The flip side of that is that every time a new AI approach becomes popular even more people proclaim "this is what thinking is", believing that the new technolo

The flip side of that is that every time a new AI approach becomes popular even more people proclaim "this is what thinking is", believing that the new technology reflects the underlying process of human intelligence. This phenomenon goes back further than AI as a formal discipline, to early computers, and even during the age of mechanical computers. There are parallels with robotics, where for centuries anything that could seemingly move like a human was perceived to be imbued with human-like qualities.[1] The human instinct to anthropomorphize is deep-seated and powerful. I keep returning to this insight by a researcher of the Antikythera Mechanism, which in the context of ML seems even more apropos today than in 1986: > I would like to conclude by telling a cautionary tale. Let us try and place the Antikythera Mechanism within the global context of ancient Greek thought. Firstly came the astronomers observing the motions of the heavenly bodies and collecting data. Secondly came the mathematicians inventing mathematical notation to describe the motions and fit the data. Thirdly came the technicians making mechanical models to simulate those mathematical constructions, like the Antikythera Mechanism. Fourthly came generations of students who learned their astronomy from these machines. Fifthly came scientists whose imagination had been so blinkered by generations of such learning that they actually believed that this was how the heavens worked. Sixthly came the authorities who insisted upon the received dogma. And so the human race was fooled into accepting the Ptolemaic system for a thousand years. > Today we are in danger of making the same mistake over computers. Our present generation is able to view them with an appropriate skepticism when necessary. But our children's children may be brought up within a society dominated by computers, that they may actually believe this is how our brains work. We do not want the human race to be fooled again for another thousand years. -- E.C. Zeeman, Gears from the Greeks, January 1986, http://zakuski.utsa.edu/~gokhman/ecz/gears_from_the_greeks.pdf http://zakuski.utsa.edu/~gokhman/ecz/gears_from_the_greeks.p... I also regularly return to Richard Stallman's admonition regarding the use of the term, intellectual property. He deeply disliked that term and argued it was designed to obfuscate, through self-serving[2] equivocations, the legal principles behind the laws of copyright, patent, trademark, trade secret, etc. Contemporary machine learning may rightly be called artificial intelligence, but to conflate it with human intelligence is folly. It's clearly not human intelligence. It's something else. The same way dolphin intelligence isn't human intelligence, or a calculator isn't human intelligence. These things may be able to tell us something about the contours and limits of human intelligence, especially in contrast, but equivocations or even simple direct comparisons only serve to obfuscate and constrain how we think of intelligence. [1] See, e.g., the 1927 film Metropolis, which played off prevailing beliefs and fears about the progress and direction of actuated machines. [2] Serving the interests of those who profit the most from expanding the scope and duration of these legal regimes by obfuscating the original intent and design behind each regime, replacing them with concepts and processes that favored expansion.