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Comment by tedsanders | Hacker News Reader

Sol is not world-endingly dangerous. I work at OpenAI and I've never heard a single person ever come close to claiming that. I think you're bashing a straw man here.

One can simultaneously believe:

- GPT-5.6 Sol will not end the world

- GPT-5.6 Sol does far more good than bad

- GPT-5.6 Sol does bad things on occasion, and it's worth investing a lot of effort to figure out how to make it do bad things less often, especially as models get more capable

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What do you recommend people who are technically inclined enough to participate meaningfully here on HN, but do not work at the labs and cannot assist in that capacity, do to help the broader public understand this technology better and mitigate potential risks (by e.g. ‘up-leveling everybody’ through AI literacy etc and other sorts of collective defensive efforts)?

Not sure, to be honest. I don’t think I have any special insight here. My own approach is conversations with friends and family, and the occasional social media post. Exposure and experience are the best teachers, and that’s one reason I’m happy OpenAI tries to make their models generally available. But you could argue, perhaps correctly, that broad access to dumber models actually causes the public to update in the wrong direction on AI.

My experience as a practitioner and educator in the space lead me to think it might be an issue of how AI cannot be easily perceived at a 'classical level' by most humans. In other words, people are 'far from the metal' when using consumer AI tools, and that leads them to develop the wrong understanding about it. When I provide a demo of e.g. local AI, say in LM Studio showing the console of it rapidly flashing through thousands of words in just a few seconds, and my machine heats up and the fans spin, the 'theatrics' of it, the very real-time feedback from the system, make people correctly update about what the tech is capable of, how it works, etc (despite what they may have heard online cranks say to the contrary). But I am only one person, and there is only so much of that I can do on my own that will 'scale' in time... (and this is to say nothing about severe deficits in peoples' understanding of how weights are not verbatim representations of data, how pre-training vs post-training works, the models as amnesiacs (and hence 'one-way single-purpose conversations'), how context/memory works, context rot, etc - and hence all the 2nd and 3rd order effects that can arise from such a paradigm, e.g. unintended consequences from agent swarms, etc)

I would very much like to know more about your educational approach with regard to:

> When I provide a demo of e.g. local AI, say in LM Studio showing the console of it rapidly flashing through thousands of words

Because I am one of those individuals very interested in doing more to actively inform my family, friends, neighbors and fellow citizens facts about AI. I've actually considered doing talks at local libraries for senior citizens (or whoever), etc., and trying to build up a systematic way to get more other folks doing the same.

This is far too reasonable for this thread.

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