Yea, that's his point. The gold standard neither prevents nor encourages inequality, except inasmuch as it limits policy flexibility (which, similarly, could be used to promote or limit inequality).
NAL, but have worked in this. Griggs is a bit more complicated than that, and its progeny modify application anyway.
The TLDR is that arbitrary tests are permissible if there's no disparate impact. Tests with disparate impact are permissible iff they are not arbitrary (i.e., "directly" assess job responsibilities).
So, for example, Leetcode may have disparate impact, but it's "direct" enough to be permissible. On the other hand, most "AI Assessments" are actually so badly implemented that they're effectively random - and a coin flip won't have disparate impact.
How long would it take an aggressive company to expand production capacity? I always thought it takes a few years, at minimum, for even established players to stand up new fabs
The industry is so naturally prone to oversupply that the only stable equilibrium is undersupply. Aggressive expansion kicks off a price war, which immediately undercuts the logic of the expansion.
This only changes with new entrants, which will come, especially from China. But it takes time to build fab capacity, so the medium-term modal outcome is consistent undersupply.
The credential was certainly something - a more easily understood distillation of the of connections and status that got you there. But that's not exactly professional the way a degree in Business is.
Besides, were there not other high-minded notions that underpinned that credential - ideas of self-development and virtuous leadership? And more crass notions of polish and status? Were these not the self-justifications of these elites, made manifest through the institutions?
As a side note - I do strongly suspect elite schools will bring these ideas back. If not for virtue, for necessity - as schools seek to self-justify in ways that go beyond the dollars they risk losing.
Maybe - to your point, if we think of happiness as like “living one’s own purpose fully”, then yes, it does very directly.
But I was referring to happiness more generally as enjoyment, joy, satisfaction - that type of thing.
And in that case - there are plenty of ways being better = less happy. Eg if I were to sacrifice myself to save my family, then that’s the best version of me, but I’d be pretty dang unhappy about it.
UChicago should be pretty uniquely positioned to address the problem of AI writ large. They already require a full year of each philosophy, literature, and history (all through primary sources). This "Core" should already be fairly AI-proof, given they are primarily small-group, discussion-driven courses; oral exams, in-class essays, or even graded discussions should be straightforward adaptations.
And yet, the university shifted towards professionalism before AI ("training a mind for the workforce" rather than "the good life").
Already, this transition did what the author observes AI is doing. I would hardly believe someone who cheats through an econ/stats major is less educated - if only through osmosis - than someone who honestly completes Business Economics.
And so I wonder - if the damage of AI is primarily instrumental to the broader trend of hyper-professionalism, what damage has it actually done?
If we automate away the signal to companies "yes, I can do stats for you," does that free students to focus more on the _less_ professional aspects of education?
Sure, it undercuts credentialism, making the "piece of paper" near worthless - but if our aim of education is just to "be better," should that not give us hope?
Over a decade ago, my orientation at UChicago included the traditional "Aims of Education" address. They packed the whole first-year class into the chapel to explain, at length, that this education will not be "useful."
You're not supposed to make more money, or be happier, or really become anything other than a better version of yourself.
This... can't be a signal of strength. There's a fine line between being agile and being erratic.
AI investment makes total sense as a proximal explanation. Minimize debt by trimming OpEx, then reinvest in compute. Seems smart.
And yet - this is what, the third layoff in 5 years? And weren't they doing aggressive performance cuts too? Are they workforce planning in 12 week sprints or something?
This reminds me of an overspending sports team: just toss together overpriced players/coaches, underperform, fire them all, do it again.
You're right, but it's because we made the conscious decision to not have a totally-open playing field after seeing how it went.
It's like the old code base: we made a bunch of incremental design decisions over 50+ years that are all layered on top of each other. They are now so complex that nobody can coherently explain the whole thing. But does that mean we should burn it down? Not necessarily. If we rebuild from scratch, we're liable to simply re-learn why we built the hacky solution in the first place.
Crypto is great. It's a wonderful innovation - and will likely succeed in many ways. But it won't replace central banks and regulators (except, potentially, by replicating them) because the institutions are actually useful.
> I see the same thing when I look at the real world: it is not a collection of objects, but rather a system of processes, and those processes are best understood through mathematics.
This sentence gets to me. He's _so close_ to right, it's just that the answer is from a world so different than where he lives.
In management consulting, I learned the exact same thing, _except_ that the best way to understand the system is through _social relations_ (read: office politics), not math. Such an understanding inevitably leads you, when you hope to create change, to FIRST establish a need, and THEN pose a solution.
He didn't blow it. He just needs to learn to establish the need.
> there’s no sense of desperation, ... People are still bewitched by the progress
People are desperate for "artistic expression". But needs don't exist in a vacuum.
Note that the only other place it works like this law. Lawyers are always "providing advice" about complex legal matters, with no actual responsibility for the outcome (with limited exceptions). So the idea that lawyers would apply similar logic to a reasonably-similar circumstance (in terms of complexity, difficulty, potential liability, etc.) is not unreasonable.