The issue is, the regulations are tailored to address any of those concerns, some of which may not even be solvable through regulation at all:
> The implications of deepfakes and similar frauds alone are potentially devastating to informed political debate in democracies, safe and effective dissemination of public health information in emergencies, and plenty of other realistic and important trust scenarios.
The horse is out of the barn on this one. You can't stop this by regulating anything because the models necessary to do it have already been released, would continue to be released from other countries, and one of the primary purveyors of this sort of thing will be adversarial nation states, who obviously aren't going to comply with any laws you pass.
> The implications of LLMs are potentially wonderful in terms of providing better access to information for everyone but we already know that they are also capable of making serious mistakes or even generating complete nonsense that a non-expert user might not recognise as such.
Which is why AI summaries are largely a gimmick and people are figuring that out.
> they could very rapidly shift the balance from compensating those who produce useful creative content to compensating those who run the summary service.
This already happened quite some time ago with search engines. People want the answer, not a paywall, so the search engine gives them an unpaywalled site with the answer (and gets an ad impression from it) and the paywalled sites lose to the ad-supported ones. But then the operations that can't survive on ad impressions lose out, and even the ad-supported ones doing original research lose out because you can't copyright facts so anyone paying to do original reporting will see their stories covered by every other outlet that doesn't. Then the most popular news sites become scummy lowest-common-denominator partisan hacks beholden to advertisers with spam-laden websites to match.
Fixing this would require something along the lines of the old model NPR used to use, i.e. "free" yet listener-supported reporting, but they stopped doing that and became a partisan outlet supported by advertising. The closest contemporary thing seems to be the Substacks where most of the stories are free to read but you're encouraged to subscribe and the subscriptions are enough to sustain the content creation.
The AI thing doesn't change this much if at all. A cheap AI summary isn't going to displace original content any more than a cheap rephrasing by a competing outlet does already.
> Next we get to computer vision and its applications in fields like self-driving vehicles. Again we've already seen plenty of examples where cars have been tricked into stopping suddenly or otherwise misbehaving when for example someone projected a fake road sign onto the road in front of them.
But where does the regulation come in here? When it does that it's obviously a bug and the manufacturers already have the incentive to want to fix it because their customers won't like it. And there are already laws specifying what happens when a carmaker sells a car that doesn't behave right.
> Again there is a second serious concern with systems like computer vision, audio classification, and natural language processing and that is privacy.
Which is really almost nothing to do with AI and the main solutions to it are giving people alternatives to the existing systems that invade their privacy. Indeed, the hard problem there is replacing existing "free" systems with something that doesn't put more costs on people, when the existing systems are "free" specifically because of that privacy invasion.
If a government wants to do something about this, fund the development of real free software that replaces the proprietary services hoovering up everyone's data.