Episode 5: Aren't the generalists afraid of AI?

An open letter to the career strategies of my classmates

Last semester, I once had a small-group lunch with Dean Erika James of the Wharton school and asked her what were some of the big changes on the horizon that the school needed to adapt to, especially to retain the status of an elite business school. Implicitly, I was also searching for the answer for what she believes the value of a business education would be. I've mentioned before that I applied to school for the academic reasons primarily, but it was interesting to hear her reflections from the other side of the admissions process. I applied to Wharton with the belief that there had to be a way to learn entrepreneurial skills ground up without having to "move fast and break things", and that there should be an implicit way to break the stupid hype culture of Tech VC.

Dean James said that there were four big priorities that the school was adjusting to: The use of AI, restoring faith in democracy and democratic processes, training future business leaders for entrepreneurship, and protecting free speech on campuses. Almost all of these have turned out to have pivotal epochs in the last few months, and that's not even accounting for the fact that we experienced a global pandemic that enforced months of isolation four years ago. Wharton, and the broader University of Pennsylvania, is trying its best to adapt to AI-focused programs and research. I probably should be more knowledgeable about this as I come from years of AI research, and then cloud ML deployments.

However, this is not meant to be a brochure for the school. And this is also not meant to be a sweeping endorsement for all technology and tools powered on AI. I come from deep tech skepticism because I've engaged with the research literature as part of my job and have had to build models by hand. I come from the bastion of former engineers which doesn't believe that you should be in any managerial role in tech unless you've gotten hands-on experience working in that industry. But that's not an opinion my classmates share.

Everyone wants to pivot from banking/consulting to tech because they want to make lots of money while also having the illusion of a work-life balance. And I won't deny it, working at Google did have its perks in terms of nap rooms and free meals. But we also pulled overnight shifts at the office that required us to be able those nap rooms. Those transitioning to tech at this time, with no coding experience, no engagement with any work that is happening on the ground, are operating in a similar basis as Tech VC Twitter: hype and vibes. I am a part of at least four group chats at Wharton that try to be a foundry for AI sources and news, and not one of them actually credits genuine scientific research or even industry-specific news coverage (like The Information). At Wharton we have tests every quarter and at the end of every semester. Unfortunately my tolerance for nonsense is tested severely at least once every 72 hours.

The counterargument that I hear is that good managers are not required to be good engineers or researchers. I cannot tell if this is an actual counterargument or simply consulting propaganda. The idea that managers are generalists, they should be able to bring frameworks that apply across industries to every organizations, is so reductionist to me. And this reductionist view is particularly harmful in tech or in new/emerging frontiers. We do not yet know what the AI industry is going to look like, and all we know is that previous models may not hold up as well as we believe. And AI is just one small part of the new entrepreneurial futures that are to come: genetics research and engineering, space exploration booms or even the blockchain (yet).

Also, would you really pay $250K to be able to know that you can pivot from a stagnating middle management class in one kind of job to another?

In this, I keep coming back to why the generalists choose to be this way. Especially because the hype culture chatter about AI is also that generalist jobs will be replaced. Bain and McKinsey are already training an in-house instance of ChatGPT, which will presumably supplant years of expertise with generic automated frameworks. So, the terrain looks like this: people aren't at business school to get hands-on experience in the industry of their choice. People aren't at business school to take intellectually challenging courses with hard/transferable skills (like maybe taking at least one coding class or so). Then what kind of jobs do they expect to be placed in this economy? How are they operating under the delusion that these openings exist?

There are worse ways to feed into the tech hype culture, and that is through Venture Capital and Private Equity. Somehow people who have, at best a tentative idea, of how your product or industry works should be given the opportunity to spend ungodly amounts of money on it. That's how some of the most flimsy projects get ungodly quantities of funding: Tinder for dogs powered by AI? 5 billion, and just for using "AI" in the description.

It's also annoying to me that the AI that everyone speaks of now is some variant of an LLM or some wrapper over ChatGPT. Now that OpenAI has somehow built this model that everyone can use and understand, all conception of computational limits of this technology have boiled to this basic model. The frontier and research of Machine Learning has, and I cannot overstate this, enormous potential still. Many of which I genuinely believe have the ability to solve for big problems in our time – targeted medicine for pediatric care, automated driving for public transportation and safety, better mapping and comprehension of oceans, etc.

Tech culture also this stupid individualism that I was hoping the environment of business school would challenge. Entrepreneurship communities overall tend to imagine themselves as the next Elon Musk or Steve Jobs or some figure who happened to occupy the space of history, opportunity and skill at the right place and time. Dean Erika James also said that Wharton was positioning itself to an increasing interest in entrepreneurship from incoming applicants. The school wants to cultivate, if not become this environment, and it is competing against actual tech foundries like Y Combinator to serve as a better hotbed of opportunities. If the whole point of business school is the network, then why do I have to fight so hard to find those with the same intellectual hunger? Why am I the minority in searching for this?

One of the ways in which I satisfy my intellectual starvation at Wharton is by taking hard classes within the school, and also taking classes within the broader University of Pennsylvania. I am taking a 3D printing class to understand something about how materials are manufactured, even though I intend to work entirely in digital realms. This class is cross-listed under the Wharton Operations department, and the Entrepreneurship center, and permits students to run up to 25 jobs on a wide array of nearly $600 3D printing machines for free. Yet only 4 people within my general sphere of Wharton know of this class, and one of them is already graduating. I know I cannot be the only one, but it is hard to feel like there's genuine intellectual curiosity in an environment where everyone is looking for a quick-and-dirty framework to fix everything.