Research

Philosophy and AI

In recent years, any number of universities have built bridges between computer science and ethics. Students whose future careers involve designing AIs, the thought is, should learn some basic ideas in ethics. Research done at the ValuesLab questions this widely held view. In a slogan, AI needs philosophy, not “only” ethics. Why? Ethics certainly has a role to play in the training of future AI designers. Many of the key questions, however, are studied elsewhere. Here are some examples. Can AIs think? Does it make sense to speak as if AIs held beliefs, make inferences, engage in reasoning, have intentions, and so on? The relevant notions here are studied in the philosophy of mind. What makes AIs explainable? Understanding, explanation, and justification are topics in epistemology. How do LLMs work, and how can their performance be improved? This involves any number of themes from the philosophy of language. What makes an AI model unfair? Here it matters how we conceive of causation and counterfactuals, key notions in metaphysics and the philosophy of science. The list goes on. The upshot is that core questions in major subfields of philosophy bear directly on challenges in AI. Instead of “embedded ethicists,” we argue, AI courses need embedded philosophers.

Explainable AI and Ancient Values

Contrary to modern moral philosophy, ancient Greek ethics argues that values related to knowledge and understanding—in Greek, epistêmê—are fundamental to human life. This project revives this conviction and argues that it speaks to key concerns in AI. AIs decide or help decide who gets an interview for a job, whose loan application is approved, what a patient’s medical diagnosis is and what their best treatment options are, and so forth. Much of the research in the ethics of AI is about the fairness of these decisions. We argue that research should also address epistemic values such as understanding and explainability. We aim to contribute to so-called explainable AI (XAI), which appreciates that it is a basic feature of the human mind to ask and expect answers to why-questions.

Alignment and Confucian Ethics

This project explores the resources of Confucian ethics for AI development, specifically with a view to value-alignment. It is widely assumed that ethics should inform AI design. Which ethics are we talking about? Researchers often invoke consequentialism, Kantian ethics, and Aristotle. Thus AI ethics seems to find itself squarely in the Western tradition. By contrast, we ask how Confucian philosophy may contribute to the development of AIs. Confucian ethics offers a framework that attends to (i) roles and relationships, (ii) constraints on what is sayable/doable for a polite person, and (iii) specified situations. For example, a son would not say such-and-such to a father at such-and-such an occasion. It is our hypothesis that this structure of ethical theory is helpful for AI ethics. For example, LLMs need to be trained on what not to say. Some of what counts as unsayable, offensive, and so on, is addressee- and context-dependent. We also consider AI models that are used in medicine, education, and so on. In these contexts, people speak as doctor to patients, as teacher to student, and so on. Presumably, AIs used in such domains should be informed by roles and relationships, conventions of the sayable/doable, and situations. In other words, Confucian ethics may provide a structure that can be modeled in AIs.