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Culture War Roundup for the week of January 9, 2023

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Critical Social Justice in the Era of Large Language Models

https://parrhesia.substack.com/p/critical-social-justice-in-the-era

Many anticipate that AI will have the ability to engage in novel and complex philosophical reasoning or contribute to scientific progress. While AI has yet to achieve this level of sophistication, models like ChatGPT demonstrates an impressive ability to generate meaningful text. I am skeptical about the usefulness and meaningfulness of articles from certain disciplines falling under the banner of Critical Social Justice. Finding connections between abstractions or interpreting text through a postmodern critical lense isn't particularly difficult. Nor does it lend itself to error or falsification. I think traits that allow CSJ scholarship to be hoaxed will put it at risk of domination by AI-generated articles. Scholars in the future will be highly prolific, but all their work will be generated trough computers. This will become a sort of open secret. All this scholarship produced will not advance humankind because CSJ scholarship is, at best, rather useless, and, at worst, socially harmful. In other disciplines more tethered to reality, AI generating acceptable papers would mean genuine progress.

Many anticipate that AI will have the ability to engage in novel and complex philosophical reasoning or contribute to scientific progress. While AI has yet to achieve this level of sophistication, models like ChatGPT demonstrates an impressive ability to generate meaningful text

Referencing my comment from last month my interaction with chatgpt has convinced me that we are actually very far from general AI. I think the current approaches are deadends, we need to find a different way and this new breakthrough could happen tomorrow or it could happen in 500 years, with equal probability.

That's unfair, it really struggles comprehending that words are comprised of individual letters. It's opaque to the alphabet by the nature of what it can see and learn from. I asked it to generate anagrams and it was absolutely hopeless at it. It gave me nonsense like 'overwrite is an anagram of obverse'. When I really coaxed it for an anagram of obverse and observe, it gave me rubbish like 'oversbe' and 'beovers' but recognized they weren't words. It couldn't get verbose, which was really ironic seeing as it was incredibly verbose in its descriptions.

It also could not answer a question about perfect numbers, it could not find the pattern between 8128, 496 and 28 no matter how I coaxed it. I doubt a human would've made that error after being prodded and poked toward seeing the answer.

But I don't talk about the other 50 university challenge questions it got right. I don't talk about the fairly creative and reasonable ideas it came up with for how to redesign vehicles. Teething problems like the perfect number issue and your time zone issue could surely be solved by increasing the power a thousandfold - that's what GPT-4 will be doing. At least it's likely that's the case. The anagram problem or 'word ending in i' problem requires a different kind of data processing but it's not really that important. You don't need to be able to identify anagrams to be functionally intelligent and achieve things in the real world.

If we have an intelligence that's 95-98% human-level, with superhuman speed and knowledge, we're not that far from AGI.

If we have an intelligence that's 95-98% human-level, with superhuman speed and knowledge, we're not that far from AGI.

We've been seeing, and can predict, that there are plenty of tasks which can be done by machines at the 95%-98% level, but which can't be done better than that by machines because the 95%-98% are the low hanging fruit and the remaining few percent requires much more intelligence. (Self-driving cars are one of these, but it's been known for far longer than this.)