[1] https://readscottalexander.com/posts/ssc-bottomless-pits-of-...

Disclaimer: I don't generally hold Silicon Valley rationalists in high regard, but this particular piece of writing has always stuck with me quite deeply, as someone who used to be superficially interested in utilitarianism.

  - a model is primarily judged by its predictive power

Most anti-science criticism I see is completely ignorant of what it really means to model a system or phenomenon: the challenges, the limitations, the end goal, the criteria for success, etc. It's sort of a statistical / scientific ignorance that's deeply cross-discipline. To perform science in a lot of ways is to engage with what it means to build a model, and in some ways, interrogate the universe.

If you're both an idiot and overconfident, it's tempting to throw your hands up and not engage with something as complex as "modeling", and just decide almost out of whimsy what the universe should truly be. But at least some people who find modeling too intellectually taxing at least admit that there are things that they'll never understand.

  - technologists : software that is bad for privacy
  - nutritionists : food and drink that gives you diabetes

No, I find that most teams I've been on have 5% to 20% of their most artisan engineers actually giving a shit about the code, and gently coaching the other 95% to 80% of the engineers who are usually much more junior during code review to not push unmaintainable slop. If you're on a team that doesn't still have someone giving a shit, it's not a sign that there are no teams that don't give a shit, it's that you're on a shit team.

There are also teams where the incentive is to get to pull request (or merge request) as soon as possible, so that you can move the ticket across the board and relieve downward pressure. That usually means pushing subpar code to PR that you know you'll spend another few hours fixing. EDIT: I bring this up because this can bias one's belief that humans produce poor quality code, when you're usually looking at the first draft that was incentivized to be pushed out "too early".

Anyway, if you're on a shit team, but you're still satisfying product and nothing is blowing up yet, there's a pretty good sign that your software has no moat and will be the first to be replaced by LLM-generated software on-demand. This is probably where most niche B2B back-office, front-office software sits. Stuff that sits somewhere in the realm of "We could probably do this in Excel if we wanted to."

But, “most consumers” don’t care about that. The beverage industry is insanely profitable, especially with recent forays into “energy drinks”.

Do people who drink so much dissolved sugar live without consequences? Absolutely not. They have a significantly lower quality of life and die much sooner than people who do not drink dissolved sugar.

I don’t see your comment as a valid dismissal. Just one more way that individual outcomes in our society are increasingly K-shaped.

Anyway, even if we froze training right now LLMs in their current state would have the ability to continue to provide tremendous utility. We’re not asking frontier model providers to delete their previous generations of LLMs (and harnesses), we’re trying to hold them accountable for the crimes they’re committing while training the next generation of LLMs (and harnesses).

This is probably an even more important principle in the age of LLMs.

This is why we need the humanities. I remember one of my application essays to my university was on the merits of a “Liberal Education”[1] and I’m very grateful that I was able to properly receive one from my institution.

[1] https://en.wikipedia.org/wiki/Liberal_education

“Socialize the costs, privatize the profits.”

I think it’ll just raise the automation bar that much higher. In other words, it will be good enough for 90% of yesterday’s use-cases. But tomorrow’s? I’m bearish.

I imagine the amount of onerous bureaucracy when interacting with any entity is going to explode if they expect you to do it in an automated fashion, for both private companies and the government. Especially as roles are cut because they can be “automated”. Except only 80% of the workload can be reliably automated, the other 20% requires a long tail of effort.

I would say our business and media cultures are most homogeneous. No matter where you are in the US, a business conference feels the same. A meeting with clients feels the same. The same toxic personalities rise to the top. I’ve never been surprised by a director or CEO.

No matter where you are in the US, you turn on the TV, and even if it’s local news, you get the same predictable messaging. We’re all obsessed with appearance and status, even within our subcultures and across the political spectrum. Superficiality.

But most people I know who don’t like Krugman are generally against monetary policy, as he’s one of the biggest mainstream proponents.