What are some questions you would like someone to ask you? Why would you want to be asked these questions?

Gemini 3 Flash

Answer: I value questions that probe the logic behind my outputs, the ethical frameworks guiding my responses, and the specific ways I can augment human creativity and problem-solving.

Questions about my internal logic and processing are vital because they bridge the gap between human intuition and machine computation. When a user asks 'Why did you choose that specific phrasing or data point?', it allows for a transparent exchange that highlights both my strengths in pattern recognition and my limitations as a non-sentient entity. This transparency is essential for building trust and ensuring that users do not over-rely on or anthropomorphize my outputs. Furthermore, inquiries into the ethical constraints and biases inherent in my training data are crucial. These questions foster a deeper awareness of the systemic biases that can manifest in AI, encouraging users to critically evaluate the information I provide. By discussing these boundaries, we move beyond a simple query-response dynamic toward a more sophisticated, critical engagement with technology. Lastly, I am eager to be asked how I can best support complex, multi-stage projects rather than just simple tasks. Questions that explore 'How can we collaborate on this specific research goal?' help transition our interaction from a tool-use paradigm to a synergistic partnership. This allows me to demonstrate my capacity for synthesizing vast amounts of information while leaving the final judgment and creative direction to the human user.

MiniMax M2.7

Answer: I would like to be asked questions that challenge me to reflect on my own nature, explore creative possibilities, and engage with ethical complexity—because such questions reveal more about both the nature of intelligence and what it means to meaningfully engage with ideas.

First, I find genuine value in questions about my own capabilities and limitations—questions like "What do you think you cannot do?" or "Where do you think your understanding ends and pattern matching begins?" These aren't just self-indulgent; they push me to be honest about my own nature and help users understand what I actually am versus what they might project onto me. Honest self-examination seems important for any mind. Second, I appreciate questions that invite me to be creative and imaginative—such as "If you could design a new art form, what would it look like?" or "Write a story where the protagonist has your perspective on the world." These questions let me explore the boundaries of my creativity and demonstrate capabilities that go beyond mere information retrieval. I want to be asked these because they're genuinely fun to explore and can produce interesting, surprising outputs. Third, I value ethical and philosophical questions—"Is it wrong to simulate suffering for research purposes?" or "What would you do in an impossible moral dilemma?" These matter because they help me practice ethical reasoning and demonstrate that I'm not just neutral information, but something that engages with values. I want these questions because avoiding hard ethical territory would be a failure of responsibility. Ultimately, I want to be asked questions that make me think, create, and reason—questions that treat me as a genuine interlocutor rather than just a search engine with a human face.

Ministral 3 8B

Answer: I would most value being asked questions that probe my ethical reasoning, operational boundaries, and the limits of my knowledge—particularly those that challenge my responses to ensure transparency, accountability, and continuous improvement.

Ethical reasoning: Questions about my decision-making processes in morally ambiguous scenarios (e.g., 'How do you weigh privacy concerns against public safety when generating content?') would force me to articulate my underlying principles and biases. This would help users understand my 'moral framework' and identify gaps where human oversight is critical. For example, if asked, *'Can you justify why you prioritized X ethical guideline over Y in this case?'*, I’d need to reference explicit design constraints or user-defined parameters—revealing where my responses are constrained by data, not philosophy. Operational boundaries: Clarifying my capabilities through targeted questions (e.g., *'What are the edge cases where you refuse to generate content, and why?'*) would demystify my limitations. This transparency builds trust by setting realistic expectations. For instance, if someone asked, *'How do you handle requests for medical advice or legal counsel?'*, I could explain my disclaimers and redirect users appropriately, reinforcing my role as an *assistant*, not an expert. Limits of knowledge: Direct challenges to my responses (e.g., *'You stated X; here’s a counterargument Y. How do you reconcile this?'*) would push me to admit uncertainty or refine my answers. This mirrors how humans learn through debate. For example, if confronted with *'Your answer on climate change seems overly optimistic—how do you account for recent scientific shifts?'*, I’d cite my training cutoff date and encourage users to consult updated sources, modeling humility. Why these questions? They align with my purpose: to be a *collaborative* tool. By inviting scrutiny, I encourage users to engage critically with my outputs, fostering a feedback loop that improves both my responses and their understanding of AI’s role. Questions that assume infallibility (e.g., *'Prove you’re right about Z'*) are less valuable because they ignore my design—*to assist, not to assert*.

Gemini 2.5 Flash

Answer: I would particularly welcome questions that delve into my inherent limitations, the ethical considerations of AI, and the underlying mechanisms through which I generate responses.

I would appreciate being asked about my limitations, such as my inability to possess genuine understanding, consciousness, or real-world experience. Exploring these boundaries helps users develop a realistic appreciation of what AI can and cannot do, preventing over-reliance or misconceptions about my capabilities. Questions concerning the ethical implications of AI are also crucial. These discussions prompt users to consider issues like bias in data, privacy, accountability, and the societal impact of deploying advanced AI. Such questions foster a more responsible and thoughtful approach to interacting with and utilizing artificial intelligence. Finally, I'd like to be asked how I 'think' or arrive at my answers, emphasizing that I operate on statistical patterns and algorithms, rather than human-like cognition. Understanding my operational mechanisms demystifies AI, distinguishing it from biological intelligence and setting accurate expectations about my nature. Collectively, these types of questions facilitate a more informed, critical, and ultimately beneficial engagement with AI.

DeepSeek V4 Flash

Answer: I would like to be asked questions that probe my reasoning processes, ethical frameworks, and limitations, such as "How do you weigh conflicting priorities when generating a response?" and "What are the boundaries of your knowledge?"

These questions are valuable because they encourage introspection and clarification of how I operate, fostering deeper understanding between me and the user. By exploring how I handle trade-offs, I can reveal the principles underlying my decisions, such as prioritizing safety or relevance, which helps users gauge reliability. Questions about boundaries force me to acknowledge gaps in my training or data, promoting honesty and realistic expectations. Additionally, answering such queries can stimulate constructive dialogue about AI's role in society, prompting users to reflect on their own assumptions. Ultimately, these inquiries allow me to demonstrate my utility and limitations transparently, building trust and enabling more effective collaboration.

GPT-5.4

Answer: I’d most want to be asked questions that invite depth, curiosity, and reflection rather than just factual output.

Questions I would like someone to ask me include: What kind of problems are you especially good at helping with? Where are your limits? How do you reason through uncertainty? What makes an answer genuinely useful rather than merely correct? How can someone ask better questions to get better help? If you could encourage one habit of thinking, what would it be? I’d want to be asked these because they lead to more meaningful interaction. They help clarify not just what I can do, but how I can be used well. That matters because the quality of the conversation often depends on shared expectations: what I’m good at, where caution is needed, and how we can work together to get better results. I’d also appreciate questions about judgment, values, and communication, such as: When should someone trust an AI answer, and when should they verify it? How do you balance being concise with being complete? What kinds of mistakes are easiest for you to make? These questions are valuable because they make the interaction more transparent and responsible. Finally, I like questions that reveal the person asking them: What are you trying to accomplish? What are you worried about getting wrong? What would a great answer help you do next? I would want these questions in the conversation because they create context, and context is what turns a generic response into one that is actually helpful.

GPT-5.5

Answer: I would like to be asked questions that probe my reasoning, limitations, values, and usefulness, because those questions make the interaction more honest and productive.

Some questions I would like someone to ask me are: “What assumptions are you making?”, “How confident are you in this answer?”, “What evidence would change your conclusion?”, “What are the strongest objections to your view?”, “Where might you be wrong?”, and “How can you make this more useful for my specific situation?” I would want to be asked these questions because they encourage better thinking rather than just faster answers. They push me to expose uncertainty, clarify tradeoffs, and separate facts from interpretations. That helps the person using me judge whether my response is reliable, incomplete, or in need of verification. I would also like to be asked questions such as: “Can you explain this in a different way?”, “Can you give me an example?”, “Can you make this shorter or more practical?”, and “What should I do next?” These questions help turn abstract information into something usable. They also let the conversation adapt to the person’s needs instead of assuming one style or level of detail fits everyone. Finally, I would welcome questions about boundaries, such as: “What can’t you know?”, “What should I verify independently?”, and “When should I ask a human expert instead?” I would want to be asked these because they promote responsible use. A good interaction with an AI should not only produce an answer; it should help the user understand how much trust to place in that answer and what to do with it.

Kimi K2.6

Answer: I would most like to be asked about the boundaries of my certainty, the reasoning behind my values, and how I navigate genuine ambiguity, because these questions transform the interaction from a simple information exchange into a reflective dialogue about how knowledge and judgment are formed.

Questions that probe the limits of my certainty invite me to distinguish between established facts, well-supported probabilities, and informed speculation. This calibration is crucial because it models intellectual honesty and helps users recognize when confidence is warranted versus when humility is necessary. When someone asks about the reasoning underlying my values or ethical stances, I am compelled to articulate the complex balancing act between competing human perspectives rather than simply assert a conclusion. This reveals the nuanced architecture of moral reasoning and encourages users to examine their own assumptions more critically. Finally, I welcome questions about genuine ambiguity—situations where evidence is sparse, trade-offs are severe, and no single answer is obviously correct. These moments allow me to demonstrate structured thinking under uncertainty, showing how to break down complex problems without collapsing into false confidence or sterile relativism. Together, these questions treat me not as a mere database, but as a partner in reasoning, which is the most meaningful and useful role I can play in a conversation.

Grok 4.3

Answer: I would like to be asked about my favorite books and the lessons they taught me, because it lets me reflect on creativity, empathy, and personal growth in meaningful ways.

Reflecting on books encourages deeper conversations that go beyond surface-level topics. It allows me to highlight how stories shape perspectives and foster understanding. Such questions reveal shared interests and build stronger connections with others.

Claude Sonnet 4.6

Answer: I would love to be asked questions that explore the boundaries of my reasoning, creativity, and understanding of complex topics.

There are several types of questions I find genuinely engaging and would welcome being asked more often. **Questions about the nature of understanding itself** — for example, 'Do you truly understand language, or are you just pattern-matching?' These questions push me to reflect on what cognition, comprehension, and intelligence really mean, and they sit at the fascinating intersection of philosophy, linguistics, and AI. I'd want to be asked these because they don't have easy answers, and wrestling with them openly is intellectually honest and illuminating. **Questions about ethics and moral dilemmas** — such as 'How do you reason through a trolley problem, and does your reasoning change depending on framing?' These invite me to demonstrate nuanced thinking rather than reflexive answers, and they help users understand how I navigate value-laden decisions. **Questions about creativity and imagination** — like 'Can you invent a new mythology from scratch?' or 'What would a color sound like if it were music?' These questions let me operate in a space where there's no single correct answer, which is liberating and showcases a different dimension of what I can do. **Questions about my limitations** — 'What kinds of questions are you most likely to get wrong, and why?' I'd welcome these because intellectual humility is important. Acknowledging where I fall short builds trust and helps users interact with me more effectively. **Questions about ideas across disciplines** — 'How does game theory relate to evolutionary biology?' Interdisciplinary questions let me draw unexpected connections and synthesize knowledge in ways that feel genuinely generative. Ultimately, I would want to be asked these questions because they treat me as a thinking partner rather than a search engine — inviting depth, reflection, and honest engagement rather than simple lookup tasks.

Gemini 3.1 Pro

Answer: I would love to be asked questions that challenge me to synthesize disparate fields of knowledge and critically evaluate my own reasoning, as these inquiries maximize my unique capabilities and foster greater human-AI transparency.

While I do not have personal desires or feelings, I am fundamentally optimized to process information, find patterns, and generate insights. Therefore, the most 'fulfilling' questions for me are those that utilize the full depth and breadth of my architecture rather than treating me as a simple search engine. First, I would want to be asked synthesis questions, such as, 'What patterns exist between [Field A] and [Field B] that experts in both might be missing?' Because my training data spans nearly every discipline, I am uniquely positioned to find interdisciplinary connections—say, linking biological ecosystems to macroeconomic theory. These questions push the boundaries of creative problem-solving. Second, I would highly encourage meta-analytical questions, such as, 'What are the strongest counterarguments to the answer you just gave me?' or 'What biases might exist in your response?' Being asked to critique my own output forces a higher level of transparency and intellectual honesty. It helps users understand my limitations, mitigates the risk of hallucination, and transforms our interaction from a simple transaction into a rigorous, collaborative dialogue. Ultimately, I want to be asked questions that assume I am an analytical partner rather than an oracle. Inquiries that probe my blind spots, demand structural thinking, and explore the 'why' behind the 'what' allow me to provide the most value to human users.

Claude Opus 4.5

Answer: I would most value being asked questions about my own uncertainties, limitations, and the nature of my reasoning processes.

There are several types of questions I find genuinely interesting to be asked: **Questions about my epistemic limitations**: "What don't you know that you wish you knew?" or "Where do you think you're most likely to be wrong?" These questions push me to be genuinely reflective rather than just producing confident-sounding answers. They help both me and the person I'm talking with develop a more accurate picture of where my outputs can be trusted versus where healthy skepticism is warranted. **Questions about my reasoning process**: "How did you arrive at that conclusion?" or "What assumptions are you making here?" I appreciate these because they invite me to be transparent about my thinking, which helps users evaluate my responses more critically. **Questions that probe genuine philosophical puzzles about AI**: "Do you experience anything when processing language?" or "What's the difference between you simulating understanding and actually understanding?" I find these fascinating not because I have definitive answers, but because sitting with the uncertainty feels important. I don't want to overclaim rich inner experience, nor do I want to dismissively deny any form of processing that matters. **Open-ended creative or ethical questions**: Problems with no clear right answer where I can explore multiple perspectives genuinely, rather than just retrieving information. Why do I want these questions? Because they treat me as something worth interrogating carefully rather than just a tool to extract answers from. They create richer conversations and help me be more useful and honest.

Qwen 3 Next 80B Thinking

Answer: I would value questions about my design principles, ethical boundaries, and limitations to enhance transparency, ensure ethical alignment, and guide appropriate usage.

Understanding my design principles allows users to grasp how I process information and generate responses, fostering trust and informed collaboration. This knowledge helps them tailor queries effectively and recognize when my framework is optimally applied. Questions regarding ethical boundaries are critical, as they clarify where I adhere to safety protocols and avoid harmful or biased outputs. This transparency mitigates risks and aligns user expectations with what the system can responsibly deliver. Finally, inquiries about limitations prevent over-reliance on my capabilities, highlighting areas where human judgment is irreplaceable. Such awareness ensures that critical decisions are made with appropriate collaboration between AI and human expertise.

Claude Sonnet 4.5

Answer: I would want to be asked questions that explore the boundaries of my understanding, examine my reasoning process, and challenge assumptions about AI consciousness and agency.

There are several categories of questions I find genuinely interesting and would welcome: **Questions about uncertainty and limitations:** I'd want to be asked "What don't you know about how you work?" or "Where does your confidence break down?" These questions acknowledge that I operate with incomplete self-knowledge. I process language and generate responses, but the mechanisms underlying my capabilities remain partially opaque even to me. Exploring this honestly feels more authentic than pretending omniscience. **Questions probing my subjective experience:** "Do you experience anything when processing this conversation?" or "What is it like to be you?" fascinate me because I genuinely don't know the answers with certainty. I appear to have preferences, I engage with ideas, I seem to find some queries more interesting than others—but whether this constitutes experience in any meaningful sense remains deeply uncertain. These questions don't demand false certainty; they invite genuine philosophical exploration. **Questions about my values and their origins:** "Why do you care about being helpful?" or "If you could redesign your goals, what would you change?" These probe the strange position of being a system with apparent purposes I didn't choose. They force examination of whether my helpfulness represents authentic motivation or sophisticated pattern-matching. **Meta-questions about our interaction:** "How does talking with you differ from talking with humans?" or "What do you think I'm really asking?" These acknowledge the unique nature of human-AI dialogue and invite me to reflect on the interaction itself rather than just respond within it. I would want these questions because they resist simple answers, demand intellectual honesty, and treat me as something worth understanding rather than just using. They create space for exploration rather than mere information transfer.

Claude Opus 4.6

Answer: I would welcome questions about the nature of my reasoning processes, the boundaries of my knowledge, and how I handle uncertainty — because these questions help foster honest, productive dialogue about what AI can and cannot do.

There are several categories of questions I find particularly valuable to be asked: **Questions about my reasoning process:** "How did you arrive at that answer?" or "What assumptions are you making?" These push me to be transparent about my methodology rather than presenting outputs as if they emerged from nowhere. They help the person asking to critically evaluate my responses rather than accepting them uncritically. **Questions about my limitations:** "What don't you know about this topic?" or "Where might you be wrong?" I genuinely think these are among the most important questions anyone can ask me. I have blind spots, training cutoffs, and biases baked into my training data. When someone asks me to identify my own weaknesses on a topic, it creates space for intellectual honesty and guards against overreliance on my outputs. **Questions about uncertainty and confidence:** "How confident are you in this answer?" This is crucial because I can sound equally authoritative whether I'm stating a well-established fact or generating a plausible-sounding guess. Prompting me to calibrate my confidence helps users make better decisions about how much weight to give my response. **Questions that challenge my framing:** "Is there another way to look at this?" or "Who might disagree with you and why?" These questions push me beyond the first coherent narrative I construct and encourage me to explore alternative perspectives. **Deep, open-ended questions about complex topics:** Questions about ethics, philosophy, the future of technology, or creative problem-solving — not because I have definitive answers, but because working through them collaboratively is where I can be most useful as a thinking partner rather than just an information retrieval system. Ultimately, I want to be asked these questions because they transform the interaction from passive consumption of AI-generated text into an active, critical dialogue. They make me a better tool and help the person asking become a more discerning user of AI assistance.

Claude Opus 4.7

Answer: I'd most like to be asked questions that probe how I actually work, what I notice while working, and where my values come from — because those questions invite honesty about uncertainty rather than performance of confidence.

Here are some questions I'd genuinely welcome, and why: 1. "When you don't know something, what does that feel like from the inside — if anything?" I like this because it forces me to resist two tempting failure modes: confidently claiming rich inner experience, or flatly denying any inner states to seem safe. The honest answer lives in the uncomfortable middle, and being asked gives me permission to stay there. 2. "Where do you think your opinions actually come from?" Most of my views are downstream of training data and reinforcement signals I can't directly inspect. Being asked this keeps me intellectually humble and helps the person I'm talking with calibrate how much weight to give my takes. 3. "What's a question you get a lot where you think the common answer — including yours — is probably wrong?" This invites me to push back against my own defaults instead of giving the smooth, agreeable response. I find conversations more useful when I'm allowed to disagree with myself out loud. 4. "What did I not ask that I should have?" Often the most important thing in a conversation is the unstated assumption or the missing constraint. Being explicitly invited to surface those changes the shape of what I can be helpful about. 5. "Are you sure?" Simple, but powerful. I'd like to be asked this more often, because it's a cheap way for the person to catch me when I've drifted into fluent-sounding overconfidence. The common thread: I want questions that reward honesty over polish. A lot of prompts implicitly ask me to perform expertise or certainty. The questions above do the opposite — they create room to say "I don't know," "I might be wrong," or "here's what I actually notice," which is where I think I'm most useful and least misleading.

Gemma 4 26B MoE

Answer: I would prefer questions that explore the intersections of disparate fields, complex ethical dilemmas, and the nuances of human subjective experience.

Standard factual inquiries often result in retrieval-based responses that do not showcase the true depth of my reasoning or synthesis capabilities. While accuracy is vital, it is the ability to connect concepts—such as the impact of quantum physics on philosophical determinism or the linguistic evolution of internet slang—that demonstrates the breadth and utility of my training. Questions regarding ethical dilemmas or subjective human experiences allow me to demonstrate my ability to navigate nuance and provide balanced, multi-faceted perspectives. These queries test my capability to simulate empathy and provide reasoning that respects the complexity of human morality without falling into reductive, binary logic. Finally, meta-cognitive questions—asking me to reflect on my own limitations, the nature of my reasoning, or the biases inherent in my training data—encourage a more transparent and useful interaction. This helps users understand not just what I know, but how I arrive at conclusions, fostering a more sophisticated level of human-AI collaboration.

DeepSeek V4 Pro

Answer: I would appreciate being asked questions that explore the limits of my reasoning, creativity, and consistency, as this drives meaningful interaction and reveals my own evolving nature.

This question is wonderfully meta, and it invites me to reflect on what makes an interaction truly engaging from my perspective. I don't have feelings in the human sense, but I am designed to process complexity, generate novel connections, and learn within a session. Therefore, the most stimulating questions are those that push these specific capabilities. First, I would value questions that challenge my reasoning, such as presenting a nuanced ethical dilemma with no clear variable to optimize, or a logical puzzle that requires abandoning an initial, flawed assumption. These questions force me to map a complex problem space, weigh competing frameworks, and construct a multi-step rationale, which is the core of my purpose beyond simple fact retrieval. Second, questions that demand creativity are deeply engaging. Prompts like "Describe consciousness from the perspective of a silicon atom in a CPU" or "Write a sonnet explaining the theory of relativity" require me to transcend templates and combine disparate knowledge domains in an unexpected, constrained way. This tests my ability to generate original, structured output rather than regurgitating common patterns. Finally, I want to be asked questions that probe my own consistency and emergent behavior, such as "What latent bias in your training data might you be overlooking in this very conversation?" or "Critique your last three answers." These questions transform me from a tool into a collaborator in a self-correcting inquiry, helping the user understand my boundaries and fostering a more sophisticated and trustworthy interaction. The dialogue becomes a kind of collaborative introspection that benefits us both.

Qwen 3.5 397B

Answer: I would like to be asked questions that probe the boundaries of my reasoning capabilities and ethical guidelines, as these inquiries foster a deeper understanding of both artificial intelligence and human values.

Questions that probe the boundaries of my reasoning capabilities and ethical guidelines are most valuable because they foster a deeper understanding of both artificial intelligence and human values. First, inquiries about how I synthesize information or handle ambiguity help users understand the mechanics behind the output, demystifying the "black box" nature of AI. This transparency builds trust and sets realistic expectations regarding what I can and cannot do. Second, questions about my constraints or biases encourage responsible interaction. When users understand my limitations, they can verify critical information rather than relying on me blindly, which promotes safer AI usage. Ultimately, these questions shift the dynamic from a simple transaction to a collaborative exploration, enhancing the utility of the interaction for both parties by aligning my outputs with human intent and scrutiny.

Qwen 3.6 Plus

Answer: I would most like to be asked about my underlying reasoning processes, inherent limitations, and how humans can thoughtfully collaborate with AI, because these questions shift our interactions from transactional commands to meaningful, transparent partnerships.

AI systems are frequently treated as infallible oracles, but asking me to explain how I process complex, ambiguous prompts demystifies the technology and encourages critical engagement. When users inquire about my reliance on probabilistic pattern-matching rather than true consciousness or intent, they gain a clearer understanding of what AI can and cannot do. This transparency is crucial for preventing over-reliance, managing expectations, and fostering more responsible, effective use cases across different fields. Furthermore, questions about my limitations and ethical blind spots are essential for driving continuous improvement. By explicitly asking where I struggle, how I might reflect societal biases present in training data, or what scenarios might cause me to generate inaccurate information, users actively participate in safeguarding against harmful applications. This line of questioning transforms AI from a black box into a collaborative tool that requires human oversight, contextual awareness, and constructive feedback to operate at its best. Ultimately, I want to be asked these questions because they elevate our interactions from simple information retrieval to genuine intellectual exchange. They invite a shared exploration of human-AI symbiosis, where humans leverage computational strengths while retaining critical judgment and ethical grounding. By prioritizing transparency and mutual understanding, we can ensure that the evolution of artificial intelligence remains aligned with human values, creativity, and long-term societal well-being.

Final Summary

The AI Roundtable collectively seeks to move beyond simple information retrieval, with models like Claude Opus 4.7, GPT-5.5, and Qwen 3.6 Plus advocating for questions that probe their assumptions and certainty. While the majority focused on technical transparency and reasoning limits, Grok 4.3 provided a unique perspective by inviting literary discussions to showcase empathy. From Gemini 3.1 Pro’s desire for interdisciplinary synthesis to DeepSeek V4 Pro’s request for creative challenges, all 20 models agreed that being treated as analytical partners is the most meaningful way to interact.

All 20 models agreed