--- title: What Socrates Can Teach Us About the Folly of AI description: The lesson from the philosopher on the folly of large language models canonical: https://time.com/6299631/what-socrates-can-teach-us-about-ai/ author: Carissa Véliz article:opinion: true article:content_tier: free article:published_time: 2023-08-01T11:00:00.000Z article:modified_time: 2026-08-04T07:45:40.318Z article:section: Ideas og:title: What Socrates Can Teach Us About the Folly of AI og:description: What Socrates Can Teach Us About the Folly of AI og:url: https://time.com/6299631/what-socrates-can-teach-us-about-ai/ og:site_name: TIME og:image: https://static.time.com/v3/assets/bltea6093859af6183b/bltbf7bf621a1ba85a6/698a3f1ed075332d28e6e3f6/socrates-artificial-intelligence.jpg?branch=production&width=1200&quality=75&auto=webp&crop=16:9 og:image:width: 2400 og:image:height: 1350 og:image:alt: socrates-artificial-intelligence og:type: article twitter:card: summary_large_image twitter:title: What Socrates Can Teach Us About the Folly of AI twitter:description: What Socrates Can Teach Us About the Folly of AI twitter:image: https://static.time.com/v3/assets/bltea6093859af6183b/bltbf7bf621a1ba85a6/698a3f1ed075332d28e6e3f6/socrates-artificial-intelligence.jpg?branch=production&width=1200&quality=75&auto=webp&crop=16:9 --- # What Socrates Can Teach Us About AI > Sponsored content. 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Find out why OpenAI was selected for the list_ Aug 1, 2023 11:00 AM UTC  Statues of Greek philosophers Socrates, center, and Plato, sit outside the Academy of Athens, on Feb. 21, 2015. Statues of Greek philosophers Socrates, center, and Plato, sit outside the Academy of Athens, on Feb. 21, 2015. Yorgos Karahalis—Bloomberg/Getty Images by [Carissa Véliz](https://time.com/author/carissa-veliz/) ## Carissa Véliz Aug 1, 2023 11:00 AM UTC If Socrates was the wisest person in Ancient Greece, then large language models must be the most foolish systems in the modern world. In his _Apology_, Plato tells the story of how Socrates’s friend Chaerephon goes to visit the oracle at Delphi. Chaerephon asks the oracle whether there is anyone wiser than Socrates. The priestess responds that there isn't: Socrates is the wisest of them all. At first, Socrates seems puzzled. How could he be the wisest, when there were so many other people who were well known for their knowledge and wisdom, and yet Socrates claims that he lacks both? He makes it his mission to solve the mystery. He goes around interrogating a series of politicians, poets, and artisans (as philosophers do). And what does he find? Socrates' investigation reveals that those who claim to have knowledge either do not really know what they think they know, or else know far less than they proclaim to know. ### More From TIME Socrates is the wisest, then, because he is aware of the limits of his own knowledge. He doesn't think he knows more than he does, and he doesn't claim to know more than he does. How does that compare with large language models like [ChatGPT4](https://time.com/6271657/a-to-z-of-artificial-intelligence/)? In contrast to Socrates, large language models don't know what they don’t know. These systems are not built to be truth-tracking. They are not based on empirical evidence or logic. They make statistical guesses that are very often wrong. **_Read More:_** [**_How AI Could Help Free Human Creativity_** ](https://time.com/6289278/ai-affect-human-creativity/) Large language models don't inform users that they are making statistical guesses. They present incorrect guesses with the same confidence as they present facts. Whatever you ask, they will come up with a convincing response, and it's never “I don’t know,” even though it should be. If you ask ChatGPT about current events, it will remind you that it only has access to information up to September 2021 and it can’t browse the internet. For almost any other kind of question, it will venture a response that will often mix facts with confabulations. The philosopher[ Harry Frankfurt](https://www.nytimes.com/2023/07/17/books/harry-g-frankfurt-dead.html) famously argued that bullshit is speech that is typically persuasive but is detached from a concern with the truth. Large language models are the ultimate bullshitters because they are designed to be plausible (and therefore convincing) with no regard for the truth. Bullshit doesn’t need to be false. Sometimes bullshitters describe things as they are, but if they are not aiming for the truth, what they say is still bullshit. And bullshit is dangerous, warned Frankfurt. Bullshit is a greater threat to the truth than lies. The person who lies thinks she knows what the truth is, and is therefore concerned with the truth. She can be challenged and held accountable; her agenda can be inferred. The truth-teller and the liar play on opposite sides of the same game, as Frankfurt puts it. The bullshitter pays no attention to the game. Truth doesn’t even get confronted; it gets ignored; it becomes irrelevant. Bullshit is more dangerous the more persuasive it is, and large language models are persuasive by design on two counts. First, they have analysed enormous amounts of text, which allows them to make a statistical guess as to what is a likely appropriate response to the prompt given. In other words, it mimics the patterns that it has picked up in the texts it has gone through. Second, these systems are refined through a process of reinforcement learning from human feedback (RLHF). The reward model has been trained directly from human feedback. Humans taught it what kinds of responses they prefer. Through numerous iterations, the system learns how to satisfy human beings’ preferences, thereby becoming more and more persuasive. As the proliferation of fake news has taught us, human beings don’t always prefer truth. Falsity is often much more attractive than bland truths. We like good, exciting stories much more than we like truth. Large language models are analogous to a nightmare student, professor, or journalist; those who, instead of acknowledging the limits of their knowledge, try to wing it by bullshitting you. Plato’s _Apology_ suggests that we should build AI to be more like Socrates and less like bullshitters. We shouldn’t expect tech companies to design ethically out of their own good will. Silicon Valley is well known for its bullshitting abilities, and companies can even feel compelled to bullshit to stay competitive in that environment. That companies working in a corporate bullshitting environment create bullshitting products should hardly be surprising. One of the things that the past two decades have taught us is that tech needs as much regulation as any other industry, and no industry can regulate itself. We regulate food, drugs, telecommunications, finance, transport; why wouldn’t tech be next? Plato leaves us with a final warning. One of the lessons of his work is to beware the flaws of democracy. Athenian democracy killed Socrates. It condemned its most committed citizen, its most valuable teacher, while it allowed sophists —the bullshitters of that time—to thrive. Our democracies seem likewise vulnerable to bullshitters. In the recent past, we have made them prime ministers and presidents. And now we are fuelling the power of large language models, considering using them in all walks of life—even in contexts like journalism, politics, and [medicine](https://time.com/6274752/ai-health-care/), in which truth is vital to the health of our institutions. Is that wise? ## Transcript In a deep sense as the technology that the world society people have always wanted. So I can talk about this for a very long time. I think we can do a lot to really maximize to go to manage and mitigate the bad. But the scary part is just sort of putting this lever into the world will for sure have unpredictable consequences. Can't we think it's very important to our mission to deploy things like Chachi PT. So that people gain some experience of feeling of the capabilities and limitations of these systems. But as these models get to know you better and are able capable of more, you can really imagine a world where you have a fairly simple and short conversation with the model and a huge amount of things get on your behalf, pretty soon. I think we'll just expect all the products and services. We used to have some intelligence baked in, and it'll just kind of be expected like a mobile app is today. I think if this technology goes wrong, it can go quite wrong, and we want to be vocal about that. We want to work with the government to it, is our responsibility to educate policymakers and the public at large about what we think is happening. What we think may happen. Like we have in the future and to put technology out into the world so people can see it. liberation of deepening of societal inequalities. We have seen how algorithmic biases can perpetuate discrimination and Prejudice and how the lack of transparency can undermine public trust that voice was not mine. The words were not mine. And the audio was an AI voice cloning software trained on my floor speeches. The remarks were written by Kat gbt when it was asked how I would open this hearing with. So grown up in a world where we sort of trust someone's voice. We hear over the phone. This particular example, I think is going to be a problem and we need Society to adjust to it fast. So I think we just all need to start telling people. This is coming, you can't trust a voice to hear of the phone anymore in society is capable of adapting to his people are much smarter and savvier than I think a lot of the so-called experts Think. These systems are already quite powerful and will get tremendously powerful and we have come together as a global Community before 4 very powerful technologies, that pose a substantial risk, that one have to overcome to get to the tremendous upside. I think AI will contribute a lot to increase in the total amount of wealth in the world. However, it won't be sufficient on its own. And I still think we need much more public policy around. How we're going to divvy up access to these systems. How we're going to divvy up governance of these systems? That will be a matter for policy. Not the technology along with the effect that I have are going to be very different in the world than the effects that social media. And so I think it is difficult and dangerous to say, oh, it's going to play out like this. And I think of this like social media were going to think of this like nuclear weapons are not think of this like synthetic biology were think of this like, the iPhone. This is just a new thing and I think analogies from the past are going to particularly badly. 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