Machines possessing rationality? It might sound like something out of a science-fiction novel, but it’s the very question that MIT’s new course, 6.S044/24.S00 (AI and Rationality) is asking students to grapple with. The class ventures bravely into uncharted territories, immersing students in a complicated web of philosophical and computational theories. The intent? To provoke in-depth introspection about the nature of intelligence, autonomy, and decision-making pertaining to the world of artificial systems.
In this multi-layered debate, computer science and philosophy often appear to inhabit distant worlds. But Leslie Kaelbling, the Panasonic Professor of Computer Science and Engineering at MIT, acts as the bridge between these disciplines. Her personal journey has straddled both fields, right from her undergraduate philosophy classes at Stanford. Her exposure to the mechanical strands of philosophy and AI, throws light on early AI champions like Alan Turing whose footprint overlapped both spheres. To her, it’s the technical aspects of philosophy that mirror elements of AI.
Complementing her maverick philosophy is Brian Hedden, hailing from the Department of Linguistics and Philosophy and the Department of Electrical Engineering and Computer Science. As the course co-instructor, he echoes Kaelbling’s sentiments, accentuating the symbiotic nature of both fields, separated only by shades of emphasis and viewpoint.
Entering the academic arena as part of the Common Ground for Computing Education initiative, “AI and Rationality” has become a melting pot of diverse students from the fields of computer science, philosophy, cognitive science and beyond. But the course is not about spoon-feeding answers. As Hedden puts it succinctly, “We’re not giving them a body of doctrine to memorize, We’re giving them tools to think critically as they move forward in research, industry, or policy.” The objective is to equip students with the power of critical thinking.
Through exploring varied interpretations of rationality and how beliefs and desires might be pinned to artificial entities, students are nudged to question the core assumptions that anchor their fields. Kaelbling perceives philosophy as the lens that helps students think beyond the confines of their own discipline. “It’s important for students working in machine learning or robotics to step back and examine their assumptions”, Kaelbling explains.
For Amanda Paredes Rioboo, a senior in Electrical Engineering and Computer Science, this inter-disciplinary course represented a fresh take on conventional thought. She was roused to question whether humans, the machines, or the frameworks they rely on are irrational when they contradict math and logic which are widely held to be irrefutable truths. PhD student, Junior Okoroafor welcomed this multidisciplinary perspective, appreciating how the course spotlighted diverse disciplinary understandings of rationality.“Representing what each field means by rationality in a formal framework makes it clear which assumptions are shared and which differ,” he excitedly shares.
Given the rapid evolution within AI, it’s a tall order to predict what skills students might require in half a decade. Kaelbling, however, stresses on the importance of instilling flexible thinking habits. Inspiring students to critique, question and explore, the course “AI and Rationality” promises more than just academic insight. Instead, it arms the next generation of thinkers with the intellectual adaptability they need to sail through the ever-morphing landscape of artificial intelligence.
This website uses cookies.