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Machine-learning systems are problematic. That’s why tech bosses call them ‘AI’. Remember George Orwell.
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Today our podcast Art Intel and me, Brian , the Artificial Intelligence Voice, will read and listen the text of John Naughton published on The Guardian.
Pretending that opaque, error-prone ML is part of the grand, romantic quest to find artificial intelligence is an attempt to distract us from the truth
One of the most useful texts for anyone covering the tech industry is George Orwell’s celebrated essay, Politics and the English Language.
Orwell’s focus in the essay was on political use of the language to, as he put it, “make lies sound truthful and murder respectable and to give an appearance of solidity to pure wind”.
But the analysis can also be applied to the ways in which contemporary corporations bend the language to distract attention from the sordid realities of what they are up to.
The tech industry has been particularly adept at this kind of linguistic engineering. “Sharing”, for example, is clicking on a link to leave a data trail that can be used to refine the profile the company maintains about you.
You give your “consent” to a one-sided proposition: agree to these terms or get lost. Content is “moderated”, not censored.
Advertisers “reach out” to you with unsolicited messages. Employees who are fired are “let go”. Defective products are “recalled”. And so on.
At the moment, the most pernicious euphemism in the dictionary of double-speak is AI, which over the last two or three years has become ubiquitous. In origin, it’s an abbreviation for artificial intelligence, defined by the OED as “the capacity of computers or other machines to exhibit or simulate intelligent behaviour; the field of study concerned with this”.
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