The AI Effect, or "moving the goalposts," highlights a shifting perspective in the evaluation of artificial intelligence capabilities. As AI systems achieve proficiency in tasks previously deemed exclusive to human intelligence, such as playing chess or recognizing speech, these accomplishments are often downgraded in significance or no longer regarded as true measures of intelligence. This phenomenon underscores the evolving nature of AI benchmarks and the human tendency to recalibrate what constitutes intelligent behavior as technology advances. The AI Effect poses a philosophical challenge to defining AI and measuring its progress, suggesting that as long as machines continue to emulate and surpass human capabilities, society's benchmarks for "true" intelligence will keep advancing.
Discussions around the AI Effect have been part of AI discourse since the early days of the field, with notable mentions in the 20th century as AI began achieving milestones previously thought to require human-like intelligence.
Although the AI Effect is a widely recognized phenomenon within the AI community, it is more of a cultural and philosophical observation rather than a technical concept attributed to specific individuals. Figures such as Alan Turing have contributed to the broader dialogue on measuring AI intelligence, which indirectly encompasses discussions about the AI Effect. Turing's famous Turing Test, proposed in 1950, can be seen as an early acknowledgment of the challenges in defining and recognizing AI intelligence, setting the stage for future discussions about the AI Effect.