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Culture War Roundup for the week of April 8, 2024

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Paging @2rafa or anyone else who can explain to me what an investment banking analyst actually does: AI is coming for Wall Street: Banks are reportedly weighing cutting analyst hiring by two-thirds (paywalled for me on desktop but it's loading fine on mobile):

Incoming junior Wall Street analysts could be in danger of losing their jobs to AI, sources within banks told the New York Times.

Big firms are reportedly mulling whether to pull back on hiring new analysts as Wall Street leans more heavily on AI, several people familiar with the matter at Goldman Sachs, Morgan Stanley, and other banks told the publication this week.

Incoming classes of junior investment-banking analysts could up being cut as much as two-thirds, some of the people suggested, while those brought on board could fetch lower salaries, on account of their work being assisted by artificial intelligence.

I don't know how to evaluate the claims in the article because I have little understanding of what a banking analyst actually does on a day to day basis. How much of it requires "thought" (not thought of incredible complexity and originality, but thought nonetheless) and how much of it is just plugging numbers into Excel in a relatively formulaic fashion?

In general I lean towards being skeptical of these claims, especially in domains where I have little expertise, because the dominant pattern of the last 2 years is that people who don't know much about X tend to overestimate how good AI is at X.

If I compare this to a domain where I do have some knowledge (computer programming), most of the tests that people use to demonstrate LLMs' coding ability aren't particularly representative of what programmers do on a daily basis. Sitting down and opening a new blank file and "writing code to do X" is certainly part of the job, and it can be a bigger or smaller part of the job depending on what type of organization you're at and what type of project you're working on etc, but it's not the whole job (for some programmers, it's a very small part of it!)

So I'd like people with more domain knowledge to weigh in on what aspects of these financial jobs are liable to be automated today and what the forecast for the field is like.

IB analyst/associate is a fake job to give 22 year olds a few years to learn some basic professionalism and finance skills. After a few years of polishing they move on to a somewhat more real job (real in the sense that they’re doing something with real-world consequences, not necessarily socially useful) like PE or more senior banker.

Banks provide this training for various reasons discussed downthread but it’s not surprising that as revenue decreases they start cutting back. They don’t want to announce to clients that they’ve been charging them to train Harvard grads with fancy finance jobs for even fancier finance jobs all this time, so instead they pretend it’s about AI. I am skeptical that LLMs are actually good at doing what junior bankers do, rather, what junior bankers do is close to pointless.

So I'd like people with more domain knowledge to weigh in on what aspects of these financial jobs are liable to be automated today and what the forecast for the field is like.

The classic IB/PE role/career track will definitely survive. I don’t think AI/LLM is very relevant to what a more senior person does. Junior roles are cyclical (related to the state of the economy, not AI developments). Back-office or support-type roles like IT will probably be most impacted for the same reason that these kinds of roles will be impacted economy-wide.

So it's an apprenticeship, and I think the problem will be that if you cut out the juniors and replace them by AI, where are the new seniors going to come from when the current lot retire/move on/die?

You haven't trained up the next generation of successors and if everyone has done the same thing by replacing the lower ranks with AI, you can't hire them on from elsewhere, either.

I think you're misunderstanding the process of AI development.

  • Capabilities are encapsulated within tool use.
  • AI retrained on this tool use now use it 'intuitively'.
  • Instead of breaking down tasks into low level skills, AI gain the ability to break them down into high level skills.
  • This makes high level skills that were previously too complex to learn into tasks that are no longer to complex to learn.
  • These new capabilities are encapsulated within tool use.

We've been focusing so hard on communicating to people that AI aren't human, that we've been glossing over how anthropomorphic this process actually is. Once the AI have fully internalized the low level skills that we teach to entry level human analysts, the same process that allows some of those low level human analysts grow into senior analysts, make the jobs of more senior analysts learnable to AI.

LLMs are probably very good at doing what junior bankers do, since what they do is essentially running basic statistics on publicly available financial data (already categorized by the big financial data providers) and then adding some light commentary, charts and visuals for pitches. I remember using FactSet’s primitive auto pitchbook feature in 2014 or 2015 and thinking that this was a job that was going to be automated very soon. But you’re correct that that isn’t really the point.