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Will Douglas Heaven writes:
Every time I'm asked what's next, the Luke Haynes song gets stuck in my head: “Please don't ask me about the future. I'm not a fortune teller.” But here it is. What will happen in 2030? My answer: the same, but different.
When it comes to predicting the consequences of generative AI in the near future, opinions differ. In one camp we have the AI Futures Project, a small donation-funded research organization led by former OpenAI researcher Daniel Kokotailo. The non-profit organization made a big splash back in April when it released AI 2027a speculative account of what the world will look like in two years.
The story follows the runaway advances of an artificial intelligence company called OpenBrain (any similarities are coincidental, etc.) to a choose-your-own-adventure boom or bust. Kokotailo and his co-authors have made no secret of their expectation that in the next decade, the impact of AI will surpass that of the Industrial Revolution, a 150-year period of economic and social upheaval so great that we still live in the world it caused.
At the other end of the scale we have the team Normal technology: Arvind Narayanan and Sayash Kapoor, a pair of researchers at Princeton University and co-authors of the book. Snake Oil AIwhich disprove not only most of AI 2027's predictions, but more importantly, its underlying worldview. They argue that this is not how technology works.
Progress on the cutting edge may be fast and furious, but changes in the broader economy and society as a whole occur at human speed. Widespread adoption of new technologies can be slow; acceptance is slower. AI will be no exception.
What should we do about these extremes? ChatGPT came out three years ago last month, but it's still unclear how good the latest versions of the technology are at replacing lawyers, software developers or (gulp) journalists. And new updates no longer bring such incremental changes in capabilities as before.
