It's easy to miss his real point due to the provocative headline - the froth and churn of AI in 2022-2024 is full of con artistry, but that doesn't mean it's all useless:
"But it's not all doom and gloom. Doctorow believes that the situation isn't a zero-sum game, and that once the dust settles, there may be some residual upshots that could drive meaningful technological progress in the future. 'Tech bubbles come in two varieties: The ones that leave something behind, and the ones that leave nothing behind,' Doctorow argued. Following the dotcom bubble popping, millions of young people were lured into the tech sector, creating an 'army of technologists.'"
Transformer neural networks have been catastrophically overhyped - they are considerably dumber than bees - but they are clearly useful for lots of things, and the engineering work on getting them to run cheaply will pay dividends when LLMs are run on more advanced architectures.
It feels surreal seeing so many comments like this here and in public discourse in general. The advertising/hype machine convincing people a low quality continuation model is the next coming of AI must be amazing.
LLMs have lots of cool advancements involved in them but isn't what you are being sold. Anybody who knows how these models work and isn't making money off them can explain just how limited they are and how they can't safely be applied at scale. Yet they are doing so anyways. Invest and lie while you can, and get out before it all falls apart.
>>A new randomized controlled trial by Harvard and Stanford economists finds that ChatGPT can substantially boost productivity for professionals completing everyday writing tasks.
>>Participants were randomly assigned realistic work simulations with or without access to ChatGPT.
>>Those with access to the AI tool completed assignments 40% faster while producing 18% higher quality output as judged by expert evaluators.
Any assessment of LLMs that overlooks the profound positive impact they are already having on society is completely inaccurate.
Yes, they do have use. They are also very oversold and literally being sold for jobs they cannot do.
It does help write things that were either formulaic or entirely without real content.
Allowing them to do analysis or summary of anything that isn't already in a Wikipedia entry is radically dangerous because of how good they are at hallucinating and lying (and we can't detect that at scale). It is like an automated "yes man". This is the most dangerous bubble in living memory and the cost of it popping will be in the failure of any industry that is foolish enough to rely on them at scale.
And to attack that study in particular, "help people who couldn't write well write better" is complicated, increasing accessibility is good, but there is a BIG difference in an increase in writing quality versus an increase in productivity AND correctness.
Everything new is going to be oversold. That is not an indictment of the technology, although it's also fair to point that out to counteract the exaggerated perceptions that the overselling creates.
Putting aside all of the hype, LLM are already providing enormous productivity boosts in some activities, and those boosts can be fairly characterized as revolutionary when you consider how significant they are and how quickly they came about since GPT2.
The future will have arrived!