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Will Douglas Heaven writes:
Each time I’m asked what’s coming next, I get a Luke Haines song stuck in my head: “Please don’t ask me in regards to the future / I’m not a fortune teller.” But here goes. What’s going to things be like in 2030? My answer: same but different.
There are huge gulfs of opinion on the subject of predicting the near-future impacts of generative AI. In a single camp now we have the AI Futures Project, a small donation-funded research outfit led by former OpenAI researcher Daniel Kokotajlo. The nonprofit made a giant splash back in April with AI 2027, a speculative account of what the world will appear like two years from now.
The story follows the runaway advances of an AI firm called OpenBrain (any similarities are coincidental, etc.) all of the solution to a choose-your-own-adventure-style boom or doom ending. Kokotajlo and his coauthors make no bones about their expectation that in the subsequent decade the impact of AI will exceed that of the Industrial Revolution—a 150-year period of economic and social upheaval so great that we still live on the earth it wrought.
At the opposite end of the dimensions now we have team Normal Technology: Arvind Narayanan and Sayash Kapoor, a pair of Princeton University researchers and coauthors of the book , who beat back not only on most of AI 2027’s predictions but, more necessary, on its foundational worldview. That’s not how technology works, they argue.
Advances on the innovative may come thick and fast, but change across the broader economy, and society as an entire, moves at human speed. Widespread adoption of latest technologies might be slow; acceptance slower. AI shall be no different.
What should we make of those extremes? ChatGPT got here out three years ago last month, nevertheless it’s still not clear just how good the most recent versions of this tech are at replacing lawyers or software developers or (gulp) journalists. And latest updates not bring the step changes in capability that they once did.
