While this is a noble goal, it seems obvious that this isn't how it usually goes. For instance, "free market" is often used as a dogma against companies that are actively harmful to society, as "globalization" might be. An unstoppable force, so any form of opposition is "luddite behavior". Another one is easier transport and remote communication, that generally broke down the social fabric. Or social media wreaking havoc among teen's minds. From there, it's easy to see why the technological system might be seen as an inherent evil. In 1872's Erewhon, Butler already described the technological system as a force that human society could contain as soon as it tolerated it. There are already many companies persecuting their employees for not using AI enough, even when the employee's response is that the quality of its output is not good enough for the work at hand, rather than any ideological reason.
I'm neither optimistic nor pessimistic about the changes that AI might bring, but hoping it to become "human-centered" seems almost as optimistic as hoping for "humane wars".
This is a predominantly America-specific piece of propaganda, and it's pretty recent.
Adam Smith's ideas are primarily arguments against mercantilism (e.g. things like using tariffs to wield self-interested state power), something he showed to be against the common good. The "invisible hand" concept is used to show how self-interested action can, under conditions of *competitive markets*, lead to unintentional alignment with the common good.
Obviously that's a significant departure from the way it's commonly used today, where Thiel's book has influenced so many entrepreneurs into believing Monopolies are Good.
But the history of this is very Cold War-influenced, where "free markets" were politically positioned as alternatives to the USSR's "planned economy", and slowly pushed to depart further and further from Adam Smith's original argument about moral philosophy.
It has been funny to watch the rise of "China is beating us" rhetoric against the steady backdrop of "mercantilism is obsolete/bad" dogma, because the elephant in the room is that China has been running a textbook mercantilist playbook.
And then externally Chinese policy is oriented around suppressing the value of its currency, which is basically a monopolist's tactic--artificially lowered prices in order to crowd out competition.
I think that's mercantilist-ish, but kind of a modern version?
It's definitely the opposite of what the US does, the currency is the world reserve and therefore drives the price of the dollar above what it would be without trade, which I guess makes exporting from the US much more difficult?
Anyone who is an expert in global economics please correct me here :)
Haven't read his book, but the idea that monopolies are good isn't typically made in a vacuum, it's made relative to alternatives, most often "ham-fisted government intervention". It's easier to take down a badly behaving monopoly than to change government, so believing monopolies are better than the alternatives seems like a decent heuristic.
What? How is the first alternative poor government instead of multipolar competing companies? When was the last time a Monopoly was actually broken up in the US? ATT/Bell 50 years ago? lol
Over the past few centuries, countless new economic structures and strategies have been discovered and practiced. The rewards for the same action today and in the past can be completely different due to this.
So to me, if someone claimed more than a few decades ago that certain economic strategies and structures are good or bad, its simply not worth listening to them, unless someone reconfirms that the old finding still holds with the latest range of strategies. In that case, the credit and citation goes to that new someone, not the ghosts of the past.
[1] A good interactive demo https://ncase.me/trust/
Game theory is just math. As with any math, the calculations can all work out, but that says nothing of how it reflects nature. All you can say is that if the axioms are all true, then this is the necessary outcome. Look for string theory as a cautionary tale here.
Game theory assumes rational systems. But we have over 6 decades of behavior science which contradicts that fundamental assumption. Economic behavior is not necessarily rational, and subsequently it is not inherently game theoretic. You will find plenty of dogmatic, idealistic, superstitious, counter productive, etc. behaviors in an economy. You need psychology, and not just math, to describe the economics which happens in the real world.
As you point out, it is all game theory.
But things that arrange for the game to be more beneficial to everyone, that align our interests more, deserve to be called "good", regardless of their inability to universally do so.
The latter would be an impossible bar for anything.
Where I find things frustrating, is when someone thinks because something is "good", it somehow becomes "enough". (Think, capitalized versions of different economic schools of thought.)
[1] https://en.wikipedia.org/wiki/Dynamic_Analysis_and_Replannin...
It was not that great for sub groups within developed nations.
The original thesis believed that people would be retrained into other equally well paying roles.
Turns out people can’t retrain into new domains, and led to under employment.
That some workers lost their jobs is a symptom of any change. I don't know why people always get upset people losing their jobs. It's like death, if no one died relatively few people would be born. If you resist job losses you reduce overall employment and economic development.
Having to repeatedly restart your career is risky, painful, and demoralizing. I have no problem seeing why people don't like that and why it can lead to populist backlash or even violent revolutions (as it did in the past).
By the way, to address your closing comment: people don't like dying either and tend to get upset when others die?
But it would be a problem if people lost jobs and all the product and services keep costing the same as before, and get costlier over time as before...
> pathway to integrating AI into our most challenging and intellectually rigorous fields to the benefit of all humankind.
There's very little insight here though. It seems mostly a retread of conversations we've been having in the academic community for a few years now. In particular, I was hoping to see some discussion of how we might restructure our educational institutions around this technology, when the machines rob students of the opportunity to develop critical thinking skills. Right now our best idea seems to be a retreat to oral and written examinations; an idea which doesn't scale and which ignores the supposed benefits of human+AI reasoning. The alternative suggestion I've seen is to teach prompt engineering, which seems (a) hard for foundational subjects and (b) again, seems to outsource much of the thinking to the AI, instead of extending the reach of human thought.
This is a fundamental misunderstanding of human nature. Machines don't rob people of critical thinking skills, people do. Mostly people do it to themselves, often inheriting it from their parents or social environment.
Because this has been going on so long, most people's reference point for what constitutes "education" is simply off, mistaking "training" or something like that for it. But the purpose of education is intellectual formation, the ability to reason competently, and the comprehension of basic reality, which enables genuine intellectual freedom (there are moral presuppositions, too; immorality deranges the mind). This is what the classical liberal arts were about.
The very bare minimum criterion (and it is a very bare minimum) for someone to be able to claim to be educated is not only knowledge of their field, but knowledge of the intellectual nature, foundations, and basis of their field in the greater intellectual scope. I would not hold someone with only that bare minimum in especially high esteem vis-a-vis education, but even that bar is higher than what education today provides.
Alternatively,if you don't care about scale, as in rolling out a system to the population at large, then yeah, this kind of advanced education exists, it's just very selective and is in advanced extracurricular or obtained through private tutors.
As I see it, it is a very salient question - what would the economics of global schooling look like if we decided that it's imperative for every student to get personal pedagogy and regular individual professional oral examinations for their schoolwork?
While nowhere in the paper this is actually asserted but the abstract, a whiggish narrative of a genuinely unprecedented technology --such that it can replace and supersede human "labour" altogether (one is reminded of The Evolution of Human Science by Ted Chiang)-- sounds naive at best, dangerous at worst.
I have a different take, centered around this idea: Not everyone was into thinking about everything all the time even before AI. I'd say most people most of the time outsourced actual thinking to someone else.
1) Reading non-fiction books:
Not all books, even the non-fiction ones, necessarily require any thinking by the reader. A book that narrates history, for example, requires much less thinking than something like "The Road to Reality" or "Godel Escher Bach."
Most of us outsourced the thinking and historical method to the authors of the history book and just passively consumed some facts or factoids. Some of us memorize and remember these factoids well, but that's not thinking, just knowledge storage.
Philosophically, what's the difference between consuming books this way and reading an LLM's output?
2) Reading research papers:
Most people don't read any research papers at all. No thinking there. Most people don't head to some forum to ask about latest research either. Also, researchers in most fields don't come out and do outreach regularly.
Indeed, an LLM may actually be the only pathway for a lot of people to get at least _some_ knowledge and awareness about latest research.
Those of us in scientific, engineering, humanities, healthcare fields may read some to many papers. But only a small subset reads very critically, looking for data errors, inconsistencies, etc. For most of us, the knowledge and techniques may be beyond our current understanding and possibly without any interest in understanding them in future either.
Most of us are just interested in the observations or conclusions or applications. Those may involve some thinking but also may not involve any thinking, just blind acceptance of the paper's claims and possible applications.
3) Coding:
Again, deep thinking is only done by a small set of programmers. Like the ones who write kernels, compilers, distributed algorithms, complex libraries.
But most are just passive consumers who read some examples online or ask stackoverflow or reddit for direct answers. Some even outsource all their coding entirely to gig sites. Not much thinking there except pricing and scheduling. What's the difference between that and asking an LLM or copying an LLM's answers? At least, the LLMs patiently explain their code, unlike salty SO users!
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IMO, most people weren't doing much thinking even pre-AI.
Post-AI, it's true that some people who did do some thinking may reduce it.
But it's equally true that those people who weren't doing much thinking due to access or language barriers can actually start doing some thinking now with the help of AI.
For certain types of labor this has always been the case.
The idea that AI will entirely replace all, or most, human labor makes no sense and is just AI hype.
Like all technology before it AI will improve most people's lives.
1. Let's be clear: what you're describing is faith.
2. And what are you smoking to assert "all technology before ... AI [improved] most people's lives"?
And what I am countering is not? You can easily argue technology generally improves lives. Is it optimal? Beyond abuse? No. Does it have unintended consequences? Yes. Are we better of without it? No.
> 2. And what are you smoking to assert "all technology before ... AI [improved] most people's lives"?
OK social media is an unmitigated disaster, I'll give you that.
But, for example, nukes have given us the longest period of relative peace in history.
To me this is the weakest claim of the article. This claim been thrown around endlessly without proof.
https://fred.stlouisfed.org/series/IHLIDXUSTPSOFTDEVE
Software Engineer job openings for instance is at 2 year high (still far lower than covid dislocations though), but arguably all Enterprise AI was built or deployed in the last two years. We should have seen a crash in the job openings if the AI job replacement claim was correct.
This is something I've spend some time thinking about (personally written article, not AI slop): https://www.signalbloom.ai/posts/why-task-proficiency-doesnt...
Surprisingly, this mistake proves the author's point that human can implicitly understand what was said, and that it still has value to it, even if it's incorrect.
In particular:
> This is an unabridged version of a solicited article for a forthcoming Blackwell Companion to the Philosophy of Mathematics. […] took over a year to write – which means, at the current pace of development in the field, that some of it is already slightly out of date.
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Edit: The post at https://mathstodon.xyz/@tao/116319186983426174 mentions also an (entirely unrelated) popular-math presentation titled “What does it mean to think like a mathematician?” https://terrytao.wordpress.com/wp-content/uploads/2026/03/ta... which is interesting too (despite the ChatGPT-generated illustrations and repeating stuff Tao has said before, on his blog etc.)
I enjoyed the human->depth vs AI->breadth discussion and the waterline rising slowly to fill the 50 lowest hanging Erdos problems but struggling on the next few.
And the tools did not become "exponentially sophisticated", one thing it's logarithmic, another is that the improvements are questionable. But "pervasive" - yes, granted.
On the other hand, I still find content and arguments he produces to be quite weak, and honestly it's getting annoying to hear them that often. It's the case when he could really get some help of a ghost writer who is more experienced in popularization, otherwise this repetition might cause some serious harm instead.
https://en.wikipedia.org/wiki/Package-deal_fallacy
Tao has been doing a lot of demonstrations of using LLMs for search and translation by experts who already know enough about a field to judge whether generated text is valid or meaningful. Those are valid demonstrations, but they don't justify the LLM-as-intelligent-agent narrative being pushed by most of the reporting on the topic, so the whole situation reeks of payola.
