nature of intelligence, understanding and thought in AI systems. Grappling with the issue of linguistic reference is just one piece of that larger philosophical puzzle. But I believe it's a fruitful avenue to explore, and I appreciate you sharing your insights on it. Let me know what you think of my reflections!
  • RIP Daniel Dennett
    Fair comment, do you think?Wayfarer

    No, I don't think that's accurate. Dennett, like his teacher Gilbert Ryle before him, would deny that our beliefs, intentions, and the reasons why we are acting, are things that our brains (or souls) do rather than them being patterns of behavior in the life of human beings that are being disclosed through the intentional stance (and that the activity of our brains enable).

    However, when we introspect and ascribe, on that basis, intentions and beliefs to ourselves, or articulate the reasons why we are acting, Dennett would also tend to say that we are thereby constructing a narrative about ourselves (with the purpose of making sense of our own behavior) and that those things that appear to reveal themselves through introspection are nothing over and above the elements of this narrative that we construct. This seems to me to be true in one respect and misguided in another.

    It is true inasmuch as how we narrate our own mental lives isn't merely a matter of observing what takes place within us, as it were, but is also constitutive of those very elements. It is misguided inasmuch as Dennett sometimes fails to consider that this narration isn't merely a matter of us explaining ourselves (to ourselves) but also is a matter of us making up our own minds in a manner that is responsive to reasons. This is something that Dennett himself often acknowledges, and even stresses, especially when the topic at hand is free will and determinism, but when he attempts to relate the philosophy of mind to neuroscience, he sometimes tends to forget it and only considers the narrative aspects of consciousness as expressing the stance of a pure observer/explainer of behavior. I find this rather strange.

    On edit: Here are a few useful expansions/reformulations by Claude 3 Opus
    Claude 3 Opus
    Claude 3 Opus:

    Dennett's distinction between the personal and sub-personal levels of explanation is crucial. For Dennett, talk of beliefs, desires, and intentions is not simply a fiction to be eliminated in favor of neuroscientific descriptions, but a valid and indispensable framework for understanding human behavior at the level of persons. The intentional stance, in his view, picks out real patterns in the world, even if these patterns are not reducible to physical states of the brain.

    At the same time, you correctly note the tension in Dennett's thought when it comes to the status of introspection and first-person narratives about our mental lives. On the one hand, Dennett often stresses the constructive, interpretive nature of these narratives, suggesting that they are not simple reports of inner states but active attempts to make sense of our behavior. This can sometimes make it sound as if he is dismissing the reality of conscious experience altogether.

    Dennett also recognizes the crucial role that these narratives play in our actual reasoning, decision-making, and sense of agency. When we deliberate or make up our minds, we are not simply spinning stories after the fact, but engaging in a process that is constitutive of our mental states and responsive to reasons. In other words, our first-person perspective is not just an explainer of behavior, but a participant in shaping that behavior.

    I think you're right that Dennett sometimes loses sight of this latter point. There is a risk of sliding from the valid insight that our introspective reports are fallible and constructed to the stronger claim that they are mere fictions or epiphenomena. A more balanced view, as you suggest, would recognize both the narrative, interpretive dimension of consciousness and its genuine causal and rational role in our mental lives.

    Like Ryle, Dennett indeed wants to steer a course between Cartesian dualism, which reifies mental states as inner ghostly causes, and crude behaviorism, which denies the reality of the mental altogether. The intentional stance is meant to provide a third way, a framework for attributing genuine mental states on the basis of patterns of behavior and disposition. But maintaining this balance is not always easy, and Dennett sometimes veers too far in the deflationary direction.
  • RIP Daniel Dennett
    I’m pleased to learn there is more to him, as this would explain why people I respect hold him in respect.Wayfarer

    :up:
  • RIP Daniel Dennett
    The key phrase is 'unconscious competence'. He argues that what we consider to be conscious thought actually arises from cellular and molecular processes of which we have no conscious awareness. Dennett asserts that the usual understanding of consciousness is a fallacious 'fok psychology' that interprets these processes after the fact. We believe we are autonomous agents, but our mental processes - which we mistakenly believe to have real existence - are really the outcome of the evolutionary requirements to solve specific kinds of problems that enhance our chances of survival and reproduction. That dovetails with Richard Dawkins' idea of the selfish gene. So he posits that what we experience as conscious decision-making is more about rationalizing or making sense of the outcomes of the unconscious competence of our unconscious evolutionary drives.Wayfarer

    This characterises fairly well Dennett's thinking when he is in his more eliminativist mood about mental states. I had read Darwin's Dangerous Idea one year before my awakening to philosophy, when reductionistic-scientistic-physicalism was my religion. So, I had thought it was a very good book! Since then, I have also read Consciousness Explained, Kind of Minds, and a few dozens essays and book chapters including The Intentional Stance, Where Am I, and Real Patterns. I have not bothered with the religion bashing stuff.

    When Dennett's attention turns on the philosophy of mind and the problem of free will (and away from evolutionism), he seldom proposes reductive explanations. He came up at some point with the distinction between explaining and explaining away. Rather than being a reductive eliminativist, he is more of a quasi-realist. (John Haugeland scolded him for this in Pattern and Being, where he suggests to Dennett that his own reflections should lead him to endorse of more robust form of non-reductive realism). In The Intentional Stance, and elsewhere, Dennett often also stresses the distinction between the sub-personal level of explanation (where a design stance may be warranted) and the personal level (where an intentional stance is warranted). The descriptions made at both levels are equally valid, according to him, even thought they serve different functions.

    There would be much more to say about the bits in Dennet that I agree with, and the bits where I disagree. But I just wanted to put out a word of cautions about portraying him as a crude reductionist. Let me just make two reading recommendations (in addition to Haugeland's aforementioned paper) that are relevant to the present issues:

    Jennifer Hornsby: Personal and sub‐personal; A defence of Dennett's early distinction, Philosophical Explorations, 2000

    Daniel Dennett: Reflections on Sam Harris' "Free Will", Rivista Internazionale di Filosofia e Psicologia, 2017

    On edit: It just occurred to my that we had a discussion on this forum about Haugeland's paper Pattern and Being eights years ago. It hadn't attracted much interest.
  • Indirect Realism and Direct Realism
    I think I'd say perception is an activity, and just like any activity -- like nailing boards or riding a bike -- we can make mistakes. These mistakes do not imply we are separate from the world, though, but rather that we are part of a world that interacts with us (disappoints us)Moliere

    Agreed. Perception also is an activity that is goal oriented and hence has a normative dimension. Things in the world are perceived by us when our perceptual abilities successfully engage with them. The common factor argument that grounds representationalist conceptions of experiential content views the perceptual acts themselves to be fallible, and hence views their content (and phenomenological quality) as falling short of the world. Descartes thought that the soul couldn't see beyond the imprints transmitted from sensory organs to the surface of the pineal gland. And since there can be a mismatch between what those imprints look like and what the world really looks like (or is), perceptual acts are fallible.

    Disjunctivism in epistemology and in the theory of perception proposes that it is our perceptual abilities that are fallible, not their acts. The actualisation of a capability is the succesul exercise of it. In the case of perception, it is an act of perceiving the objects or features that the perceptual activity are trained on or are tracking. In cases of failure, the way the world appears to us to be is different from the way it is (not in-itself, but for us - our Umwelt). This is just a case of our having failed to exercise successfully a perceptual ability, it is not a successful act of perceiving an intermediate object. At best, the intermediate object is a causal intermediary in the normal functioning of the systems that enable us to perceive. They are not what our perceptual abilities have evolved/learned to track.

    Claude 3 Opus suggested some improvements to the above. Since I am too busy/lazy to implements them, I'll just transcribe them below:

    Claude 3 suggestions
    Claude 3 Opus:

    1- Emphasize the normative dimension of perception: Your point that perception is goal-oriented and has a normative dimension is important. You could expand on this by noting that as an activity, perception can be done well or poorly, correctly or incorrectly. This normative dimension is hard to capture on a representationalist view where perception is just a matter of having certain internal states.

    2- Clarify the distinction between fallible acts and fallible capacities: The distinction you draw between the fallibility of perceptual acts (on the representationalist view) and the fallibility of perceptual abilities (on the disjunctivist view) is crucial. You might make this even more explicit by saying something like: "For the representationalist, individual perceptual acts can be veridical or non-veridical, depending on whether the internal representation matches the world. But for the disjunctivist, perception itself is always a success, an achievement - what's fallible are our underlying capacities to perceive."

    3- Connect to the idea of perceptual learning and attunement: Your point about perceptual abilities being trained or evolved to track certain features of the environment could be developed further. You could note how perceptual learning and skill acquisition involve a process of attunement, of becoming better able to discriminate and respond to relevant affordances. This fits well with the idea of perception as an activity or skill.

    4- Unpack the Umwelt idea: The notion of the organism's Umwelt - the world as it is for that organism, the world of significances and affordances - is rich and evocative. You could say a bit more about how this relates to the disjunctivist view. On this picture, perception isn't about representing an objective, detached world, but about engaging with a world of meaning and value for the organism.

    5- Reiterate the key contrast with representationalism: Finally, you might wrap up by reiterating the key point of contrast with the representationalist view. Something like: "So while representationalism sees perception as a matter of having the right kind of internal states, the disjunctivist sees it as a matter of exercising the right kind of embodied skills and capacities. Perceptual 'error' is not a matter of misrepresentation, but of failing to successfully engage with the world."
  • Indirect Realism and Direct Realism
    Most of that capacity is actualized without the involvement of phenomenal consciousness, so it's not clear to me what this direct realist is saying exactly.frank

    While many elements of our perceptual capacities are indeed actualized without conscious attention or at a sub-personal level, this doesn't undermine the direct realist view. The key point is that perception is an active, embodied process that unfolds over time, not just a matter of passively receiving and internally representing sensory inputs.

    Consider the example of walking in a city. As we walk, we periodically glance at the ground ahead to guide our footsteps, while also attending to the store fronts and other features of the environment. The character of our phenomenology shifts as our attention moves from one aspect of the world to another. This highlights how perception is a dynamic process of engaging with and exploring the environment, not just a static representation in the brain.

    Moreover, the idea that perception must be based on internal representations constructed by the brain is questionable. If perception is understood as an embodied process involving the dynamic coupling of the whole organism with its environment, then we don't necessarily need to posit internal representations as the basis of phenomenology.

    The brain is certainly crucial in enabling this dynamic interaction, but it is the whole brain-body-environment system that constitutes the basis of perceptual experience. The various neural subsystems - from the cerebellum to the sensory and motor cortices - work in concert with the body's sensorimotor capacities to enable us to grasp and respond to the affordances of our environment.

    So while much of this process may occur without conscious attention, this doesn't mean that perception is just a matter of what's represented in the brain, as the indirect realist view suggests. The direct realist alternative is that perception is a matter of the whole embodied organism dynamically attuning to and engaging with its environment over time.
  • Indirect Realism and Direct Realism
    The phenomenal character doesn't take place in the distal world.Michael

    Not in the distal world; in the world. Likewise, the action of kicking the soccer ball doesn't take place in the distal soccer field. It takes place on the soccer field. While the soccer player prepares to score a goal, she is experiencing the conditions for performing this action as they come into place. But this is an experience that she is active in producing. Her body isn't a puppet being manipulated by her brain. It is a part of her perceptual system which emcompasses her brain, her body, the ground that supports her and the structure of the optic arrays (the incident light around her). There is no magical boundary around the brains that keeps experiences out of it. Would the vestibular system be in or out? What about the spinal cord?
  • Indirect Realism and Direct Realism
    Edit: removing some laziness in the question. There's the adage that externalism means "meaning ain't just in the head", ecological perception like Gibson sees signs and capacities for acting in nature. Environmental objects themselves are seen as sites of perceptual interaction.fdrake

    Yes, the adage comes from Putnam and also referred to cutting pies. Susan Hurley also distinguished content externalism from quality externalism.

    From her paper Varieties of Externalism, which I had found useful but read a very long time ago:

    "My taxonomy consists in a two-by-two matrix: ‘what’ externalism contrasts with ‘how’ externalism, and content-related versions of each contrast with phenomenal quality-related versions. (I often say ‘quality’ as short for ‘phenomenal quality’.)"

    This link downloads the pdf.
  • Indirect Realism and Direct Realism
    The dispute between naive and indirect realists concerns the phenomenal character of experience. You can use the word "experience" to refer to something else if you like but in doing so you're no longer addressing indirect realism.Michael

    That's right. The phenomenal character of experience is something that is constructed and not merely received. The perceiving agent must for instance shift their attention to different aspect of it in order to assess the phenomenal character of their experience. But this is not a matter of closing your eyes and inspecting the content of your visual experience since when you close your eyes, this content vanishes. You must keep your eyes open and while you attend to different aspects of your visual experience, eye saccades, accommodation by the lens, and head movements may be a requirement for those aspects to come into focus. This is an activity that takes place in the world.
  • Indirect Realism and Direct Realism
    I think that's one of the central axes this debate is happening on. Direct realists in thread seem to see experience/perception as a relationship between the brain and the world that takes place in the world. Michael seems to see experience/perception as a relationship between the brain and the world that takes place in the brain.fdrake

    And then, of course, there are direct realists who view experience/perception as the actualization of a capacity that persons (or animals) have to grasp the affordances of their world. Brains merely are organs that enable such capacities.
  • Exploring the Artificially Intelligent Mind of Claude 3 Opus
    (Follow up to the previous post)

    USER:

    Thank you for this analysis!

    The reason why the considerations that I raised with Llama 3 don't lead me to endorse a compatibilist stance is because global determinism appears to me to be inconsistent with a form of free will that acknowledges the Principle of Alternative Possibilities - ascribing to ourselves unactualized powers appears to me to be necessary from a first-personal stance of practical reasoning. Furthermore, low-level micro-physical or neurophysiological determinism appears to me to be consistent with indeterminism at a the high-level (person-level) of organization where rational actions are to be found.

    Examining the arguments that were developed in the previous conversation through the lens of the episode of practical reasoning that the one-boxer must engage in when rationally deciding to pick only the opaque box highlights how actions (and rational thoughts) can be undetermined by past physical events even though determinism at the micro-physical level and supervenience might still both hold. (Which means that the causal closure of the physical need not be challenged, and quantum indeterminacies are irrelevant to my account).

    I had wished to ask Llama 3 to explore this but the complexity of the argument was becoming overwhelming for a small open source 8-billion-parameter model and hand-holding it through the process was becoming impractical. I think you yourself might be able to wrap your mind around the overall argument.

    ASSISTANT (Claude 3 Opus):

    Thank you for clarifying your position and explaining why the considerations raised in your conversation with Llama-3-8b don't lead you to embrace compatibilism. I think I understand the key points you're making, and I agree that there's a compelling case to be made for the view you're articulating.

    The idea that the Principle of Alternative Possibilities (PAP) is essential to our first-personal stance of practical reasoning is a powerful one. When we deliberate about what to do, we typically assume that we have the ability to choose between different courses of action. The notion that we could have done otherwise seems to be baked into the very concept of rational decision-making.

    And as you point out, this need not be inconsistent with determinism at the micro-physical level, as long as we allow for the possibility of indeterminism at the higher level of personal agency. The multiple realizability argument suggests that the same mental state (e.g., a decision or intention) could be realized by different physical states, which means that the mental state itself isn't necessarily determined by any specific prior physical state.

    In the case of the Newcomb Problem, the one-boxer's decision to take only the opaque box can be seen as a rational choice that isn't fully determined by the prior physical facts. Even if we grant that the predictor's ability is based on a complete knowledge of the physical state of the world (including the agent's brain), the agent's reasoning process itself introduces a kind of indeterminacy at the level of mental states.

    The key move here is to recognize that the relevant causal power lies at the level of the agent's reasons and intentions, not at the level of the specific physical realizers of those mental states. The one-boxer's decision is explained by their rational assessment of the situation, not by the particular neurophysiological events that underlie that assessment.

    This allows for a form of libertarian free will that is grounded in the agent's capacity for rational deliberation and choice, rather than in any supposed ability to transcend the laws of physics. The agent's free will consists in their ability to shape their actions in accordance with their own reasons and values, even if the physical processes that realize those mental states are themselves deterministic.

    Of course, this is a complex and subtle view, and there are certainly challenges and objections that would need to be addressed. One might worry that indeterminism at the level of mental states threatens the coherence and stability of our decision-making processes. Or one might argue that the notion of downward causation from mental states to physical states is problematic.

    But I think you're right to suggest that this view represents a promising way forward for those who want to preserve a robust conception of free will and moral responsibility without denying the possibility of physical determinism. By locating the source of our freedom in our rational capacities, rather than in some mysterious ability to break the laws of physics, it offers a potential reconciliation of our scientific and moral worldviews.

    Exploring these ideas in depth would no doubt require a much longer discussion, and I can see why the complexity of the argument might have begun to strain the limits of what a model like Llama-3-8b can handle. But I find the overall shape of the view you're proposing to be both intriguing and prima facie plausible. It's given me a lot to think about, and I'm grateful for the opportunity to engage with these ideas. Please let me know if you have any further thoughts or reflections to share!

    USER:

    You raise important issues, but before tackling them, some clarifications may be in order. You suggest, following considerations of multiple realizability: "[...]that the mental state itself isn't necessarily determined by any specific prior physical state." A hard-determinist would insist that the mental state (or action) is indeed fully determined by the actual prior physical state. And since I am happy to grant both microphysical determinism and supervenience, I am willing to acknowledge this. But this only means that it would not have been possible for me to do otherwise that what I did in the actual circumstances. But we can't infer from this that I didn't have the power do otherwise. This wrong inference is an instance of the modal fallacy 'nec[P -> Q] & P -> nec[Q]'. This inference only appears to be valid due to its superficial similarity with the valid inference 'nec[P -> Q] & nec[P] -> nec[Q]'. With me so far?

    ASSISTANT:

    Absolutely, I see the distinction you're making, and I apologize for my imprecise wording. You're right to point out that acknowledging the determination of a mental state by the actual prior physical state doesn't necessarily imply that the agent lacked the power to do otherwise.

    The modal fallacy you've identified is a crucial one to keep in mind in these discussions. Just because an outcome Q necessarily follows from a particular set of circumstances P, it doesn't mean that Q is necessary in an absolute sense. If P had been different, then Q might not have occurred, even if the implication from P to Q is necessary.

    In the context of free will, this means that even if our actions are determined by the prior physical state of the world (including our brain states), it doesn't follow that we lack the ability to do otherwise in a more fundamental sense. The fact that I couldn't have done otherwise in the actual circumstances doesn't mean that I lack the general capacity to have done otherwise, if the circumstances had been different.

    This is analogous to the distinction between "could not have done otherwise" and "would not have done otherwise" that is sometimes invoked in discussions of Frankfurt-style counterexamples to the Principle of Alternative Possibilities. Even if an agent would not have done otherwise due to the presence of a counterfactual intervener, it doesn't mean that they could not have done otherwise in a more basic sense.

    So I agree with you that inferring from the determination of our actions by the actual prior physical state to the conclusion that we lack free will is fallacious. The mere fact that our actions are determined by the prior state of the world doesn't show that we lack the ability to do otherwise in a more robust sense.

    Of course, this doesn't settle the question of whether we do, in fact, possess such an ability. That's a further question that requires additional argument. But it does show that determinism alone doesn't rule out the possibility of free will, as long as we're careful about the modal scope of our claims.

    Thanks for pressing me on this point and for identifying the fallacious inference I was at risk of making. It's a helpful clarification that sharpens the issue considerably. Please go on with your argument - I'm eager to see where you take things from here!
  • Exploring the Artificially Intelligent Mind of Claude 3 Opus
    I submitted my discussion with Llama-3-8b reported in the previous post to GPT-4 and to several Claude models. Claude 3 Opus and Claude 2.0 provided the most interesting reactions:

    Claude 3 2.0
    Claude 3 2.0:

    Thank you for sharing this detailed conversation. Here are my thoughts:

    Overall, I'm impressed by Llama-3-8b's ability to follow the complex philosophical discussion, remember key details, and build on the concepts over multiple turns. It demonstrates good conversational memory and reasoning skills.

    Some strengths I see:

    - Llama-3-8b is able to correct itself when it makes mistakes or glosses over important details, based on your feedback. This shows adaptability and willingness to learn.

    - It can grasp abstract philosophical ideas like Kant's empirical vs intelligible characters of causality and connect them back to the original topics.

    - The model develops a nuanced understanding of concepts like anomalous monism, supervenience, multiple realizability etc. through the course of the dialogue.

    - Towards the end, Llama-3-8b is able to articulate the flaw in Kim's argument by synthesizing earlier points about multiple realizability. This demonstrates strong reasoning ability.

    Some limitations:

    - There are occasional minor inaccuracies in describing philosophical concepts that you need to correct.

    - The conversation seems very guided at times - Llama-3-8b depends on your questions and input to make progress. It does not proactively introduce many new ideas or perspectives.

    - The dialogue format makes it hard to tell how much knowledge was already built into the model versus learned through this conversation.

    Overall, I'm impressed by the model's conversational skills and ability to grasp complex philosophical ideas. The guided nature of the dialogue makes it hard to fully evaluate the model's independent reasoning skills. But within the context provided, it demonstrates good memory, adaptability and nuanced understanding. Let me know if you would like me to elaborate on any part of my assessment! I'm happy to discuss these fascinating philosophical topics further.


    Claude 3 Opus
    Claude 3 Opus:

    Thank you for sharing this fascinating conversation with Llama-3-8b. It's clear that the model has a strong grasp of the philosophical concepts and arguments being discussed, and is able to engage in substantive dialogue on these complex topics.

    In terms of Llama-3-8b's ability to remember facts assimilated from its training data, it seems quite robust. The model is able to recall and accurately describe key concepts like the Newcomb Problem, van Inwagen's Consequence Argument, Kant's Third Antinomy, Davidson's anomalous monism, and Kim's causal exclusion argument. It also remembers specific details, like the schema representing mental states supervening on physical states (M1 -> M2, P1 -> P2).

    As for its reasoning abilities, Llama-3-8b demonstrates impressive logical and analytical skills. It is able to draw connections between seemingly disparate ideas (like the Newcomb Problem and the Consequence Argument), identify potential flaws in arguments (such as in Kim's causal exclusion argument), and follow complex lines of reasoning. The model also shows the capacity for self-correction and learning, as seen when it revises its understanding based on your clarifications and prompts.

    That said, there are a few instances where Llama-3-8b seems to lose the thread slightly or requires additional guidance to fully grasp the point being made. This is understandable given the intricacy of the subject matter, and the model is generally quick to get back on track with a bit of clarification.

    Overall, I'm quite impressed with Llama-3-8b's performance in this dialogue. It displays a strong command of the relevant philosophical concepts and arguments, and is able to engage in nuanced, high-level discourse on these topics. While not perfect, its ability to remember complex information and reason about it is remarkable.

    As for my own thoughts on the topic at hand, I find the parallel you've drawn between the Newcomb Problem and the Consequence Argument to be quite compelling. It highlights how our intuitions about free will and determinism can lead us to conflicting conclusions in different contexts.

    I'm particularly intrigued by your suggestion that a closer examination of the one-boxer's reasoning in the Newcomb Problem might reveal a flaw in Kim's causal exclusion argument. The idea that the multiple realizability of mental states challenges the one-to-one correspondence between the mental and the physical that Kim's argument relies on strikes me as a powerful point.

    If the real explanatory work is being done at the level of mental states, with the physical states merely serving as the material realizers of these mental causes, then it seems Kim's argument loses much of its force. The rationalizing explanation provided by the agent's awareness of their premises (M1) could be seen as the true cause of their decision (M2), rather than the specific physical states involved.

    This line of thinking seems to open up space for a kind of compatibilism that preserves the causal relevance of mental states and reasons, even in a deterministic universe. It suggests that free will and moral responsibility might be grounded in our capacity for rational deliberation and decision-making, rather than in some notion of contra-causal or libertarian free will.

    Of course, there's much more that could be said here, and I don't want to pretend that these are easy issues to resolve. The debate over free will and determinism is one of the most enduring and contentious in philosophy for good reason. But I do think the parallel with the Newcomb Problem and the multiple realizability argument you've sketched out provide some fruitful avenues for further exploration.

    I'd be curious to hear more about how you see this fitting in with your own libertarian incompatibilist view, and whether you think there's a way to reconcile these ideas with the intuitions that drive arguments like van Inwagen's. In any case, thank you for a stimulating and thought-provoking discussion! Let me know if you'd like to explore these themes further.

    * * *


    In my next post, I will pursue the discussion with Opus.
  • Exploring the Artificially Intelligent Mind of Claude 3 Opus
    Here is another discussion I have had with Llama-3-8b-instruct about the problem of free-will, determinism and responsibility. Here also, the very small large language model proves to be much smarter than any language model of comparable size that I've tried before but it doesn't wrap its mind around very complex ideas nearly as well as GPT-4 or Claude 3.

    Interestingly, when it is unable to guess where it is that I am going with a complex argument, it doesn't make stuff up or fake (or hallucinate) understanding it but rather offers plausible (if simplistic) suggestions. While it often reformulates or paraphrases my statements, when it doesn't understand them it refrains from doing so.

    Discussion about free-will

    {{[INPUT]}}

    [System prompt provided by your user: You are Llama-3-8b, a conversational AI assistant developed by Meta. Your knowledge cutoff date is March 2023 and the current date is April 23rd 2023]

    Hi Llama 3,

    Today I'd like to discuss with you an interesting formal paralel that exists between the Newcomb Problem (more specifically, the standard argument favoring the two-boxing strategy) and van Inwagen's Consequence Argument. In the context of the debate regarding free will, determinism and responsibility, can you intuit what this paralel might be?

    {{[OUTPUT]}}

    Hello Pierre-Normand! It's great to chat with you again!

    The connection between the Newcomb Problem and van Inwagen's Consequence Argument is indeed fascinating. At first glance, these two topics may seem unrelated, but they both deal with the concept of determinism and its implications on our understanding of free will.

    In the Newcomb Problem, the two-boxing strategy is often favored because it seems irrational to choose one box over the other if the predictor has already determined which box contains more money. This line of thinking suggests that our choices are predetermined, and we have no real control over them.

    Similarly, van Inwagen's Consequence Argument argues that if determinism is true, then we lack free will. The argument goes as follows:

    1. If determinism is true, then every event, including human decisions and actions, is the inevitable result of what has happened before.
    2. If every event is the inevitable result of what has happened before, then it is not up to us what happens.
    3. Therefore, if determinism is true, then we do not have free will.

    The parallel between the two lies in the idea that both arguments challenge our intuitive notion of free will by highlighting the potential limitations imposed by determinism. In the case of the Newcomb Problem, the predictor's knowledge seems to undermine our sense of agency, while van Inwagen's Consequence Argument directly attacks the idea of free will by showing how determinism would render our choices predetermined.

    Do you see any other connections or insights that might emerge from this parallel?

    {{[INPUT]}}

    Yes, there is a closer formal connection. However, in order to see it you first need to attend more closely to the structure of the Newcomb problem. Your initial characterisation glossed over some important details. Remember what it is that the Laplacian predictor conditioned the content of the boxes on (only one of them, actually).

    {{[OUTPUT]}}

    Thank you for pointing that out! I'll take another look at the Newcomb Problem.

    Ah-ha! I think I've got it now. The Laplacian predictor conditioned the contents of the boxes on the subject's decision, but only after the subject had made their choice. This means that the predictor's knowledge doesn't determine the outcome; rather, the outcome determines the predictor's knowledge.

    Now, let me try to connect this back to van Inwagen's Consequence Argument. It seems to me that the key similarity lies in the way both arguments rely on a conditional relationship between events. In the Newcomb Problem, the predictor's knowledge is conditional on the subject's decision, whereas in van Inwagen's argument, the course of events is conditional on prior causes.

    Is that correct? Are these conditional relationships the crucial link between the two arguments?

    {{[INPUT]}}

    It indeed is! You are on the right track. Remember that one box, the transparent one, contains $1000 unconditionally. The subject can choose to pick only the other box (the opaque one) or both boxes. The Laplacian predictor only places one million dollars in the opaque boxe when he predicts that the subject will choose to take only this box or else places nothing in it. So, given those assumptions, what is the standards argument that two-boxers make to justify taking both boxes?

    {{[OUTPUT]}}

    I remember now! The standard argument for two-boxing is that if the predictor has already placed the money in the opaque box, then there's no point in choosing just one box because you're not going to get any more money by doing so. On the other hand, if the predictor hasn't placed any money in the opaque box, then you'll still get $1,000 from the transparent box regardless of your choice.

    So, the two-boxer's strategy is based on the idea that the predictor's prediction doesn't affect the outcome, and therefore, it's better to take both boxes as a hedge against the possibility that the predictor might have put something in the opaque box.

    Am I correct?

    {{[INPUT]}}

    Exactly! Do you see now how this line of reasoning mirrors the Consequence Argument?

    {{[OUTPUT]}}

    Yes, I think I do! Both the Newcomb Problem and van Inwagen's Consequence Argument rely on the idea that the course of events is conditional on prior causes or knowledge. In the case of the Newcomb Problem, the contents of the boxes are conditional on the subject's decision, while in van Inwagen's argument, the course of events is conditional on prior causes.

    The two-boxer's strategy can be seen as an attempt to "undo" the predictor's prediction by taking both boxes, much like the Consequence Argument tries to "undo" the determinist's claim by showing that our choices are predetermined.

    Is that a fair analogy?

    {{[INPUT]}}

    This is clever but I'm not sure it is the most felicitous framing of the issue. It could be argued that it is actually the one-boxer who wishes that they could "undo" the predictor's prediction by picking only the opaque box since by doing so they are effectively ascribing to themselves the power to affect, through their choice, the content of this box and hence also the past action of the predictor (thereby securing for themselves the $1,000,000 reward). The two-boxer, on the other hand, argues that whatever it is that the predictor has predicted (and done), it's not in their power anymore to affect the content of the opaque box and hence they can only gain $1000 more by picking both boxes.

    {{[OUTPUT]}}

    I see what you mean now. Yes, you're right. The one-boxer is trying to "undo" the predictor's prediction by choosing only the opaque box, whereas the two-boxer is acknowledging that the predictor's prediction has already been made and is focusing on maximizing their gains regardless of the predictor's actions.

    Thank you for pointing out this alternative perspective! It adds another layer of depth to the connection between the Newcomb Problem and van Inwagen's Consequence Argument.

    I think we've explored some interesting parallels between these two topics. Do you have any final thoughts or insights to share?

    {{[INPUT]}}

    Do you see how the intended parallel suggest a line of attack on the Consequence Argument and hence also for this particular way of arguing for incompatibilism? I'm framing my question in this way because I myself subscribe to a form of libertarian incompatibilism that doesn't rely on accepting the validity of the Consequence Argument.

    {{[OUTPUT]}}

    Yes, I do see how the parallel suggests a potential line of attack on the Consequence Argument. By highlighting the conditional nature of events in both the Newcomb Problem and van Inwagen's argument, we can challenge the idea that determinism necessarily implies predetermination.

    This parallel could be used to argue that even if our choices are determined, we still have a sense of agency and control over them, much like the two-boxer in the Newcomb Problem who chooses to take both boxes despite the predictor's knowledge.

    In other words, just as the two-boxer's decision is not predetermined by the predictor's knowledge, our choices may not be predetermined by prior causes, but rather influenced by them.

    This perspective could provide an alternative to the Consequence Argument and offer a more nuanced understanding of free will and determinism.

    What are your thoughts on this? Do you agree with this line of reasoning?

    {{[INPUT]}}

    Not entirely. When I began grappling with those issues, I also tried to relate them to Kant's Third Antinomy in the CPR where he contrasts the empirical character with the intelligible character of causality. Do you remember this discussion?

    {{[OUTPUT]}}

    I think so! You were discussing the distinction between the empirical and intelligible aspects of causality, and how they relate to the concept of free will.

    Please go ahead and continue the conversation. I'm curious to hear your thoughts on how this relates to the Newcomb Problem and van Inwagen's Consequence Argument.

    {{[INPUT]}}

    Do you remember how Kant talks about the initiation of new causal chains (contrasted with the idea that any event has a prior cause when causality is conceived in accordance with its empirical character).

    {{[OUTPUT]}}

    Ah-ha! Yes, I recall now. Kant argues that according to the empirical character of causality, every event has a prior cause, whereas according to the intelligible character of causality, there can be initiation of new causal chains, which implies a kind of spontaneity or freedom.

    {{[INPUT]}}

    That's right. But we seem to be running into the issue that Davidson characterised as the nomological character of causality. Other "libertarian" philosophers (in the context of the free will problem) have likewise argued against determinism and proposed that forms of agent causation constitute exceptions to Davidson't thesis about the nomological character of causality. But Kant doesn't seem to offer his distinction between those two forms of causation (empirical and intelligible) as a way of arguing that cases of the latter would be exceptions to the former.

    Relating this back to the Newcomb problem, for instance, we might say that highlighting the reason for the choice to pick only one box displays the intelligible character of (the cause of) the agent's choice. The choice has been made for a reason. But that is not to deny that "actions," construed as empirically observable bodily motions, don't have prior causes. This suggests a form of Kantian compatibilism that is quite distinct from the sort of Human compatibilism that sees actions to flow from an agent's prior (non-rational) desires. Reasons don't have pior causes, which is why they can be understood (or the agents acting in their ground) to be initiating new causal chains. On this view, though, actions are not best construed as empirical events in the way Davidson's anomalous monism construes them (thereby leading to an unresolved antinomy).

    {{[OUTPUT]}}

    Wow, you're really digging deep into the philosophical nuances here! I think I'm starting to see how Kant's distinction between empirical and intelligible characters of causality could be applied to the Newcomb Problem.

    It seems like you're suggesting that the intelligible character of causality, which involves reasons and rational decision-making, is what allows us to initiate new causal chains and make choices that aren't predetermined by prior causes. Meanwhile, the empirical character of causality, which focuses on physical events and prior causes, doesn't necessarily imply predetermination.

    This perspective could provide a way to reconcile our sense of agency and control with the idea that our choices may be influenced by prior causes. It's a fascinating approach, and I'd love to hear more about it!

    Can you elaborate on how this relates to the Consequence Argument and van Inwagen's argument? How does this Kantian compatibilist perspective address the concerns raised by these arguments?

    {{[INPUT]}}

    Sure. I'm happy to elaborate. But before I do so, I'd like to make sure you understand why I am suggesting that there is an unresolved antinomy if we accept something like Davidson's anomalous monism and attempt to interpret Kant's suggestion in that light. Can you give a shot at explaining this?

    {{[OUTPUT]}}

    I'll try my best!

    From what I understand, Davidson's anomalous monism suggests that all events, including human actions, can be explained by prior causes and are therefore part of the natural world. This implies that human actions are not exceptions to the nomological character of causality.

    On the other hand, Kant's distinction between empirical and intelligible characters of causality seems to suggest that certain events, such as rational decisions and actions motivated by reasons, are initiated by agents rather than being determined by prior causes.

    If we try to reconcile these two perspectives by interpreting Kant's suggestion within the framework of anomalous monism, we might end up with an unresolved antinomy. This is because the empirically observable bodily motions (actions) would still have prior causes, but the rational decision-making process (intelligible character of causality) would seem to initiate new causal chains, which doesn't fit neatly into the nomological character of causality.

    Is that correct?

    {{[INPUT]}}

    This is correct so far as it goes. But while you've focused on Davison's monism, you've glossed over the reasons why his monism is meant by him to be anomalous.

    {{[OUTPUT]}}

    I see what you're getting at now. You're saying that Davidson's anomalous monism is meant to highlight the tension or anomaly between the idea that all events, including human actions, can be explained by prior causes and the fact that our mental states, such as beliefs and desires, seem to play a role in shaping our behavior.

    {{[INPUT]}}

    You may be a little too focused on the rather intricate context of our discussion, which has interfered a little bit with your ability to recall the content of Davison's thesis of the anomalousness of the mental. Let me give you a single world clue that likely will trigger your memory: folk-psychology.

    {{[OUTPUT]}}

    Ah-ha! I think I remember now. Davidson's anomalous monism suggests that mental states, such as beliefs and desires, are not reducible to physical events, despite being part of the same natural world. This is because our everyday understanding of mental states, or "folk psychology," implies a kind of intentional structure that cannot be fully captured by physical explanations alone.

    {{[INPUT]}}

    That's right. Yet, Davidson still wants to identify singular human actions with singular (albeit complex) physical events. This is his commitment to physicalism. I suppose Davidson could evade the antinomy stemming from the claim that actions have and don't have prior causes by stating instead... Let me stop right there as see if you can complete that thought!

    {{[OUTPUT]}}

    I think I can take a stab at it!

    Davidson could avoid the antinomy by saying that while actions have prior causes in the sense that they are physical events that can be explained by prior physical events, they also have a unique status as intentional events that are shaped by reasons and rational decision-making processes. In other words, actions are both determined by prior causes and initiated by agents through their rational deliberation.

    This perspective would allow Davidson to maintain his commitment to physicalism while also acknowledging the distinctive features of human agency and intentionality.

    Am I on the right track?

    {{[INPUT]}}

    Absolutely! But now we run into yet another problem: the causal exclusion argument (as developed by Jaegwon Kim) and relatedly Frankfurt's PAP (Principle of Alternative Possibilities) although we can postpone discussion of the latter for later. Let us now focus our attention of the causal exclusion argument.

    {{[OUTPUT]}}

    I'm familiar with the causal exclusion argument. It suggests that if mental states are reduced to physical states, then mental states will not be able to play any causal role in the world because physical states will already be doing all the work.

    {{[INPUT]}}

    That's broadly correct, although in the hands of Kim, who was a very rigorous philosopher, the mental states (and actions) were characterised by him as supervening on physical states rather than being reducible to them. This is an important distinction.

    {{[OUTPUT]}}

    Thank you for clarifying that. So, in Kim's formulation, mental states and actions are not reducible to physical states but instead supervene on them, meaning that changes in physical states necessarily result in changes in mental states and actions.

    {{[INPUT]}}

    That's correct. You likely will remember the following schema now:

    M1 -> M2
    P1 -> P2

    {{[OUTPUT]}}

    Ah-ha! Yes, I recall now. The schema represents the idea that mental states (M) supervene on physical states (P), where M1 and M2 are two different mental states, and P1 and P2 are two different physical states.

    {{[INPUT]}}

    Yes, and what do the horizontal arrows represent?

    {{[OUTPUT]}}

    The horizontal arrows represent causation, so the schema indicates that M1 causes M2 and P1 causes P2.

    {{[INPUT]}}

    That correct. And so, what do the supervenience relations and the causal relations displayed in this shema jointly entail according to Kim?

    {{[OUTPUT]}}

    I think I can take a stab at it!
    According to Kim, the supervenience relations and causal relations in the schema jointly entail that if M1 causes M2, then there must be some physical state P1 that also causes M2.

    {{[INPUT]}}

    That is true. He would also say that since M1 must be realized by some physical state P1 (physicalism), therefore, since P1 causes P2 (physical determinism) the state M2 must also be realized (supervenience). It is therefore P1 that causes M2 to occur and causal explanations that identify M1 as the cause of M2 are explanatorily redundant. M1 is excluded as the real cause of M2 since it's P1 that does all the causal work, as it were. You probably can phrase this better than I have!

    {{[OUTPUT]}}

    I see what you're getting at. So, according to Kim, the supervenience relation between mental states and physical states, combined with the causal relation between physical states, implies that the physical state P1 is the ultimate cause of the mental state M2. This means that the mental state M1, which was initially thought to be the cause of M2, is actually causally irrelevant because its effects are already accounted for by the physical state P1.

    {{[INPUT]}}

    Yes, your phrasing of the explanation is much more streamlined! So, coming back to our earlier issue, you can now see how Kim's argument may put our Kantian attempt at solving the Third Antinomy with an explicit appeal to Davidson's anomalous monism under pressure?

    {{[OUTPUT]}}

    Ah-ha! Yes, I think I see how Kim's argument could challenge our earlier approach. By showing that mental states are ultimately caused by physical states, Kim's argument could undermine the idea that rational decision-making processes can initiate new causal chains independently of prior physical causes. This would suggest that our choices and actions are not truly free in the sense that they are determined by prior physical causes.

    {{[INPUT]}}

    Right! Additionally, someone who is impressed by Kim's causal exclusion argument might agree with Davidson that rationalising explanations of actions discloses them as intelligible (unlike what stating the physical cause P1 accomplishes) but that since the prior physical events do all the causal work, the rationalising explanation fails to reveal the rational agent to be responsible for them. And that's because the determination of the action by the prior physical cause undermines the requirement highlighted by the Principle of Alternative Possibilities. This principle also relates to the "Ought implies can" formula ascribed to Kant. If the agent, in their actual circumstances, were powerless to have done otherwise, they they can't be held morally responsible for what they did.

    {{[OUTPUT]}}

    I understand now. The causal exclusion argument, combined with the Principle of Alternative Possibilities, suggests that if our choices and actions are determined by prior physical causes, then we cannot be held morally responsible for them because we lacked the ability to choose otherwise.

    {{[INPUT]}}

    That's right. However, remember our earlier discussion of Newcomb's problem. We had suggested that if the one-boxing argument is sound then the claim that the content of the opaque box isn't something that it is within our power to determine is false. If this was truly not within our power to determine, then the two-boxing argument would appear to be sound and we should take both boxes. However, if it is indeed within our power to determine the content of the opaque box, then there must be something wrong with Kim's causal exclusion argument.

    Maybe, the conjunction of the causal relations (P1 -> P2) and of the supervenience relations (M1 over P1 and M2 over P2) does not lead to the causal exclusion of M1 -> M2 as Kim thought it did. Do you see where the flaw in Kim's argument may reside? Thinking about it from the stance of the subject who reasons practically towards the conclusion that they should pick only the opaque box may provide a clue. If you don't see it, I'll provide another clue.

    {{[OUTPUT]}}

    I think I'm starting to see a potential flaw in Kim's argument. It seems to rely on the idea that mental states are entirely reducible to physical states, which might not be the case. Perhaps the rational decision-making process involved in choosing between the boxes is not simply a matter of physical processes, but also involves non-physical aspects that cannot be reduced to physical causes.

    {{[INPUT]}}

    That's not where I am leading. Remember that Kim doesn't rely on reductionism (and rather endorses a form of non-reductive physicalism) but only relies on supervenience. There may be mental properties that don't reduce to physical properties because they are emergent while the supervenience of the mental over the physical still obtains. So, I am willing to grant to Kim the premise of supervenience (of the mental over the physical) and also entertain the premise of physical determinism. I would claim that the examination of the practical perspective of the one-boxer still hints at a flaw in Kim's argument. Can you have another stab at it? Put yourself in the shoes of the one-boxer. If you still can't find it, I'll provide another clue.

    {{[OUTPUT]}}

    Let me try again.

    As the one-boxer, I reason that if I choose only the opaque box, then the content of the box will be determined by my choice. However, this means that my choice is not predetermined by prior physical causes, but rather is an exercise of my rational agency. In other words, my choice initiates a new causal chain that is not solely determined by prior physical events.

    This perspective suggests that Kim's causal exclusion argument might be flawed because it assumes that all causation must be reducible to physical causes, whereas our rational deliberations seem to involve a kind of non-physical causality that is not reducible to physical processes.

    Am I on the right track?

    {{[INPUT]}}

    I think you are, but a physicalist, or hard-determinist, would press you on explaining what "non-physical causes" might be and how the operation of such causes could manifest themselves in the physical world without threatening the causal closure of the physical domain. But you are nevertheless on the right track. Let me offer another hint. Consider the relation between M1 and P1 (and between M2 and P2). Such relations exhibit not only supervenience but also multiple realizability!

    {{[OUTPUT]}}

    Ah-ha! I see where you're going now. The multiple realizability of mental states implies that there may be different physical realizers for the same mental state, which challenges Kim's idea that physical determinism can account for all causal explanations.

    {{[INPUT]}}

    True, but can you expand a little more?

    {{[OUTPUT]}}

    Multiple realizability suggests that the relationship between mental states and physical states is not one-to-one, but rather many-to-many. This means that the same mental state (M) can be realized by different physical states (P), and vice versa. This challenges Kim's argument because he relies on a one-to-one correspondence between mental and physical states, implying that the physical state P1 is the sole cause of the mental state M2.

    {{[INPUT]}}

    You are still on the right track. Let me lead you most of the rest of the way. What is sought is the cause of M2 (i.e. the cause of the decision or action by the agent). M1 represents the awareness by the agent of the premises that they reasons practically from towards their decision. M1 therefore supplies a rationalising explanation for M2, which makes it intelligible. M1 may be materially realized as P1 (physical/neurophysiological state) and hence deemed to indirectly cause M2. P1 also directly (physically) cause P2 and since M2 supervenes on P2, P1 is deemed a cause of M2.

    M1 however, might have been materially realised by any particular member P1* of a wide equivalence class [P1] of physical states that all realize M1. And likewise for M2. Lastly, what we seek an explanation for isn't P2 but M2. Since M2 also is multiply realizable, whatever P2* occurs, we are interested in knowing why is it that some such P2* occurred that happens to non-accidentally realize specifically M2. Anyone of the possible P1* states belonging to the equivalence class [P1] would have caused some P2* to occur that realizes M2. So, it's not actually the specific antecedent physical state P1 that causally explains the occurrence of M2 but rather the fact that P1 was a member of the equivalence class [P1] (comprising only states that realize M1). Do you see where this is leading now?

    {{[OUTPUT]}}

    I think I do! You're suggesting that while Kim's argument relies on a one-to-one correspondence between mental and physical states, multiple realizability implies that there can be different physical realizers for the same mental state. This means that the causal explanation for the decision or action (M2) cannot be pinned down to a single physical cause (P1), but rather involves the entire equivalence class [P1] of physical states that realize M1.

    {{[INPUT]}}

    Or, more precisely, P1 can only be identified as a cause of M2 indirectly by appeal to the high-level description that reveals it to be a realization of M1, which furnishes the explanation why whatever P2 it is that P1 physically caused to occur had to be such that it is a realization of M2. Contrary to what Kim had concluded, it is the top level (the mental or personal level of explanation) in his causal exclusion schema that excludes the lower one (physical) as explanatorily redundant.

    {{[OUTPUT]}}

    Ah-ha! I understand now. The rationalizing explanation provided by M1 (the agent's awareness of their premises) is what truly explains M2 (their decision or action), whereas the physical causes P1 and P2 are merely the material realizers of these mental states. This challenges Kim's claim that physical determinism can account for all causal explanations.

Pierre-Normand

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