The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by arguing that it is not "real" intelligence.
Author Pamela McCorduck writes: "It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'." Researcher Rodney Brooks complains: "Every time we figure out a piece of it, it stops being magical; we say, 'Oh, that's just a computation.'"
Definition
"The AI effect" is that line of thinking, the tendency to redefine AI to mean: "AI is anything that has not been done yet." This is the common public misperception, that as soon as AI successfully solves a problem, that solution method is no longer within the domain of AI. Geist credits John McCarthy giving this phenomenon its name, the "AI effect".
McCorduck calls it an "odd paradox" that "practical AI successes, computational programs that actually achieved intelligent behavior, were soon assimilated into whatever application domain they were found to be useful in, and became silent partners alongside other problem-solving approaches, which left AI researchers to deal only with the 'failures', the tough nuts that couldn't yet be cracked." It is an example of moving the goalposts.
Tesler's Theorem is: "AI is whatever hasn't been done yet." Larry Tesler Douglas Hofstadter quotes this as do many other commentators.
When problems have not yet been formalised, they can still be characterised by a model of computation that includes human computation. The computational burden of a problem is split between a computer and a human: one part is solved by computer and the other part solved by a human. This formalisation is referred to as a human-assisted Turing machine.
AI applications become mainstream
Software and algorithms developed by AI researchers are now integrated into many applications throughout the world, without really being called AI. This underappreciation is known from such diverse fields as computer chess, marketing, agricultural automation and hospitality.
Michael Swaine reports "AI advances are not trumpeted as artificial intelligence so much these days, but are often seen as advances in some other field". "AI has become more important as it has become less conspicuous", Patrick Winston says. "These days, it is hard to find a big system that does not work, in part, because of ideas developed or matured in the AI world."
According to Stottler Henke, "The great practical benefits of AI applications and even the existence of AI in many software products go largely unnoticed by many despite the already widespread use of AI techniques in software. This is the AI effect. Many marketing people don't use the term 'artificial intelligence' even when their company's products rely on some AI techniques. Why not?"
Marvin Minsky writes "This paradox resulted from the fact that whenever an AI research project made a useful new discovery, that product usually quickly spun off to form a new scientific or commercial specialty with its own distinctive name. These changes in name led outsiders to ask, Why do we see so little progress in the central field of artificial intelligence?"
Nick Bostrom observes that "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labelled AI anymore."
The AI effect on decision-making in supply chain risk management is a severely understudied area.
To avoid the AI effect problem, the editors of a special issue of IEEE Software on AI and software engineering recommend not overselling not hyping the real achievable results to start with.
The Bulletin of the Atomic Scientists organization views the AI effect as a worldwide strategic military threat. As they point out it obscures the fact that applications of AI had already found their way into both US and Soviet militaries during the Cold War. AI tools to advise humans regarding weapons deployment were even developed by both sides and received very limited usage during that time. They believe this constantly shifting failure to recognise AI continues to undermine human recognition of security threats in the present day.
For example, AI helps YouTube review uploaded videos and replaces employees who were previously responsible for reviewing them. About 47% of jobs are predicted to be replaced by AI in the next 20 years.