In the decades since the field began, most of the debate surrounding artificial intelligence has been about the intelligence part: can machines really think like we do? But in recent weeks, US President Donald Trump has kicked off an argument about the other part – and joined a long tradition of shifting the goal posts when it comes to AI. arXiv might not survive AI slop onslaught, warn mathematicians “The use of the word artificial makes intelligence fake, it makes it sound fake, and it is not fake. It’s actually amazing,” said Trump during a speech at the UN General Assembly on 22 September.
He is calling for artificial intelligence to be rebranded as “super intelligence”, backing this move with an executive order signed on 29 September and the launch this week of a body called the Super Intelligence Force for coordinating US AI policy. Putting aside the fact that “Super Intelligence Force” sounds like a Saturday morning cartoon, what are we to make of this attempted rebrand? Trump isn’t actually alone in seeking to distance modern AI systems from the original conception of AI in the 1940s and 50s.
Last year, Meta CEO Mark Zuckberg published a note declaring that “superintelligence” (one word) is now in sight. Reaching further back, the word was originally popularised by philosopher Nick Bostrom as the title of his 2014 book. For me, Trump’s super intelligence and Bostrom’s superintelligence have distinct meanings that are worth preserving.
Trump’s rebrand is an effort to cement US dominance in the field of AI – his executive order states that “the term ‘Super Intelligence’ more appropriately captures the promise, potential, and rapidly advancing capabilities of these technologies”. But superintelligence as envisioned by Bostrom goes far beyond the capabilities of our current AI systems. To understand why, we need to dig into history a bit more.
Long before the birth of ChatGPT, AI researchers distinguished between weak AI and strong AI, terms first defined by philosopher John Searle in a 1980 paper titled “Minds, brains, and programs”. Loosely speaking, he considered weak AI to be a computer simulation of a human mind, but not an actual mind itself, whereas he felt strong AI describes actual cognition emerging from software. Searle dismissed this latter idea as ridiculous: “No one supposes… that a computer simulation of a rainstorm will leave us all drenched.
Why on earth would anyone suppose that a computer simulation of understanding actually understood anything?” Decades on, I find it hard to disagree. In the wake of Searle’s influential paper, weak and strong AI underwent their own Trump-style rebranding, as people began to discuss differences in AI capabilities rather than AI consciousness – perhaps because the former is much easier to measure and moves the arena of debate from the philosophy department to the computer science lab. Weak AI merged with another term, narrow AI, to mean a system capable of human-level performance at a specific task.
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