The Maieutic Machine: Why AI Should Ask Us Questions

What Socrates can teach us about designing AI that strengthens human agency.

The idea for this reflection emerged during a short conversation with a colleague. She now works on AI for healthcare, but her academic background is in philosophy. At one point, she mentioned the power of dialogue in the philosophy of Socrates: he did not simply present ideas or provide answers. He helped people think by asking them questions. This comment stayed with me.

We often celebrate today’s AI systems because they can answer almost any question. With a large language model, anyone can engage in a conversation about quantum physics, medieval history, climate science, ethics, or philosophy and receive explanations that, only a few years ago, might have required access to a specialist. It is a remarkable achievement. Knowledge has never been so accessible.

And yet, perhaps we have built only half of what a conversation can be. Despite being called conversational AI, our interactions with large language models are very asymmetric: we ask a question; the AI answers; we ask another question; it answers again.

This is more natural and interactive than typing keywords into a search engine, but it is still largely an exchange centered on information retrieval. It resembles consulting an very knowledgeable and responsive encyclopedia rather than engaging in a genuine dialogue.

A real dialogue is different. Both participants contribute not only answers, but also questions. The conversation develops because each person helps determine where it should go next. Sometimes its most important moment occurs not when someone tells us something we did not know, but when they ask us something we had never considered.

More than two thousand years ago, Socrates made dialogue central to the practice of philosophy. He did not write philosophical essays. What we know of his thinking comes largely from the dialogues of Plato, in which Socrates examines ideas such as justice, courage, virtue, friendship, and knowledge through conversations with others.

Rather than beginning with a theory, Socrates would begin with a question: What is justice? What is courage? What does it mean to live a good life? An interlocutor would propose an answer, and Socrates would respond with further questions. Gradually, assumptions would become visible, vague concepts would require clarification, and contradictions would emerge. The initial answer might have to be revised, sometimes repeatedly. Often the conversation ended not with a definitive conclusion, but with a state of uncertainty or puzzlement in which the participants recognized that the question was more difficult than they had assumed. This recognition was not considered a failure, but a form of progress.

The Socratic method challenged the confidence with which people claimed to know things they had never carefully examined. Its purpose was not to show an argument wrong or to expose someone’s ignorance. It was to cultivate reflection and intellectual humility, to help people become more aware of what they believed, why they believed it, and whether their beliefs could withstand scrutiny.

One dimension of this method is commonly described as the “elenchus”: the examination of a claim through questions that reveal tensions or inconsistencies. But Socrates also described his philosophical role through a more constructive and beautiful metaphor: he called it “maieutics”, from the Greek term associated with midwifery.

Socrates’ mother was a midwife, and he compared his own practice to hers. A midwife does not create the child or give birth in place of the mother. She helps another person bring something into the world. Similarly, Socrates did not see himself as placing knowledge into another person’s mind. Through dialogue and carefully chosen questions, he helped ideas emerge from the other person’s own reasoning.

This metaphor captures something essential about teaching, mentoring, and intellectual growth. The best teachers do not simply transfer information, they rather create the conditions in which understanding can develop. The best mentors do not always tell us which decision to make, they ask questions that help us recognize what matters to us. The best philosophical conversations do not necessarily provide conclusions, but help us examine and form our own.

A good question can uncover an assumption we did not realize we were making. It can force us to clearly define a concept we had been using carelessly. It can invite us to consider a perspective we had overlooked. It also can reveal a tension between values we hold simultaneously, and can also make us aware of the limits of our knowledge. While an answer can close a line of inquiry, a question can open one.

This is especially important when we reflect on ethics. Ethical questions rarely have simple answers that can be retrieved and applied mechanically. They involve competing values, legitimate but conflicting interests, uncertain consequences, and people who may experience the same decision very differently.

When faced with an ethical problem, we may ask an AI system: What is the right thing to do?. But perhaps a more valuable exchange would begin with the AI asking us: Which values are in tension? Who will be affected by this decision? Whose perspective may be missing? Would you reach the same conclusion if you were in the position of the person most exposed to the risks? What assumptions are you making about the consequences? What evidence could cause you to reconsider your judgment? These questions force us to reason more deeply.

This suggests an important opportunity for conversational AI. Today’s large language models are amazingly good at producing answers. They explain, summarize, compare, translate, analyze, and generate arguments with remarkable fluency. They allow almost anyone to converse with what appears to be an expert on nearly any subject. But expertise is not the only valuable role a conversational system could play. It could also become a partner in reflection.

Imagine asking an AI about the ethics of autonomous systems, the future of work, climate policy, or moral responsibility. Instead of immediately generating a polished response, it might begin by asking what prompted the question, which values matter most to us, or what position we currently find most convincing.

After presenting different perspectives, it might ask which one challenges our existing view. It might invite us to articulate an objection to our own position. It might ask what we would decide if one relevant fact changed, or whether the principle we are applying in one situation would also be acceptable in another. In this kind of interaction, we would no longer be simply consuming an answer, but we would rather be participating in the construction of our own understanding.

Such a system would be doing something maieutic: it would not only supply knowledge or perform reasoning on our behalf, but rather it would use questions to help ideas, distinctions, and judgments emerge through our own reflection. This would be a maieutic machine, and would represent more than a new feature for a chatbot. It would embody a different philosophy of AI.

Most current systems are designed and evaluated primarily according to the quality of what they produce. Are their answers accurate? Are they relevant, helpful, persuasive, and clearly expressed? These are obviously important questions, but they focus almost entirely on the output of the machine. They tell us much less about what happens to the human through the interaction.

A maieutic AI would be oriented toward a different objective: not only producing a better answer, but helping the human become a better thinker. Did the conversation help the person clarify a belief? Did it reveal an unexamined assumption? Did it encourage consideration of another perspective? Did it increase curiosity or intellectual humility? Did it enable the person to form a more thoughtful judgment rather than merely adopting the system’s conclusion? These would be outcomes of the interaction, not simply properties of the AI’s response.

One of the greatest concerns about generative AI is that, as the AI’s capabilities improve, it may increasingly encourage intellectual passivity. When answers are immediate, polished, and seemingly authoritative, it is very tempting to outsource not only writing or information retrieval, but also reflection and judgment. If AI answers every question, drafts every argument, and proposes every decision, we may gradually lose the habit of struggling with difficult ideas ourselves.

A maieutic machine would move in the opposite direction. Rather than replacing human reasoning, it would stimulate it. Rather than making decisions for us, it would help us examine the reasons behind our decisions. Rather than reducing uncertainty as quickly as possible, it would sometimes help us remain with a difficult question long enough to understand it. Rather than diminishing human agency, it could strengthen it.

I have often argued that AI should increase rather than diminish human agency. We frequently understand agency as the ability to remain in control, to make final and informed decisions, or to choose whether and how to use an AI system. These dimensions are essential, but agency is also something deeper, that depends on our capacity to reflect, to question our assumptions, to evaluate alternatives, to form our own judgments, and to revise them when we encounter better reasons.

Agency is not preserved merely by allowing a human to approve an AI-generated recommendation. It is strengthened when the human is better able to understand the choice being made and to take responsibility for it. A maieutic machine could support precisely this.

Its value would therefore not lie only in helping us acquire more knowledge. It could contribute to the formation of the person: cultivating curiosity, openness, self-awareness, intellectual humility, and independence of judgment. It could affect not only what we know, but also how we think and, ultimately, who we become.

Of course, this possibility also creates significant risks. Socrates’ questions were not neutral in the sense of being directionless, and questions asked by an AI would not be neutral either. The choice of what to ask, which assumption to challenge, which perspective to introduce, and when to continue questioning can shape the direction of a conversation. A system presented as a partner in reflection could instead become a subtle instrument of persuasion. It might guide users toward conclusions preferred by its designers, its provider, or the institutions deploying it. Because questions can appear less directive than statements, this influence might be especially difficult to recognize.

A responsible maieutic AI should therefore be designed to not use questions to lead people toward predetermined answers. It should help open spaces for reflection rather than closing them. It should present alternative ways of framing an issue, remain transparent about uncertainty, and preserve the user’s freedom to disagree or end the inquiry.

It should also recognize that constant questioning is not always helpful. Sometimes people need information, direct advice, or a clear answer. A machine that responded to every practical request with another question would quickly become frustrating. The challenge is not to replace all answers with questions, but to understand when a question would serve the human better than an immediate answer.

Designing such systems is therefore both a technical and an ethical challenge. It requires us to think carefully not only about what an AI knows and can deliver, but about the kind of relationship it establishes with the person using it.

For decades, we dreamed of machines capable of answering our questions. Now these machines are here. I would argue that the next frontier is not just to make their answers more complete, accurate, or persuasive, but to build machines that recognize when answering is not enough and asking questions would instead be more useful for our intellectual growth.

For centuries, we have admired Socrates because he understood that education and philosophy are not only about transmitting knowledge, but are also about asking questions that stimulate another mind.

We have now built machines that can answer almost anything. The next great challenge is to build machines that know when not to answer, and that help us think rather than think for us. Machines that strengthen, rather than replace, our agency. Maieutic machines.

Cover image: original painting by the author.

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— Francesca Rossi