The possibilities made available for bad actors to manipulate the masses with this technology is unprecedented and terrible.
I think there needs to be a return to a more siloed, community based, web-of-trust model of communication where there is confidence that the people being interacted with are actually human.
A persuasive, funny, distributed army of commenters that sound like real people that are given prompts by people with the resources to spin up accounts undetected (or allowed via backdoor deals) and mimic the general public is nightmare material. I think a fair bit of that kind of manipulation is already starting to ramp up.
This technology is in my opinion on the same scale of danger as nuclear weapons and needs to be treated as such. It’s insanely dangerous.
I don’t think it can be regulated out of existence, and that also risks concentrating it in the hands of bad actors. I think attempts to regulate it effectively should still be made. But I think the only practical way out of this is some kind of distributed private set of communication networks where people control their own servers, their own online identities, and only connect to people they meet in real life (and then connect to others through networks of relations). I think that’s more realistically accomplishable then it sounds and is desperately needed.
Like train a classifier(with good jokes and bad jokes) on r/jokes according to the scores, to filter/sort automatically what GPT generates?
1. It _really_ _really_ wants to repeat itself and your own prompt, which is antithetical to comedy. The temperature, presence penalty, and frequency penalty parameters _kinda_ help, but when you increase those too much, things start to break in other ways, like you hit an <|endoftext|> before you hit the punchline you were looking for, because the model is trying so hard to avoid repetition.
2. Being just a predictive language model, it doesn't really _know_ you want comedy, nor can you purposefully instruct it to be funny (even in the instruct models). The AI is going to bias towards playing it completely straight.
3. Since it was trained on the entire internet, there's a good chance if you get a funny output, it just "plagiarized" someone else's joke, which can be awfully disappointing when you Google your output to see if that was the case.
4. Sadly, despite the name, OpenAI is very restrictive in their use cases, and they're heavily indexed towards appealing to commercial customers. The playground is still overly sensitive about what it considers "inappropriate" outputs, and their list of disallowed use cases seems longer than the rest of their documentation. It's hard for me to imagine them allowing too many funny use cases of their API, given what I've read on there.
There are many professional comedians that I don't find funny at all but enough people do that they can make a career out of it.
To me, it would be like trying to classify music with a good or bad label. It is so subjective to taste.