Rather than trying to amass oceans of scientific papers listing self-evident results and futile findings, instead of inserting AI and unnecessary technologies into the most human of activities, like teaching, universities and research institutions should value and support their people (something that, nowadays, happens more and more rarely) and be especially inclusive of the ones among them who are able to think outside the box, to go the extra mile towards the achievement of what is believed to be unattainable or, simply, impossible – like the decipherment of undeciphered writing systems.I agree with all of the above, not least the reservations about AI matching human creativity in the foreseeable future.There’s no question that challenges remain. Linear A, the Phaistos Disc, the Indus Valley script, the Rongorongo writing system, the Singapore Stone and many other mysteries still await their codebreakers. Their decipherment seems unlikely – especially for scripts with very few surviving texts – but so too did the breakthroughs in Ancient Egyptian hieroglyphs and Linear B.
This long article has a good discussion of the challenges of deciphering lost languages, a challenge that is more difficult today because most of the remaining lost-language remnants survive in such sparse samples. It also includes detailed accounts of Champollion's decipherment of Egyptian hierogyphics and Ventris's decipherment of Linear B.
The headline mentions the decipherment of cuneiform, but the article says little about it. For more, see here, here and (especially) here.
For a test-case of AI decipherment from some years ago, using Ugaritic, see here and here. For more comments on the use of AI for various aspects of ancient language decipherment and analysis, see here, here (especially), here, and here.
For the importance of the decipherment of the ancient Egyptian and cuneiform languages, see my post Why we need Akkadian (and the humanities!), again from some years ago, but still relevant. See also here.
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