From the New York Times, May 17:
By Theo Baker
Mr. Baker is a college senior and the author of “How to Rule the World: An Education in Power at Stanford University.”
At Stanford University, where I am a senior, tech chief executives are something like rock stars. When the Nvidia founder Jensen Huang showed up to give a guest lecture late last month, students mobbed him. They offered up their laptops and personal workstations, desperate for a signature from a kingpin of the artificial intelligence era. Last year, speaking to the same class, Mr. Huang gave out shining $4,000 graphic cards with his name autographed in gold ink — the ultimate dorm room status symbol.
Stanford has always been a haven for aspiring techies, but recent events have taken the school into uncharted territory. A.I. is everything. We talk about it at the dining halls and in history classes, on dates and while smoking with friends, at the gym and in communal dorm bathrooms. Nearly all of higher education has been overtaken by this technology, and Stanford is a case study in how far it can go. For the past four years, my classmates and I have been the subjects of a high-stakes experiment.
We are the first college class of the A.I. era — ChatGPT arrived on campus about two months after we did. When we graduate next month, this technology will have altered our lives in very different ways. For some, it has opened the door to staggering wealth. But for many who came to Stanford — just four years ago! — when a degree seemed like a guaranteed ticket to a high-paying job, the door has been slammed shut. For all of us, A.I. has permanently changed how we think and behave.
Stanford already had a shaky reputation for integrity when I arrived in 2022. It was the origin place of the Theranos fraudster Elizabeth Holmes (now serving a 10-year prison sentence), the crypto fraudster Do Kwon (now serving a 15-year prison sentence) and the founders of Juul (which was forced to pay billions for getting kids hooked on vapes). All of these scandals were in the news when freshman year began. Many of my classmates arrived idealistic and hopeful, but among the strivers seeking a path to fortune, hustle culture was the accepted way of life. Now A.I. has made deception easier and more remunerative than ever before.
Cheating has become omnipresent. I don’t know a single person who hasn’t used A.I. to get through some assignment in college, yet the school was at first slow to realize how widespread this would become. As freshman year went on, some professors suggested that the “nuclear option” might be called for: allowing faculty to proctor in-person exams, a practice banned at the university for over a century to demonstrate “confidence in the honor” of students.
In our tech-enabled, newly A.I.-powered world, students were increasingly fudging just about everything. They would embezzle dorm funds to spend on their friends and lie about having Covid to get the UberEats credits that the school offered to those in quarantine. Some kids I knew published a paper that claimed a groundbreaking new A.I. advancement. Online sleuths quickly pointed out that it appeared to be just a stolen Chinese model, to which the two Stanford co-authors responded by blaming the plagiarism on the third author.
In junior year, 49 percent of the 849 computer science majors who responded to an annual campus survey said they would rather cheat on an exam than fail. A friend of mine captured the school’s ethos while we were discussing the tech hardware and other items our student club neglected to return to corporate sponsors. It was all, I recall her saying, “just a little bit of fraud.”
About halfway through freshman year, some coding classes started requiring students to sign a declaration — “I did not utilize ChatGPT” — to submit each assignment. During the first term these attestations began to appear, I watched a freshman I knew sign the declaration that he’d done his homework without A.I. as ChatGPT was still open in the next window — while on the deck of a yacht party financed by venture capitalists. The incentive structures were not aligned toward honesty. One could get ahead, quickly, by cutting corners, by focusing on self-presentation.
The money is a big part of it. A.I. has merely accelerated a trend that was already underway at Stanford and has been reflected by many of the country’s most corporatized universities: Education itself can be seen as a secondary goal to enabling future success, frequently defined as a future windfall.
The first time our college class gathered together was for a convocation ceremony in late September 2022. As one of the speakers droned on, I remember looking around and seeing a number of my classmates slumped over in the shade, dozing off. One of those kids is going to become a billionaire soon, it occurred to me. I wondered who it would be, and how.
At first the answer seemed to be cryptocurrency, and then it was A.I.
Most of my friends remember where they were and what they were doing when ChatGPT came out on Nov. 30, 2022. I was nearing the end of my time in Stanford’s infamous computer science “weeder” course, CS107. Like organic chemistry for pre-meds, this was the class that filtered out the true coders from those without the requisite hustle (with lots of shameless public tears involved).
The velocity of change that began on the day ChatGPT entered our lives was stunning. A friend texted me a link to the research preview of OpenAI’s latest demo: “Have you seen this yet? It’s INSANE.” We began kicking around silly prompts, reveling as ChatGPT explained the bubble-sort algorithm “in the style of a fast-talkin’ wise guy from a 1940s gangster movie.” It’s “very good. Very very good,” I messaged my friend. Still, neither of us understood that this would mark the transformation of A.I. from a technology to a product.
Students were probably the earliest wide-scale adopters. After all, it was far and away the quickest route to an A. When I took CS107, the only viable way for people to cheat was to seek out a student who’d gone through the class before and beg for solutions to the notoriously difficult problem sets. There was no alternative to putting in a large amount of work. Even if one did obtain the answers from another student (engaging, by the way, in a social act, if nothing else), the students I knew who did this still spent hours sculpting their stolen code so as not to be caught....
....MUCH MORE
As noted introducing September2023's "Fiduciary Investors Symposium at Stanford: Brain Research Is Opening investable Commercial Opportunities"
I don't know if it is going to work out as well as 2013's "Why Is Machine Learning (CS 229) The Most Popular Course At Stanford?"—which was followed by 2014's Deep Learning is VC Worthy—which was followed by 2015 to date "Saaaay, this Nvidia may be on to something."
But we shall see....
So it's a bit [!] surprising that the folks at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) didn't see this coming. They did however, point out in the 2023:
Stanford Uni. AI Index Report 2023: "Measuring trends in Artificial Intelligence"
...Industry races ahead of academia.
Until 2014, most significant machine learning models were released by academia. Since then, industry has taken over. In 2022, there were 32 significant industry-produced machine learning models compared to just three produced by academia. Building state-of-the-art AI systems increasingly requires large amounts of data, compute, and money, resources that industry actors inherently possess in greater amounts compared to nonprofits and academia.
And although not related to the opinion piece, if one is so inclined we have on offer:
Stanford University's 2026 AI Index Report
