Gregory's ServerThe issue: Big Tech has the $$ infrastructure, data, ability to pay talent, and access to market which no one else does. So as academics, you either pay retail for access, or get it discounted/free by yoking yourself to Big Tech (via dual affiliation, or just being hired). 2/
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BUT the current proposals to alleviate this imbalance largely exacerbate it. Insofar as they amount to gov paying Big Tech to get academics access to Big Tech resources. This strengthens Big Tech control & further normalize access to Big Tech infra as "the way AI gets done." 4/ But it's not just this. By accepting the frame that such access is vital/necessary, we're buying into Big Tech marketing that says AI is real, lasting, and requires the diversion of billion$ (that could be spent otherwise). 5/ In reality, there is a thick cloud of smokey hype around AI, and it's not clear that the promises being made by the corps betting billions will ever be fulfilled (IMO gen AI is ~a solution in search of a problem so big it justifies the $$ to create/run it, which few do). 6/ Which raises a much more urgent question: does AI justify the diversion of such funding from, say, libraries, parks, schools, etc. to Google, Amazon, Microsoft on behalf of research? And if so, where's the hard proof backing this significant tradeoff? 7/ For more, a paper I wrote a few years ago: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4135581 8/ And this stellar report from Sarah Myers West and Jai Vipra, via AI Now. 9/ https://ainowinstitute.org/publication/policy/compute-and-ai (Bonus, for the vocab builders among us, the word 'iatrogenic' is helpful in metaphorically describing the false solution space current proposals present.) |
IRL, no academic can afford to pay retail ($100b training runs, y'all). So, academic labs vie for access/proximity to Big Tech infra in pursuit of doing 'relevant' research--something that should alarm fans of academic neutrality/those concerned w conflict of interest. 3/