âThe best way to predict the future is to invent itâ*âŚ
Dario Amodei, the CEO of AI purveyor Anthropic, has recently published a long (nearly 20,000 word) essay on the risks of artificial intelligence that he fears: Will AI become autonomous (and if so, to what ends)? Will AI be used for destructive pursposes (e.g., war or terrorism)? Will AI allow one or a small number of âactorsâ (corporations or states) to seize power? Will AI cause economic disruption (mass unemployment, radically-concentrated wealth, disruption in capital flows)? Will AI indirect effects (on our societies and individual lives) be destabilizing? (Perhaps tellingly, he doesnât explore the prospect of an economic crash on the back of an AI bubble, should one burstâ but that might be considered an âindirect effect,â as AI development would likely continue, but in fewer hands [consolidation] and on the heels of destabilizing financial turbulence.)
The essay is worth reading. At the same time, as Matt Levine suggests, we might wonder why pieces like this come not from AI nay-sayers, but from those rushing to build itâŚ
⌠in fact there seems to be a surprisingly strong positive correlation between noisily worrying about AI and being good at building AI. Probably the three most famous AI worriers in the world are Sam Altman, Dario Amodei, and Elon Musk, who are also the chief executive officers of three of the biggest AI labs; they take time out from their busy schedules of warning about the risks of AI to raise money to build AI faster. And they seem to hire a lot of their best researchers from, you know, worrying-about-AI forums on the internet. You could have different models here too. âWorrying about AI demonstrates the curiosity and epistemic humility and care that make a good AI researcher,â maybe. Or âperformatively worrying about AI is actually a perverse form of optimism about the power and imminence of AI, and we want those sorts of optimists.â I donât know. Itâs just a strange little empirical fact about modern workplace culture that I find delightful, though I suppose Iâll regret saying this when the robots enslave us.
Anyway if you run an AI lab and are trying to recruit the best researchers, you might promise them obvious perks like âthe smartest colleaguesâ and âthe most access to chipsâ and â$50 million,â but if you are creative you might promise the less obvious perks like âthe most opportunities to raise red flags.â They love thatâŚ
â source
In any case, precaution and prudence in the pursuit of AI advances seems wise. But perhaps even more, Tim OâReilly and Mike Loukides suggest, weâd profit from some disciplined foresight:
The market is betting that AI is an unprecedented technology breakthrough, valuing Sam Altman and Jensen Huang like demigods already astride the world. The slow progress of enterprise AI adoption from pilot to production, however, still suggests at least the possibility of a less earthshaking future. Which is right?
At OâReilly, we donât believe in predicting the future. But we do believe you can see signs of the future in the present. Every day, news items land, and if you read them with a kind of soft focus, they slowly add up. Trends are vectors with both a magnitude and a direction, and by watching a series of data points light up those vectors, you can see possible futures taking shapeâŚ
For AI in 2026 and beyond, we see two fundamentally different scenarios that have been competing for attention. Nearly every debate about AI, whether about jobs, about investment, about regulation, or about the shape of the economy to come, is really an argument about which of these scenarios is correctâŚ
[Tim and Mike explore an âAGI is an economic singularityâ scenario (see also here, here, and Amodeiâs essay, linked above), then an âAI is a normal technologyâ future (see also here); they enumerate signs and indicators to track; then consider 10 âwhat ifâ questions in order to explore the implications of the scenarios, honing in one ârobustâ implications for eachâ answers that are smart whichever way the future breaks. They concludeâŚ]
The future isnât something that happens to us; itâs something we create. The most robust strategy of all is to stop asking âWhat will happen?â and start asking âWhat future do we want to build?â
As Alan Kay once said, âThe best way to predict the future is to invent it.â Donât wait for the AI future to happen to you. Do what you can to shape it. Build the future you want to live inâŚ
Read in fullâ the essay is filled with deep insight. Taking the long view: âWhat If? AI in 2026 and Beyond,â from @timoreilly.bsky.social and @mikeloukides.hachyderm.io.ap.brid.gy.
[Image above: source]
* Alan Kay
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As we pave our own paths, we might send world-changing birthday greetings to a man who personified Alanâs injunction, Doug Engelbart; he was born on this date in 1925. An engineer and inventor who was a computing and internet pioneer, Doug is best remembered for his seminal work on human-computer interface issues, and for âthe Mother of All Demosâ in 1968, at which he demonstrated for the first time the computer mouse, hypertext, networked computers, and the earliest versions of graphical user interfaces⌠thatâs to say, computing as we know it, and all that computing enables.
https://youtu.be/B6rKUf9DWRI?si=nL09hD5GQD670AQO
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