How different would we think about artificial intelligence if AI pioneers Allen Newell and Herbert Simon had won support for the seemingly less hype-prone term of "complex information processing," rather than "artificial intelligence," which was ultimately adopted by the field? On the surface, this thought experiment is interesting because it asks if artificial intelligence is intrinsically hyped. That is, is the word alone enough to get us in trouble? This was the focus of a recent Wall Street Journal article where columnist Christopher Mims asks experts in artificial intelligence whether the name alone produces confusion and hype? Mims quotes Melanie Mitchell, a professor at the Santa Fe Institute, who quips, "What would the world be like if it [AI] was called that [complex information processing] instead?"

How different would we think about artificial intelligence if AI pioneers Allen Newell and Herbert Simon had won support for the seemingly less hype-prone term of "complex information processing," rather than "artificial intelligence," which was ultimately adopted by the field? On the surface, this thought experiment is interesting because it asks if artificial intelligence is intrinsically hyped. That is, is the word alone enough to get us in trouble? This was the focus of a recent Wall Street Journal article where columnist Christopher Mims asks experts in artificial intelligence whether the name alone produces confusion and hype? Mims quotes Melanie Mitchell, a professor at the Santa Fe Institute, who quips, "What would the world be like if it [AI] was called that [complex information processing] instead?"

"Hundreds of AI tools have been built to catch covid. That's a bold statement by Will Douglas Heaven, senior editor for AI at MIT Technology Review, and is quite likely correct. Despite dozens upon dozens of machine learning algorithms designed to diagnose patients or predict just how sick COVID-19 might make them, two independent reviews published in the British Medical Journal and Nature came to the same conclusion: none of them worked. But let's not write off artificial intelligence's impact on COVID-19 too soon. Though most ML algorithms failed, there's one area where they succeeded and succeeded big. Data scientists at Moderna managed to pull off a modern-day miracle using cloud infrastructure and machine learning, as recounted by Moderna chief data and AI officer Dave Johnson. Why did Moderna succeed while many other efforts failed? Given how fast medical researchers hastened to respond to the COVID-19 threat, it's understandable why so many data science projects failed.

Originally it was Complex Information Processing. Complex Information processing lives on now only in the title of the CIP Working Papers, a series started by Herb Simon in 1956 and still accumulating entries (to 447). However, from about 1965 much of the work on artificial intelligence that was not related to psychology began to appear in technical reports of the Computer Science Department. Starting in the early 1970s (on one can recall exactly when), they did become the subject of a general mailing and thus began to form what everyone thinks of as the CMU Computer Science Technical Reports.