Daron Acemoglu Profile picture
Jun 7 14 tweets 5 min read Twitter logo Read on Twitter
AI myth 3. Abundance myth. Building on AI myths 1 and 2, a third, and perhaps more pernicious one emerges: automation and human-like performance by AI will bring economic abundance, out of which all or most of society will benefit.
There are many versions of this, going back to IJ Good’s statement that “the first ultraintelligent machine is the last invention that man need ever make provided that the machine is docile enough to tell us how to keep it under control.”
Or futurist and Google technologist Ray Kurzweil’s periodic pronouncements that “singularity” is just around the corner, e.g., amazon.com/Singularity-Ne…. Or less fanciful versions where AI boosts productivity, so that most people can get by without work.
There are at least three problems with this abundance myth. First, once you abandon myths 1 and 2, it loses its appeal. If machines will not be ultraintelligent, it is less clear that they can really bring boundless abundance.
Second and more fundamentally, the automation logic underlying this view is not as compelling as it first appeared. This is in fact a more general point (building on my work with Pascual Restrepo, economics.mit.edu/sites/default/…). Let me illustrate it with a hypothetical example.
Imagine that we move towards this type of abundance based on automation. Suppose a very fast-paced automation in which 4% of all human tasks are automated every year (so that all human tasks are eliminated in 25 years). And suppose technology does nothing else than automation.
How much growth will this generate? Suppose AI is 50% more productive than humans (a whopping amount!). Then the aggregate productivity growth will be less than: 0.04 times 0.50 = 0.02. This is slower than US economic growth before the digital revolution; amazon.com/Rise-Fall-Amer…
Just automation will not get a huge productivity boost to the economy. If you want to increase productivity, it’s much easier and more effective to make workers more productive — hence we are back to machine usefulness and human-complementarity again.
Third, all of this discussion ignores how dystopian world without work would be. There are those who think this could be a happy world, e.g., “fully automated luxury communism” amazon.com/Fully-Automate…
Yet much work shows that people want to feel they are making a contribution to society. See, e.g., Reshmaan Hussam and co-authors: hbs.edu/ris/Publicatio…, showing people’s willingness to sacrifice one third of their earnings in order to do work rather than receive transfers.
The reality is probably even worse, because social networks and democratic participation would be badly affected by the world in which people become just consumers, not contributors. (I tried to write on this before, e.g., here: project-syndicate.org/commentary/soc…)
There are deep issues here. Michael Sandel, in his wonderful book, Tyranny of Merit, amazon.com/Tyranny-Merit-… suggests a notion of social justice based on contributions rather than just what people consume. The best of my knowledge, these ideas have not been fully developed yet.
I also recently wrote on this as part of a collection of essays, here unlocked.microsoft.com/ai-anthology/, that have just been released. My essay is here for those who are interested: unlocked.microsoft.com/ai-anthology/d…
Bottom line: the idea that AI will create abundance is on shaky grounds, and that we could build a well-functioning society on the back of AI-based production and little work for humans is even on shakier grounds. For more on this, see #PowerAndProgress, amazon.com/Power-Progress…

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More from @DAcemogluMIT

Jun 6
AI myth 2. Path to AGI: Advances in generative AI are taking us towards artificial general intelligence. E.g., most recently by several leading AI experts and entrepreneurs: safe.ai/statement-on-a…. Or recent articles showing “sparks of AGI” from GPT-4: arxiv.org/abs/2303.12712.
Once you think that machine-human mind analogies at the root of AI myth 1 are questionable, AI myth 2 becomes less convincing as well. If there is something quite special about the human mind, even large models of generative AI will not get us there.
But it goes beyond this. Even if AGI were feasible, the idea that the architecture of generative AI — based on predicting next word or words after a certain string — can achieve the highly sophisticated human cognition seems a big stretch.
Read 8 tweets
Jun 5
AI myth 1. Turing hypothesis, about computers and the human mind. Alan Turing made huge breakthroughs in mathematics, including with his analysis of computable functions. His ideas also shaped the way that many people think about the human mind.
A universal Turing machine can compute any computable object. Turing then worked on whether computers (and thus Turing machines) can be intelligent — meaning that they can do the mental steps that humans do.
But he and many others later came to conceive of human mind as a Turing machine, too. If this is so, then machine intelligence — as an intellectual and computer science program — makes sense.
Read 12 tweets
Jun 5
Motivated by what I see as misleading articles in coverage in the media, I will post a number of threads in the next several days on “AI myths” — ideas or claims about AI that should be questioned more. A couple of explanations would be useful to put these into context.
First, by “myths” I do not necessarily mean that the statements I will focus on are necessarily incorrect. I claim that they are accepted without sufficient evidence and they need to be questioned more, because they are having an oversized effect on public perceptions.
Second, I am not an AI researcher and some of the issues I raise will be in the hope of generating more questioning. Better ideas, correctives and further reactions are welcome.
Read 4 tweets
May 30
Another statement from leading AI experts and entrepreneurs has come out: safe.ai/statement-on-a…. It states “Mitigating the risk of global extinction from AI should be a global priority along other societal-scale risks such as pandemics and nuclear war”.
To me, this is disappointing. Of course, we should worry about all risks, and global extinction would be terrible. Yet I believe that this is the wrong thing to focus on, for at least three reasons.
First, despite what many experts argue, I am not convinced that there is a path from current generative AI towards anything approaching human intelligence. Models that become human-like and wipe out humanity seem to be more like Hollywood material, still.
Read 7 tweets
May 30
Do new technologies benefit workers? I used to think this was a simple question. And it is at the heart of my new book with @baselinescene, Power and Progress, amazon.com/Power-Progress…
First of all, we need to be more specific about “workers”. The most optimistic answer is that all or most workers will benefit from technological advances (e.g., those increasing average labor productivity). But in general, some worker groups can be harmed.
So let us focus on “workers on average”. Here, most economic models suggest the answer is yes. In fact, almost all of the models I discussed in my graduate textbook on economic growth, amazon.com/Introduction-M… (published in 2008) imply this!
Read 25 tweets
May 28
Preliminary but fairly clear results from the runoff of the Turkish elections show that President Erdogan will have a historic third term. This has implications for democracy and the economy.
For Turkish democracy, it’s not great news, but how bad things will be will depend on several factors. Let us distinguish five facets of democracy. First, judicial independence was very bad and probably cannot get much worse.
Second, the imperial presidency that Erdogan brought and jailing of politicians weakened the other pillar of separation of powers, the legislature, and there may be further sidelining of parliament, esp. since AKP now has fewer seats. This is one big threat.
Read 16 tweets

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