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Will Douglas write Heaven:
Whenever I’m asked what’s coming next, I get a Luke Hines song stuck in my head: “Please don’t ask me about the future / I’m not one to tell fortunes.” But here goes. How will things be in 2030? My answer: same but different.
There are huge gulfs of opinion when it comes to predicting the near-future impact of generative AI. In one camp we have the AI ​​Future Project, a small grant-funded research organization led by former OpenAI researcher Daniel Kokotjlo. The nonprofit made a big splash back in April AI 2027a speculative account of what the world will look like from now on.
The story follows the runaway advances of an AI firm called OpenBrain (any similarities are coincidental, etc.) in a choose-your-own-adventure-style climax or doom ending. Kokotjlo and his colleagues make no bones about their expectation that AI’s impact in the next decade will exceed that of the Industrial Revolution.
At the other end of the scale we have the team General technology: Arvind Narayanan and Sayash Kapur, a pair of Princeton University researchers and co-facilitators of the book AI snake oilwhich not only backfires on most of AI 2027’s predictions, but more importantly on its underlying worldview. They say how technology works.
Progress may be thick and fast on the modern edge, but in the broader economy, and societies as a whole grow at human pace. Widespread adoption of new technologies can be slow. Slow acceptance. AI will be no different.
What should we make of these extremes? ChatGipt came out three years ago last month, but it’s still unclear how well the latest versions of the tech are at replacing lawyers or software developers or (GULP) journalists. And new updates no longer make the capacity changes that they once did.