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It has been funny to watch the rise of "China is beating us" rhetoric against the steady backdrop of "mercantilism is obsolete/bad" dogma, because the elephant in the room is that China has been running a textbook mercantilist playbook.
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.
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/
[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.
> 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.
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?
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.
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.
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"?
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.
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.
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...
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.)
And the tools did not become "exponentially sophisticated", one thing it's logarithmic, another is that the improvements are questionable. But "pervasive" - yes, granted.
