logravia

That's a very weird framework and dichotomy you have there. Try untangling yourself out of it by considering some empirical facts, for example, hospitals acquired by private equity often have worse outcomes.

> private equity acquisition was associated with a 25.4% increase in hospital-acquired conditions, which was driven by falls and central line–associated bloodstream infections

https://pmc.ncbi.nlm.nih.gov/articles/PMC10751598/

> Medicare beneficiaries in the emergency departments of private equity hospitals experienced seven additional deaths per 10,000 visits after acquisition relative to hospitals that were not acquired by private equity, the team found. This rise represented a 13 percent increase from a baseline of 52 deaths per 10,000 visits

https://hms.harvard.edu/news/deaths-rose-emergency-rooms-aft...

The more interesting question is why would you at any point ever extend any goodwill to an unbounded corporate entity?

Whenever you are faced with a corpo you should conceptualize it as a system that will happily mow you over for increased profits, unless it is legally bound to not prioritize profits above everything else and its structural incentives push it in a pro-social direction.

False positives are the primary issue. False positives lead to stress, invasive diagnostic procedures and wasted medical resources. Look into the debate about what is the appropriate age for mammographies and how Apple Watches have resulted in overdiagnosis of heart conditions.

For data to be useful we need rigorous medical science. We have shitton of worthless medical data with little science behind it.

Oh yeah, a month ago I was reading a comment section about LLM writing tendencies and someone humorously suggested using the loooooooong-em-dash to distinguish yourself from LLMs. I found it so charming that I made my keyboard output it when I double tap "-".

On Linux you press Ctrl+Shifs+U and then type 2E3B, then press enter.

The thing I am struggling with is where is the impact of LLM tools, especially given the massive increase in token consumption from 2025 to now and the saturated presence of LLMs everywhere.

Naively speaking, I have so many expectations for the impact of this tech.

I'd expect a noticeable uptick in applications published on Google, Apple and Microsoft app stores. I'd also expect an uptick of games published to Steam. I'd expect an uptick in Github repos and libraries on PyPi.

I'd also expect some impact on the GDP ⸻ a non-negligible part of running a business is communication, planning, ads. Naively, I'd expect that LLMs should be able to both speed some of these things up and lubricate others.

I'd also expect that large corpos like Microsoft and Apple would have more resources to spare on the essential details of their OS like having a functioning taskbar or a predictable, consistent GUI.

I'd expect increased SAT scores or improved PISA results. Maybe even improved mental health, let's go wild.

It's strikes me as a reasonably useful tool, personally.

Yet, where are the goods in the aggregate?

Sure, it covers 99.9% of cases, but top elite athletes are the genetic exceptions, they are the genetic freaks. They are the top 0.0001%. You don't get to compete at the most elite levels without your body being exceptionally gifted and almost specifically shaped for the relevant sport, which inevitably means funky genetic traits and disorders, higher testosterone levels etc.

I mean the word freak in the most loving and caring way possible, mind you.

What does fairness mean in that context?

It certainly is. For people who have not heard the statements, here are some quotes. I bring them up, because I think it's worthwhile to remember the bold predictions that are made now and how they will pan out in the future.

Council on Foreign Relations, 11 months ago: "In 12 months, we may be in a world where AI is essentially writing all of the code."

Axios interview, 8 months ago: "[...] AI could soon eliminate 50% of entry-level office jobs."

The Adolescence of Technology (essay), 1 month ago: "If the exponential continues—which is not certain, but now has a decade-long track record supporting it—then it cannot possibly be more than a few years before AI is better than humans at essentially everything."