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“Everything is progressing so swiftly,” remarked Ian Bogost. “It’s advancing so rapidly that by the moment we pose the questions, there are new queries to consider.”

Bogost, a globally acknowledged authority and theorist in digital culture, holds the Barbara and David Thomas Distinguished Professorship at Washington University in St. Louis. Last spring, he directed a weekly, one-credit seminar titled “How AI Will Transform Your Profession.”

The structure was straightforward. Each week, the course — about 100 scholars from all nine WashU faculties — was joined by a distinguished authority in a particular sector, encompassing law and healthcare, consulting, publishing, biosecurity, and computer science.

“It resembled a live podcast,” joked Bogost, who also teaches film and media studies in Arts & Sciences and computer science and engineering at the McKelvey School of Engineering. “What insights are they gaining? How is AI shaping their field?

“How is it influencing their individual tasks?”

A distinct dialogue

The concept for the course emerged from conversations with the Arts & Sciences National Council. Will the careers for which WashU students are preparing still be available in a year? In five years? “That’s the question we aimed to explore. And hopefully to answer.”

Although public discussions surrounding AI can be rife with polarizable assertions, both optimistic and dystopian, Bogost sought to encourage a different dialogue. “It wasn’t merely about opposition or acceptance,” he stated. “The premise we operated on was: This is occurring. So what implications does that have for us?”

“Everyone contributed diverse reactions,” he continued. “’This is what we comprehend.’ ‘This is where potential advantages seem evident.’ Yet no one claimed, ‘This isn’t impacting us in the least.’”

Most participants joined remotely, although several discussions took place in person. With one significant exception (more on that later), dialogues were not recorded, permitting guests to express freely regarding delicate subjects.

Conversations frequently traversed various aspects. A leading trial lawyer guided scholars through a pivotal court case involving AI and copyright. But she also reflected on how AI tools and functionalities might affect legal firms. What tasks can AI accomplish? What could that signify for partners and associates? How might they approach their responsibilities differently?

“At times, the AI framework enabled the course to reveal matters that weren’t strictly about AI but had been continuous for an extensive period and now couldn’t be ignored,” Bogost remarked. For instance, a session on clinical medicine featured extensive discourse on electronic health records.

“As a medical student, you’re instructed to assist people, to heal individuals,” Bogost noted. “Yet, you will also engage significantly in bureaucratic duties. Can AI offer assistance in that? When it does, does it enhance your role, or merely generate more paperwork?”

Accessible yet discerning

Conversely, while recognizing that AI will modify numerous roles, few guests appeared to express concern that it would eventually replace human workers. AI tools are valuable not only because they might conserve some time or resources, most concurred, but also due to their qualitative distinctions.

In other words: AI should not enable employers merely to continue with the same traditional practices. It ought to facilitate entirely new approaches to work.

“In class, the inquiry of what constitutes appropriate or inappropriate utilization of AI was less significant than considering what it means to experiment with these tools?” Bogost mentioned. “What does it signify to conduct trials? What does it imply to be open yet also critical?”

The course’s final guest, who generously permitted his discussion with Bogost to be recorded and shared, was Andrew “Boz” Bosworth. As the chief technology officer at Meta, Boz provided distinct perspectives on how AI, specifically large language models (LLMs), is transforming computer engineering and software creation.

Boz observed that LLMs excel in specific tasks, such as test engineering — the process of reviewing code, identifying bugs, and documenting technical details. This is work that human programmers frequently find monotonous or troubling. “Interpreting another person’s code is almost as labor-intensive as composing your own,” Boz mentioned. “We struggle with that. LLMs excel in it.”

However, if one instructs an LLM to produce code from scratch, “you better be knowledgeable about what you’re doing … because it can fail in notably amusing ways.”

‘Consume the world’

“We’ve anticipated software to dominate and ‘consume the world’ for an extended period,” Boz continued. That has yet to occur. Specific tasks may transform, particular roles may emerge and diminish, but “throughout human history, we’ve never genuinely generated an innovation that increased efficiency (and) diminished employment.”

“These tools are going to be present,” Boz added. “They will be ubiquitous. So being exceptionally proficient with them is a prudent investment.”

Nonetheless, Bogost empathizes with those unsettled by the pace of change. “Sometimes events occur to you,” Bogost expressed. “You didn’t opt for them, but they happened nonetheless. Today’s undergraduates, their entire postsecondary experiences have been influenced by significant transformations that they did not select.

“I believe most of us struggle with precisely what role AI ought to fulfill,” he elaborated. This includes university professors developing AI curriculums. “I’ve received feedback from students that if it’s merely a gimmick — Here’s a class where you can utilize AI! — that’s not inspiring anyone’s enthusiasm.

“Yet we’re all navigating the same challenging moment,” Bogost concluded. “What functions does this peculiar new tool serve? What isn’t it capable of? How might we manage it?

“Let’s explore this collectively.”

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