To what extent can a man-made system be rational?
A brand new MIT course, 6.S044/24.S00 (AI and Rationality), doesn’t seek to reply this query. As an alternative, it challenges students to explore this and other philosophical problems through the lens of AI research. For the subsequent generation of students, concepts of rationality and agency could prove integral in AI decision-making, especially when influenced by how humans understand their very own cognitive limits and their constrained, subjective views of what’s or isn’t rational.
This inquiry is rooted in a deep relationship between computer science and philosophy, which have long collaborated in formalizing what it’s to form rational beliefs, learn from experience, and make rational decisions in pursuit of 1’s goals.
“You’d imagine computer science and philosophy are pretty far apart, but they’ve all the time intersected. The technical parts of philosophy really overlap with AI, especially early AI,” says course instructor Leslie Kaelbling, the Panasonic Professor of Computer Science and Engineering at MIT, calling to mind Alan Turing, who was each a pc scientist and a philosopher. Kaelbling herself holds an undergraduate degree in philosophy from Stanford University, noting that computer science wasn’t available as a serious on the time.
Brian Hedden, a professor within the Department of Linguistics and Philosophy, holding an MIT Schwarzman College of Computing shared position with the Department of Electrical Engineering and Computer Science (EECS), who teaches the category with Kaelbling, notes that the 2 disciplines are more aligned than people may think, adding that the “differences are in emphasis and perspective.”
Tools for further theoretical thinking
Offered for the primary time in fall 2025, Kaelbling and Hedden created AI and Rationality as a part of the Common Ground for Computing Education, a cross-cutting initiative of the MIT Schwarzman College of Computing that brings multiple departments together to develop and teach recent courses and launch recent programs that mix computing with other disciplines.
With over two dozen students registered, AI and Rationality is certainly one of two Common Ground classes with a foundation in philosophy, the opposite being 6.C40/24.C40 (Ethics of Computing).
While Ethics of Computing explores concerns in regards to the societal impacts of rapidly advancing technology, AI and Rationality examines the disputed definition of rationality by considering several components: the character of rational agency, the concept of a totally autonomous and intelligent agent, and the ascription of beliefs and desires onto these systems.
Because AI is incredibly broad in its implementation and every use case raises different issues, Kaelbling and Hedden brainstormed topics that might provide fruitful discussion and engagement between the 2 perspectives of computer science and philosophy.
“It is important once I work with students studying machine learning or robotics that they step back a bit and examine the assumptions they’re making,” Kaelbling says. “Desirous about things from a philosophical perspective helps people back up and understand higher methods to situate their work in actual context.”
Each instructors stress that this isn’t a course that gives concrete answers to questions on what it means to engineer a rational agent.
Hedden says, “I see the course as constructing their foundations. We’re not giving them a body of doctrine to learn and memorize after which apply. We’re equipping them with tools to take into consideration things in a critical way as they exit into their chosen careers, whether or not they’re in research or industry or government.”
The rapid progress of AI also presents a brand new set of challenges in academia. Predicting what students may have to know five years from now’s something Kaelbling sees as an not possible task. “What we’d like to do is give them the tools at the next level — the habits of mind, the ways of pondering — that can help them approach the stuff that we actually can’t anticipate without delay,” she says.
Mixing disciplines and questioning assumptions
Up to now, the category has drawn students from a big selection of disciplines — from those firmly grounded in computing to others fascinated with exploring how AI intersects with their very own fields of study.
Throughout the semester’s reading and discussions, students grappled with different definitions of rationality and the way they pushed back against assumptions of their fields.
On what surprised her in regards to the course, Amanda Paredes Rioboo, a senior in EECS, says, “We’re type of taught that math and logic are this golden standard or truth. This class showed us a wide range of examples that humans act inconsistently with these mathematical and logical frameworks. We opened up this whole can of worms as as to whether, is it humans which are irrational? Is it the machine learning systems that we designed which are irrational? Is it math and logic itself?”
Junior Okoroafor, a PhD student within the Department of Brain and Cognitive Sciences, was appreciative of the category’s challenges and the ways by which the definition of a rational agent could change depending on the discipline. “Representing what each field means by rationality in a proper framework, makes it clear exactly which assumptions are to be shared, and which were different, across fields.”
The co-teaching, collaborative structure of the course, as with all Common Ground endeavors, gave students and the instructors opportunities to listen to different perspectives in real-time.
For Paredes Rioboo, that is her third Common Ground course. She says, “I actually just like the interdisciplinary aspect. They’ve all the time felt like a pleasant mixture of theoretical and applied from the indisputable fact that they should cut across fields.”
In accordance with Okoroafor, Kaelbling and Hedden demonstrated an obvious synergy between fields, saying that it felt as in the event that they were engaging and learning together with the category. How computer science and philosophy could be used to tell one another allowed him to grasp their commonality and invaluable perspectives on intersecting issues.
He adds, “philosophy also has a way of unusual you.”
