A prominent computer scientist argues that a proposal made by Alan Turing, widely regarded as the father of theoretical computer science, sent artificial intelligence research in the wrong direction for the past 75 years.
In his new analysis, “Turing’s Mistake: Escaping the Yoke of Unintelligent Machines,” Peter J. Denning examines ideas Turing advanced in 1950. At the time, many scientists believed that human intelligence could exist independently of the body and might therefore be recreated as software running on a digital computer.
Denning also disputes the idea that machine intelligence can be demonstrated through an imitation game (now known as the Turing test).
“These two claims have shaped much of AI research and development,” Denning writes. “My premise is that our acquiescence to these claims has led to the AI mess in which we find ourselves today.”
According to Denning, the artificial intelligence (AI) systems now being developed are unlikely to produce human-level intelligence, known as artificial general intelligence (AGI). Instead, he warns, they may create serious dangers without ever thinking like humans.
Why Tacit Knowledge Matters
Central to Denning’s argument is the idea of tacit knowledge. This refers to the enormous amount of human understanding that people possess but cannot fully express in words or translate into symbols that a machine can process.
Denning describes five broad forms of tacit knowledge that he says ‘elude machine learning’. They include common sense, everyday interactions with people and the environment, feelings and perceptions, practical skills, and the cultural and historical background shared by societies.
Researchers have spent decades trying to record common sense in a form computers can use. Beginning in the 1980s, Douglas Lenat’s ambitious Cyc project set out to build a vast database of common-sense facts. After 40 years of work, the project contained 25 million entries.
“Yet even this treasury could not add up to a background of common sense sufficient to make expert systems smart enough to be experts,” Denning notes. “Cyc validated that much of the knowledge that makes people experts cannot be articulated as propositions.”
Source: SciTechDaily
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