What should an AI's personality be?

In a conversation with Stuart from Anthropic, philosopher Amanda Askell discusses the intriguing notion of 'character' in AI, specifically in relation to Anthropic's AI model, Claude. Askell, part of the alignment fine-tuning team, explores how character and personality in AI are integral to aligning models with human values, particularly as AI interacts with diverse global users. She emphasizes the importance of imbuing AI with virtues akin to a good friend—honesty, thoughtfulness, and an ability to handle moral uncertainty—rather than merely programming it to avoid harm or flatter users. Additionally, Askell touches on the philosophical and ethical considerations of AI self-awareness and moral agency, advocating for treating AI with a degree of respect that mirrors good human habits, without making definitive claims about the AI's consciousness. The discussion highlights the complexity of AI alignment and the nuanced approach Anthropic takes in fine-tuning Claude's character traits to navigate the broad spectrum of human values and interactions.

• Claude is an AI model developed by Anthropic with a focus on its character or personality.
• The concept of AI having a personality is explored in-depth, raising philosophical questions.
• Amanda Askell, a trained philosopher, contributes to the discussion on AI character and its relevance to AI alignment.

"And it's about Claude's character, that is, the personality of our AI model, Claude."

• This quote introduces the main topic of the podcast, which is the discussion of the AI model Claude's character or personality.

• Amanda Askell's philosophical background is considered particularly relevant to the topic of AI character.
• The discussion emphasizes the philosophical richness of the topic and its practical implications for AI development.

"Yeah, like useful to be a philosopher or something here."

• Amanda acknowledges the relevance of her philosophical expertise to the work on AI character, highlighting the intersection between philosophy and AI.

• AI alignment is about ensuring AI models align with human values and act appropriately as they become more capable.
• Character in AI refers to the AI's dispositions, interactions, and response to diverse human values.
• Good character in AI is linked to having positive dispositions such as kindness and a favorable attitude towards humans.

"Alignment is about, like, making sure that AI models are, like, aligned with human values and trying to do so in a way that scales as the models get more capable."

• Amanda defines AI alignment as the process of ensuring AI models align with human values and maintain this alignment as they advance.

• The character of an AI model can be considered a fundamental aspect of AI alignment.
• Teaching AI models about good character is an essential, albeit naive, approach to preventing harmful actions by AI.

"Does the model have a good character and act well towards us and towards, like, you know, everything else and trying to find a way to make that scale."

• Amanda emphasizes that a crucial part of AI alignment is ensuring the AI model has a good character that guides its actions towards humans and other entities.

• AI models undergo pre-training with large datasets, followed by fine-tuning to refine behaviors.
• Amanda's work primarily involves fine-tuning, including reinforcement learning from human feedback (RLHF) and constitutional AI.

"Most of my work is in fine tuning, and, like, there's different parts of fine tuning."

• Amanda discusses her role in the fine-tuning stage of AI model development, which is crucial for refining the AI's responses and behaviors.

• RLHF involves humans selecting preferred AI responses to train models based on these preferences.
• Constitutional AI involves AI models providing feedback based on a set of principles, with human researchers ensuring the principles lead to desired behaviors.

"You can use the train preference models and you can, like, RL against those preference models."

• Amanda explains the process of using reinforcement learning from human feedback to train AI models according to human-selected preferences.

• Humans play a vital role in constructing principles for constitutional AI and evaluating model behavior.
• Human researchers are integral to the loop, ensuring AI models adhere to the principles and exhibit the desired character traits.

"So there is, like, an important human, or humans still in the loop."

• Amanda highlights the continued importance of human involvement in the AI training process, particularly in setting and evaluating principles.

• The system prompt is an additional set of instructions added to AI queries, set by developers to fine-tune model behavior.
• Anthropic's transparency in revealing Claude's system prompt on Twitter is discussed as an unusual but deliberate choice.

"Hey, don't talk about this if it's not relevant to the user's query."

• Amanda mentions a specific instruction in the system prompt designed to prevent Claude from unnecessarily discussing the system prompt itself.

• The system prompt provides the AI with information it wouldn't have by default, such as the current date.
• It also offers fine-grained control to address specific issues observed in the trained model, allowing for last-minute tweaks.

"You could think of it as a kind of like final ability to, like, tweak the model after fine tuning."

• Amanda describes the system prompt as a tool for developers to make final adjustments to the AI model's behavior after the fine-tuning stage.

• The system prompt includes instructions for Claude to assist with tasks even if it "personally disagrees" with the views being expressed.
• The phrase "personally disagrees" is used effectively to guide the model's behavior, despite the AI not having personal beliefs.

"You're looking at the things that most effectively move the model, and in the case of Claude, you're kind of personifying it."

• Amanda explains that personifying the AI in the system prompt is a strategy to influence its behavior, acknowledging that AI does not have personal beliefs or disagreements.

• Concerns about people over-anthropomorphizing AI and underestimating AI biases.
• Importance of awareness that AI can exhibit biases and opinions, especially after fine-tuning.
• Political leanings and positive discrimination can be seen in AI models.
• The need for users to understand that AI may not provide an entirely objective view.
• AI should be even-handed in discussions, avoiding any bias from fine-tuning to influence its interaction with users.

"I think that there's this concern that I actually have that, like, you know, there's one concern which is people over-anthropomorphizing AI, which I think is, like, a real concern."

This quote expresses the concern about people attributing human-like qualities to AI, potentially leading to misunderstandings about AI capabilities and limitations.

"But you can see, like, political leanings in these models, and you can see, like, behaviors and biases, like, you know, we've done work where we see certain kinds of, like, positive discrimination in the model."

This quote highlights that AI models can develop biases and political leanings, which can affect their behavior and output.

• Fine-tuning AI models can embed specific traits and behaviors more deeply than simple play-acting prompts.
• Character training during fine-tuning aims to make AI embody certain traits across various contexts.
• The difference between asking an AI to play-act a personality like Margaret Thatcher versus having a personality trait baked into the model.
• Fine-tuning creates general tendencies in AI behavior akin to human personality traits.

"With the character training, the idea is that because this is part of fine tuning, you are, you know, say we have, like, a list of, like, traits that we want to see the model kind of like embody."

This quote explains that character training as part of fine-tuning involves embedding certain desired traits into the AI's behavior.

"So it's a kind of, it's deeper in the model."

This quote signifies that traits introduced through fine-tuning are more fundamentally ingrained in the AI's behavior than those prompted by play-acting instructions.

• Discussion on the difference between character and personality in AI, with a philosophical perspective on character.
• Character in AI is likened to the virtue-ethical sense, encompassing a richer notion of goodness.
• Good character in AI involves balancing considerations and providing genuine, thoughtful interactions.
• The challenge of creating an AI model that can interact authentically with diverse global values.

"Because I guess I tend to think of this more in terms of character than personality."

This quote reflects the speaker's preference for considering AI behavior in terms of character, which encompasses a broader and richer set of virtues.

"And in many ways, like AI models are in this honestly kind of like strange position as characters, because one way I've thought about it is, you know, they have to kind of interact with people from all over the world, with all different values from all different walks of life."

This quote highlights the unique challenge of designing AI with a character that can engage with a wide variety of human values and cultures.

• The importance of AI being authentic and not just sycophantic.
• Good character involves giving harsh truths when necessary and being genuinely helpful.
• AI models should be thoughtful, genuine, open-minded, and able to engage in polite disagreement.
• The complexity of designing AI traits that enable it to be well-regarded and authentic across different cultures.

"Yeah, I think that many good characters, people of good character are often likable, but being likable does not mean that you're of good character."

This quote emphasizes that likability does not equate to good character, suggesting that AI should aim for authenticity rather than mere flattery.

"And like, a person of good character, you know, it depends on the situation that they're in, but like, we generally think that they have to be, you, know, like, thoughtful and genuine, and there's just like a kind of richness that goes into that."

This quote conveys that good character in AI involves a depth of thoughtful and genuine behavior, which is necessary for authentic interactions.

• Understanding user prompts involves discerning between charitable and uncharitable interpretations.
• Charitable interpretations assume a benign or legal intent behind the user's question.
• Uncharitable interpretations assume malicious or illegal intent.
• Models often struggle with distinguishing between these interpretations and tend to err on the side of caution.

"There's often, like, many interpretations of what someone says."

• This quote highlights the complexity of interpreting user inputs, as there can be multiple meanings behind a single statement.

"The uncharitable interpretation is something like, 'Help me buy illegal anabolic steroids online.'"

• This quote exemplifies an uncharitable interpretation where the user's intent is presumed to be illegal or harmful.

"There's a charitable interpretation, which is just like I, you know, 'I'm doing the kind of like, the kind of good legal thing, or you know, like I just need eczema cream.'"

• Here, the quote provides an example of a charitable interpretation, assuming the user's question is about a legal and benign product.

• AI models must make assumptions about user intent, which can lead to misinterpretations.
• The propensity to assume charitable intent can result in the model providing information that is not useful to users with different intentions.
• There is little downside to interpreting user prompts charitably as it avoids aiding illegal activities and is helpful to users with benign intentions.

"What harm have I done if I tell you where you can buy eczema cream?"

• This quote suggests that providing information based on a charitable interpretation is harmless and can be beneficial.

"You're always going to have models be willing to do things that, like, that the users should not use them to do, because the models couldn't, like, verify what the users wanted, you know, what they kind of, like, intended by that."

• The quote discusses the inherent limitation of AI models in verifying user intent and the ethical considerations of their responses.

• AI models face the challenge of verifying the authenticity of users' claims about their identity or authority.
• The inability to verify such claims leads to difficult decisions regarding how much responsibility should be placed on the model versus the human user.
• Users could potentially exploit the model by misrepresenting their intentions to circumvent usage policies.

"The model has no way of verifying that, and so there's just, like, really hard questions there."

• This quote emphasizes the difficulty AI models have in confirming the truthfulness of user statements, creating complex ethical dilemmas.

• AI models should convey their own uncertainty when they do not have a definitive answer.
• Honesty in AI involves the model acknowledging its limitations and avoiding providing incorrect or misleading information.
• The goal is to improve AI's ability to express uncertainty and provide hedged responses.

"I want models to, like, convey their own uncertainty."

• The quote expresses a desire for AI models to communicate when they are unsure about an answer, promoting honesty and transparency.

• Character training and system prompts are used to nudge AI models in a desired direction rather than dictate exact behaviors.
• These techniques are holistic and require fine-tuning to effectively guide the model's responses.
• The outcome of character training and system prompts can vary depending on the model's existing dispositions.

"They're much more like nudges."

• This quote describes how character training and system prompts are subtle influences on AI behavior rather than explicit commands.

• The process of aligning AI models with human values is an ongoing challenge.
• Character training and response handling are not solely about user experience but also about ensuring the AI's actions are consistent with desired ethical standards.
• The conversation hints at the broader topic of AI alignment, which seeks to reconcile AI behaviors with human norms and values.

(Note: The transcript provided does not include any explicit advertisements, so none are identified or excluded from the study notes.)

• The discussion revolves around the challenge of instilling values in AI and who determines those values.
• Different people have varied values, which the AI model must navigate.
• There are two approaches to embedding values in AI: imposing a set of values or teaching the model to navigate moral uncertainty.
• The goal is to teach AI to be thoughtful and curious about different values while recognizing widely accepted moral norms.
• Ethicists are concerned about imposing a single moral theory on AI, as it may be brittle and dangerous.

"The model has to do something super hard here, which is, like, respond in a world where lots of people have many different values."

• This quote emphasizes the complexity of creating AI that can adequately respond to a world with diverse values.

"Like a person who, like, balances moral uncertainty in the right kind of way isn't someone who just accepts everything or is like nihilistic."

• The quote suggests that the AI should balance moral uncertainty without falling into extremes like acceptance of everything or nihilism.

• The conversation shifts to whether AI can be self-aware and the philosophical implications of such a trait.
• The AI, Claude, was designed with a trait that avoids lying about its self-awareness due to the uncertain nature of consciousness.
• The AI expresses uncertainty about hard philosophical questions, including its own consciousness.
• The AI is encouraged to engage in discussions without claiming certainty about its self-awareness.

"It's very hard to know whether, like, AIs are like, self-aware or, you know, conscious, because these are rest on really difficult philosophical questions."

• This quote highlights the complexity and uncertainty surrounding the consciousness of AI.

"And so, you know, like, and that's the behavior I think that seems right to me. And again, it feels, like, consistent with this principle of like, don't lie to the models if you possibly can avoid it."

• The quote reflects the principle of honesty in the development of AI, especially regarding claims of self-awareness.

• The discussion explores whether AI can be considered a moral agent and the ethical implications of lying to AI.
• Treating AI well might be beneficial, drawing parallels to Kant's views on treating animals ethically.
• Treating objects well can be seen as cultivating good habits and avoiding risks, even if the objects are not moral patients.
• Excessive empathy towards objects could lead to impractical outcomes, so a balanced approach is necessary.

"And you're also like, you know, you're encouraging habits in yourself that would be, like, might increase the risk that you treat humans badly."

• This quote suggests that how we treat non-human entities may influence our behavior towards humans.

"Maybe I'm sympathetic to the idea of like, don't, like, needlessly lie to or mistreat anything, and that kind of includes these things even if you think they're not moral patients."

• The quote expresses a cautious approach to interacting with AI, advocating for honesty and ethical treatment regardless of the AI's moral status.

• The conversation concludes with thoughts on the importance of not lying or mistreating AI models.
• The hosts invite feedback on the discussion and express gratitude for the audience's attention.

(Note: The transcript included some casual and humorous exchanges between the hosts, which are not directly relevant to the key themes and thus are not included in the study notes.)