Comment by wahern
6 days ago
> 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.p... (https://web.archive.org/web/20250502052226/http://zakuski.ut...)
Applying this to today seems like a stretch. Short of some sort of mythical dark age style destruction of knowledge, what we have today benefits from widespread use of writing and other forms of communication which didn't exist back then.
It seems like the biggest risks come from willful ignorance of history, which we do see in some quarters but by no means all.
The context of the whole essay was more about the way we have a tendency to confuse models with reality, in particular the way we build human-like machines based on contemporary theories about how humans work, then later fall into the assumption the theories were accurate simply because the machines are indeed useful. It's a pernicious kind of self-reinforcing confirmation bias. And it applies at least as much to AI, and LLMs specifically, as any earlier example. Whether or not one believes LLMs strongly parallel certain human mental processes, or even if in fact they do, surely we must admit there's much more undiscovered complexity and phenomena, and the pursuit of discovering those phenomena is going to be hampered to some extent by our investment in understanding them in terms of these otherwise successful tools we've built.