From Aristotle to ChatGPT, Brown programs interrogate AI by means of a humanist lens

PROVIDENCE, R.I. [Brown University] — Public discourse round synthetic intelligence tends to focus totally on technical or financial issues. How succesful will AI turn into? And to what extent may it take away jobs?

While these questions are of apparent significance, different maybe extra elementary ones are effervescent beneath the floor. What does it imply for a machine to be clever? What does generative AI imply for human creativity? Can AI-generated textual content be thought-about literature — and even language?

Those are among the many questions that college students and school explored this spring by means of two Brown University programs provided by means of the Cogut Institute for the Humanities. The programs, The History of AI and Reading the Large Language Models, aimed to provide college students an opportunity to know and critique advances in AI, whereas difficult them to ponder how these applied sciences relate to humanity writ giant. Both have been team-taught by a professor from a humanities self-discipline and one from pc science. The thought was to mix a deep technical understanding of recent AI programs with wealthy cultural context and criticism.

“AI is absolutely everywhere,” stated Ellie Pavlick, an affiliate professor of pc science and linguistics who co-taught the big language fashions (LLMs) course. “And it’s this non-human thing trying to co-opt human bits of experience, like language. So we need people equipped to think about it and critique it, and they can’t only be computer scientists. We need a variety of perspectives.”

Reading the Large Language Models was a seminar-style course that explored the emergence of human-like textual content generated by programs like ChatGPT, and what meaning for language, literature and tradition. John Cayley, a professor of literary arts who co-taught the category with Pavlick, acknowledged an inherent pressure between the humanist understanding of language and the rising skills of LLMs. 

“Thinking and language are not generally understood by most of the people working in the artistic and humanist fields as being computable,” Cayley stated. “If they’re right, that means what is computed as language or as text is not actually language. It’s something else that we have to incorporate into what we, as human beings, actually do consider to be language.”

Classwork blended humanist and cultural critique with technical readings and a few experimentation with various kinds of language fashions. The pupil composition of the category — eight college students from humanities fields and eight with largely computational backgrounds — made for energetic dialogue and alternate of concepts, says Laura Romig, a Class of 2025 graduate who took the course throughout her closing undergraduate semester. As a double concentrator in comparative literature and utilized math, she had a foot in each camps. She stated that whereas the views of the 2 sides have been completely different, there was broad settlement that each have been vital.

“Both sides came to more of an understanding of the other side’s field and methods of practice,” Romig stated. “There was definitely a sense that each perspective was important to the other’s field.”

Romig stated she started the category deeply skeptical about using AI to both create or analyze literature, and that skepticism remained afterward. But she stated she got here away with a renewed perception within the energy of (human-created) fiction to make clear the world. As a closing undertaking for the category, she and a accomplice wrote a brief story a few world through which individuals have ceded their decision-making to AI fashions. 

“We wanted to write a work of fiction that showed several aspects of how AI and large language models are affecting the world,” she stated. “We came to the conclusion — and this is something that I sort of already believed — that fiction is very powerful for representing the world, changing how people feel about it and showing problems that exist.”

Discourse throughout disciplines

The History of AI, a lecture-style course with greater than 40 college students, aimed to offer historic context to what looks as if the sudden emergence of generative AI. Course readings spanned Aristotelian philosophy by means of the early computing work of Ada Lovelace to trendy concepts of augmented intelligence and technological singularity. Historical works have been mixed with fiction by the likes of Karel Čapek, whose work launched the time period robotic into the cultural discourse. Readings for every week have been organized round themes reminiscent of language, intelligence, prediction and embodiment.

The course additionally included non-Western views on AI growth, that includes a lecture by Kate Creasey, a Ph.D. pupil in historical past and educating assistant for the course. Her presentation, titled “AI and Data Sovereignty in the Global South,” spawned an outside-class studying group on the subject and a weblog submit co-authored by Creasey on the nonprofit information outlet Tech Policy Press. 

“Knowing the history of AI invariably changes the way one sees and engages with it,” stated Holly Case, a professor of historical past and humanities who co-taught the course. “In a world where technology often — intentionally or unintentionally — limits a person’s capacity to think rigorously about the ‘invisible’ artificial systems that saturate our lives, the course aims to develop and expand that capacity.”

Suresh Venkatasubramanian, a professor of pc science who co-taught the course with Case, agreed that it’s vital to know trendy AI programs in a bigger historic context. 

“When we talk about whether LLMs can understand language, and what that means for their ‘humanness,’ we should also be understanding how language — the very idea of who is allowed to speak, and what speaking says about thinking — has evolved over the centuries,” Venkatasubramanian stated. 

While the goal of the programs was to not reply each query surrounding AI over the course of a single semester, college and college students agreed that beginning a discourse throughout humanist and technical disciplines is vital to working towards these solutions. 

“I love seeing students engage with AI from a non-technical perspective, and to see technical students confront arguments about AI that aren’t empirical ones,” Pavlick stated. “It serves as a valuable reminder that complicated problems require complicated solutions.”