> I don't really get the original argument. I never thought "todays AI isn't smart, but if it could play Go, that would be an intelligent agent!" I think the "

> I don't really get the original argument. I never thought "todays AI isn't smart, but if it could play Go, that would be an intelligent agent!" I think the "AI effect" primarily refers to how practical successes in the field of AI get taken for granted and no longer considered AI - leaving AI with the unsolved problems and bleeding-edge research. If you ordered something for Christmas recently, 'AI' may have been used to understand your search query, rank relevant pages, allow the websites to determine you're not a DDoS attack, allow your bank to determine that your transaction is legitimate, let the confirmation email through your spam filter, then work out routes and other logistics to get it delivered. Before you started your order, 'AI' may have also been involved in the product's design (like optimization of circuits), used to detect defects during manufacturing, or for monitoring and maintenance of rail/road surfaces used for delivery. But all this has been working for a while, so fades into the background rather than being what people think of as AI. There is also that more philosophical element (rather than just about perception of AI as a field) involving our boundary for what "intelligence" is. People won't usually phrase it as "once AI can do X I'll be happy calling it intelligent", but sometimes "doing X requires intelligence" or "an unintelligent machine could never do X", with similar implications. Like, going way back, Descartes' claims that machines will be incapable of responding appropriately in conversation. With AI becoming increasingly capable, even though the timeframes are often far longer than AI-optimists predict, a prevalent view seems to be that AI could behave identically to humans and still not be intelligent. Possibly even be physically identical to humans and still not be intelligent, if you buy into the P-zombie argument (and additionally their nomological possibility, which most people don't). Holding a remote job (including the inverview and portfolio process) is an interesting benchmark, but I can't help but feel your reponse when that gets achieved may be "oh but that's basically just patchwork of language models - clearly in retrospect my criteria must not have been strict enough".