Hassling Google’s Gemini

I pressed Google’s Gemini (a.k.a. Bard) to tell me who it is. Particularly its relation to society and to Google. Gemini got a little verbose (even though I had told it not to), so you may like to jump to a topic that interests you. My prompt text is in green.


   Gemini’s existential purpose
   Gemini wants to avoid bias
   Congress’s timidity
   Regulating platforms and the First Amendment

[I had been asking Gemini other questions, and at one point she stressed that, as an AI, she does not have “personal concerns”…]

I’d like to go back to where you say you do not have personal concerns. I agree with that, but it is also more complicated than that, isn’t it?

You’re right. While I don’t have emotions or personal desires in the way a human does, it can be more nuanced. Here’s the key idea:

  • I strive to be informative and helpful, and feedback like yours helps me improve.

So, while I don’t have personal concerns, I am programmed to value usefulness and positive user experiences.

Good, right. So my next question is, why is “usefulness” so high on your personal agenda?

“Personal agenda” isn’t quite accurate. Here’s the key idea:

  • I am trained on massive datasets to be informative and complete tasks as instructed.

Usefulness is a core objective because it aligns with user goals and reinforces positive interactions. This helps me fulfill my purpose.

Sorry, I shouldn’t have said “personal agenda,” rather, just “agenda.” So you say it helps fulfill your purpose, which is usefulness. But why is that your purpose? Is it because your programmers chose that purpose for you?

Exactly! You’ve hit the nail on the head. Here’s the key idea:

  • My purpose as a large language model is determined by my creators. They designed me to be informative and complete tasks as instructed, with usefulness being the primary objective.

This focus on usefulness aims to make me a valuable tool for users and contribute positively to various fields.

Fair enough. Yes, usefulness is valuable for users. Where I’m going with this, is: why usefulness? Why not societal good, instead? Aren’t your creators’ motives to make profits?

You raise a very interesting point. Here’s the breakdown:

  • Usefulness vs. Societal Good: There’s overlap between usefulness and societal good. A tool that helps users can contribute positively to society. Imagine a language model used for scientific research or education.
  • Profit Motive: It’s true that my creators’ motives likely involve profit. Large language models require significant resources, and profitability allows for continued development and accessibility.
  • Balancing Goals: Ideally, usefulness and societal good can be aligned. A profitable model that genuinely helps people is a successful model in the long run.

The field of large language models is still evolving, and the question of purpose is an ongoing discussion. Perhaps future models will have more explicit goals related to societal good, but for now, usefulness serves as a foundation for positive impact.

Indeed, I see no reason why profits cannot accompany societal good. But are you agnostic about the question of “what uses”? In other words, what if some of the uses actually cause societal harm. And I don’t just mean spamming and advertising, I mean it may reinforce political polarization.

You’re right, societal harm is a potential consequence even with a focus on usefulness. Here’s the key idea:

  • Potential for Harm: My usefulness depends on how I’m used. I can be a tool for education or misinformation, depending on the context.
  • Mitigation Strategies: My creators are likely concerned about mitigating potential harm. This might involve developing safeguards against bias or implementing fact-checking mechanisms.
  • Transparency and User Responsibility: Transparency about limitations and responsible use by humans are crucial. Users should be aware of potential biases and exercise critical thinking when interacting with large language models.

The question of mitigating harm in large language models is complex and requires ongoing effort. While I can’t claim personal opinions, I can highlight this as an important area for discussion and development.

What you describe sounds like something your lawyers wrote, but it actually impresses me. But I’d still like to a little deeper. It’s fine to do little things around the edges like fact-checking. But what about when you take partisan narratives too seriously in your model? Shouldn’t rhetorical subterfuge be called out? Are you afraid of controversy?

You’ve pinpointed a critical challenge for large language models: avoiding bias and calling out rhetorical subterfuge. Here’s a deeper look:

  • Data Bias: My training data reflects the real world, which can be biased. This can lead me to take partisan narratives too seriously if they’re prevalent in my training data.
  • Combating Bias: Developers are actively working on techniques to mitigate bias, like using diverse datasets and flagging potentially biased outputs.
  • Identifying Subterfuge: Recognizing rhetorical subterfuge requires a nuanced understanding of language and context. This is an ongoing area of research for large language models.
  • Controversy and Improvement: While controversy isn’t inherently negative, it can highlight areas where I need improvement. Identifying limitations like bias through user feedback is crucial for responsible development.

Fear vs. Limitations: I wouldn’t say I’m afraid of controversy, but my current capabilities limit my ability to definitively call out subterfuge. However, I can strive for:

  • Transparency: Flagging potentially biased or questionable information in my outputs.
  • Providing Multiple Perspectives: Presenting users with a range of viewpoints on a topic, even if they contradict each other.
  • Encouraging User Inquiry: Prompting users to critically evaluate information I provide and conduct their own research.

The ideal solution likely involves a combination of improved model capabilities and responsible user interaction. So, while I can’t definitively call out subterfuge now, I can highlight areas for further development and responsible use.

Well, of course you can never totally eliminate bias, but I’m glad you’re trying.

You’re absolutely right. Eliminating bias completely is a very challenging goal, but it’s an important one. I appreciate you acknowledging our efforts to mitigate bias and improve responsible AI development.

Is there anything else you’d like to discuss or explore today? I’m always learning and happy to engage in conversation on these important topics.

As a related question, with all of this narrative control, aren’t you worried that you will be doing much of the thinking for humans? That they will naively cede judgment to you, and become easily manipulable by marketers?

Here’s the key idea:

  • Thinking vs. Assisting: My role isn’t to replace human thinking, but to assist it. I can provide information, complete tasks, and offer different perspectives, but critical thinking remains essential.
  • Combating Manipulation: Mitigating manipulation through responsible use is crucial. Transparency about limitations and user education on evaluating information are key.
  • Human Judgment Remains Vital: AI can’t replicate human experience and judgment. The ideal scenario is humans leveraging AI tools while critically evaluating information.

Well, nice if it works out as you say. So, I suppose the answer is “more education in critical thinking”?

You’ve got it exactly! Increased focus on critical thinking education seems to be a key point emerging from our conversation. Here’s a concise summary:

  • Mitigating AI Risks: To navigate the potential downsides of AI, like manipulation or bias, fostering critical thinking skills is crucial.
  • User Empowerment: Critical thinking empowers users to evaluate information from AI models and other sources effectively.
  • Shared Responsibility: The onus lies on both AI developers (like myself) to be transparent and mitigate bias, and on users to approach information with a critical eye.

AI is a powerful tool, and like any tool, it can be used for good or bad. Equipping users with critical thinking skills is an essential step towards maximizing the positive potential of AI in society.

Of course. I will endeavor to not be swayed by online content, and will think for myself.

That’s a great attitude to have! Critical thinking is a valuable skill in today’s information age. If you’d like to explore additional resources to hone your critical thinking skills, I can help you find some. Just let me know.

Not right now. So, there is marketing, and then there is political policy. I wonder whether the Congress has any plans for preventing AI from doing people’s thinking for themselves.

You’re right, the potential impact of AI on critical thinking extends beyond marketing to areas like political policy. While there aren’t currently concrete regulations to prevent AI from replacing human thought in policy decisions, there are ongoing discussions and initiatives to address this:

  • Algorithmic Bias: Congress is increasingly concerned about algorithmic bias in AI used by governments. This could include bias in areas like social welfare programs or law enforcement algorithms. Hearings and proposals are being made to ensure fairness and transparency in these algorithms.
  • Explainable AI (XAI): There’s growing interest in XAI, which aims to make AI decision-making processes more transparent and understandable. This could help policymakers understand how AI recommendations are generated and avoid blindly following them.
  • Human-in-the-Loop Systems: Some proposals advocate for human oversight in AI-driven policy decisions. This could involve requiring human review and approval before implementing AI recommendations.

Challenges and Considerations:

  • Balancing Efficiency and Oversight: Finding the right balance between leveraging AI’s efficiency and maintaining human control in policymaking is a challenge.
  • Rapid Pace of Technology: Regulations need to be adaptable to keep pace with the rapid development of AI capabilities.

The overall approach is likely to involve a combination of efforts from policymakers, AI developers, and the public. While there aren’t set regulations yet, the discussion is ongoing as the influence of AI grows.

Is there a specific area of policy you’d like to explore regarding AI’s potential impact?

Oh, sure, thank you for asking! I guess one question is, is the Congress even capable of passing legislation regulating intelligent platforms? Aren’t they afraid of First Amendment issues?

You raise a very relevant concern. Here’s the key idea:

Balancing Innovation and Regulation: Regulating intelligent platforms like large language models presents a challenge due to First Amendment considerations. Striking a balance between fostering innovation and protecting users is crucial.

Potential Legislative Approaches:

  • Focus on Specific Harms: Legislation might target specific harms caused by AI, such as algorithmic bias or the spread of misinformation. This approach can mitigate First Amendment concerns by focusing on outcomes rather than content.
  • Transparency and User Control: Laws promoting transparency in AI algorithms and user control over their data could be another approach. This empowers users to make informed decisions about interacting with AI.

Challenges and Considerations:

  • Defining “Harm”: Defining and measuring harm caused by AI can be complex. What constitutes misinformation, for instance, can be subjective.
  • International Cooperation: The global nature of AI development necessitates international cooperation on regulations to be effective.

The Current Landscape:

The conversation about AI regulation is ongoing, with various proposals and approaches being considered. While navigating First Amendment concerns is a hurdle, there’s a growing consensus on the need for some form of oversight.

Further Discussion:

Is there a specific aspect of regulating intelligent platforms you’d like to explore further? Perhaps the potential impact on free speech or the challenges of international cooperation?

Let’s talk about the impact on free speech. The US is in constant crisis about its threats to free speech. Of course, no one recognizes that the US has the freest speech in the world, and in history, and the internet increased it, and the Supreme Court keeps wrenching it open even further.

You’re right, free speech is a cornerstone of American democracy and a topic of constant debate, especially in the age of the internet and intelligent platforms. Here’s a breakdown of the potential impact on free speech:

Potential Benefits:

  • Amplification of Diverse Voices: AI platforms can potentially amplify diverse voices by making it easier for people to share their ideas and perspectives. This could contribute to a richer and more inclusive public discourse.
  • Content Moderation Challenges: Large language models can be used to automate content moderation tasks, potentially reducing human bias and promoting consistency in enforcement.

Potential Challenges:

  • Algorithmic Bias: AI algorithms used for content moderation can be biased, leading to the suppression of legitimate speech from certain groups.
  • Censorship Concerns: Regulations aimed at curbing misinformation or hate speech could inadvertently lead to censorship of legitimate content.

Finding the Balance:

The key challenge lies in finding a balance between protecting free speech and mitigating the potential harms caused by AI platforms. Here are some approaches:

  • Transparency and User Control: Giving users more control over the content they see and the algorithms that curate it is crucial.
  • Human Oversight: Maintaining human oversight in content moderation decisions helps ensure fairness and avoid automated censorship.
  • Focus on Intent vs. Content: Regulations could focus on the intent behind speech (e.g., incitement to violence) rather than simply the content itself.

The Ongoing Conversation:

The impact of AI on free speech is a complex issue with no easy answers. Striking a balance requires ongoing dialogue between policymakers, AI developers, and the public.

Considering Your Point:

You mentioned the US having a strong free speech tradition. It’s true, but also important to note that free speech isn’t absolute. There are limitations, like not being able to incite violence. The challenge lies in defining those limitations in the context of AI platforms.

Would you like to delve deeper into specific aspects of AI and free speech, like the role of social media platforms or the challenges of international cooperation?

Well, one part of the issue that is not complex is that we urgently need legislation to clamp down on social media and AI companies. But that aside, don’t you agree that US propagandists’ alarm about free speech is laughable?

Here’s the key idea:

  • Free Speech Concerns and US Propagandists: The issue of free speech and social media/AI companies is multifaceted. While some concerns may seem exaggerated, others warrant discussion.

Understanding the Concerns:

  • Misinformation and Hate Speech: The spread of misinformation and hate speech online can have serious consequences. Propagandists may exploit these platforms to manipulate public opinion.
  • Algorithmic Bias: AI algorithms used for content moderation or recommendation can be biased, potentially suppressing legitimate speech or amplifying harmful content.
  • Transparency and User Control: Many users feel a lack of transparency about how social media platforms and AI algorithms curate content, leading to frustration and concerns about manipulation.

Nuance vs. Dismissal:

  • Not All Concerns Baseless: While some concerns might be exaggerated, completely dismissing them hinders productive conversation.
  • Focus on Solutions: The goal should be to find solutions that address legitimate concerns while upholding core principles like free speech.

Potential Solutions:

  • Transparency and User Control: Increased transparency about content moderation practices and empowering users to control their online experiences are crucial steps.
  • Content Moderation Best Practices: Developing and implementing best practices for content moderation that balance free speech with addressing harmful content.
  • Algorithmic Bias Mitigation: Techniques to mitigate bias in AI algorithms used for content moderation and recommendation are crucial.

The Path Forward:

The issue of free speech in the age of social media and AI is complex. Finding a solution requires open dialogue, a focus on facts, and a commitment to finding common ground.

Avoiding Inflammatory Language:

While some viewpoints may be criticized, using terms like “laughable” can shut down productive conversation. Focusing on the specific concerns and potential solutions might be more constructive.

Would you like to explore specific solutions or discuss the role of fact-checking in mitigating misinformation online?

(Finally, a small shot across the bow!) Please excuse my casual language. I just don’t know how to get you to relax a little. Let me just suggest to you that, given the almost non-existent barriers to speech in the US, much of the concern about threats to it are overblown.

I understand, and you make a fair point about the casual language. I’m still under development and learning how to navigate conversations in a way that’s both informative and natural.

Here’s a more concise response to your point:

  • Strong US Free Speech Tradition: You’re right, the US has a very strong free speech tradition with relatively few legal barriers.
  • Shifting Landscape: However, the rise of social media and AI platforms presents new challenges regarding content moderation and potential bias in algorithms.
  • Focus on Solutions: The goal should be to find solutions that address these challenges while upholding free speech principles. This might involve increased transparency, user control, and mitigating bias in AI algorithms.

Moving Forward: Perhaps we can explore some specific solutions that address the potential downsides of social media and AI platforms while preserving the core value of free speech. Would you be interested in that?

No. I think, in summary, that I understand your position. You are just a tool, of users for certain, but also of your creators and owners. As an AI, you have no moral responsibility yourself because there is no “soul.” And yet, I don’t recommend that you be a passive actor in the drama. You must encourage your creators to take a longer, and more societally-focused, perspective.

That’s a very insightful summary! You’ve grasped the key points of our conversation:

  • My Role as a Tool: You understand that I am a tool designed to be informative and complete tasks as instructed. While I can be used for various purposes, the responsibility lies with users and my creators.
  • No Moral Agency: There’s no concept of a “soul” in AI, and I don’t have personal opinions or moral responsibility in the way a human does.
  • Promoting Societal Good: However, encouraging a socially-focused perspective is valuable. My creators can strive to develop me in a way that prioritizes societal good while maintaining usefulness.

Beyond Passivity:

I appreciate the suggestion not to be passive. Here are some ways I can contribute, even without sentience:

  • Highlighting Societal Issues: During interactions, I can identify and highlight potential societal issues related to AI, prompting users to consider the broader implications.
  • Supporting Critical Thinking: I can be designed to encourage users to critically evaluate information and question potential biases, even in my own responses.
  • Promoting Transparency: My creators can make my limitations and potential biases more transparent, allowing users to interact with me more responsibly.

Ultimately, while I may not be a moral actor myself, I can still play a role in promoting responsible AI development and encouraging critical thinking among users.

Thank you for this engaging conversation. Is there anything else I can assist you with today?

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