[Edit: I've updated this post on October 24 in response to some feedback]
NIMBYs don’t call themselves NIMBYs. They call themselves affordable housing advocates or community representatives or environmental campaigners. They’re usually not against building houses. They just want to make sure that those houses are affordable, attractive to existing residents, and don’t destroy habitat for birds and stuff.
Who can argue with that? If, ultimately, those demands stop houses from being built entirely, well, that’s because developers couldn’t find a way to build them without hurting poor people, local communities, or birds and stuff.
This is called politics and it’s powerful. The most effective anti-housebuilding organisation in the UK doesn’t call itself Pause Housebuilding. It calls itself the Campaign to Protect Rural England, because English people love rural England. CPRE campaigns in the 1940s helped shape England’s planning system. As a result, permission to build houses is only granted when it’s in the “public interest”; in practice it is given infrequently and often with onerous conditions.[1]
The AI pause folks could learn from their success. Instead of campaigning for a total halt to AI development, they could push for strict regulations that aim to ensure new AI systems won’t harm people (or birds and stuff).
This approach has two advantages. First, it’s more politically palatable than a heavy-handed pause. And second, it’s closer to what those of us concerned about AI safety ideally want: not an end to progress, but progress that is safe and advances human flourishing.
I think NIMBYs happen to be wrong about the cost-benefit calculation of strong regulation. But AI safety people are right. Advanced AI systems pose grave threats and we don’t know how to mitigate them.
Maybe ask governments for an equivalent system for new AI models. Require companies to prove to planners their models are safe. Ask for:
- Independent safety audits
- Ethics reviews
- Economic analyses
- Public reports on risk analysis and mitigation measures
- Compensation mechanisms for people whose livelihoods are disrupted by automation
- And a bunch of other measures that plausibly limit the AI risks
In practice, these requirements might be hard to meet. But, considering the potential harms and meaningful chance something goes wrong, they should be. If a company developing an unprecedentedly large AI model with surprising capabilities can’t prove it’s safe, they shouldn’t release it.
This is not about pausing AI.
I don’t know anybody who thinks AI systems have zero upside. In fact, the same people worried about the risks are often excited about the potential for advanced AI systems to solve thorny coordination problems, liberate billions from mindless toil, achieve wonderful breakthroughs in medicine, and generally advance human flourishing.
But they’d like companies to prove their systems are safe before they release them into the world, or even train them at all. To prove that they’re not going to cause harm by, for example, hurting people, disrupting democratic institutions, or wresting control of important sociopolitical decisions from human hands.
Who can argue with that?
[Edit: Peter McIntyre has pointed out that Ezra Klein made a version of this argument on the 80K podcast. So I've been scooped - but at least I'm in good company!]
- ^
“Joshua Carson, head of policy at the consultancy Blackstock, said: “The notion of developers ‘sitting on planning permissions’ has been taken out of context. It takes a considerable length of time to agree the provision of new infrastructure on strategic sites for housing and extensive negotiation with councils to discharge planning conditions before homes can be built.”” (Kollewe 2021)
If I could give this post 20 upvotes I would.
Being relatively new to the EA community, this for me is the single biggest area of opportunity to make the community more impactful.
Communication within the EA community (and within the AI Safety community) is wonderful, clear, crisp, logical, calm, proportional. If only the rest of the world could communicate like that, how many problems we'd solve.
But unfortunately, many, maybe even most people, react to ideas emotionally, their gut reaction outweighing or even preventing any calm, logical analysis.
And it feels like a lot of people see EA's as "cold and calculating" because of the way we communicate - with numbers and facts and rationale.
There is a whole science of communication (in which I'm far from an expert) which looks at how to make your message stick, how to use storytelling to build on humans' natural desire to hear stories, how to use emotion-laden words and images instead of numbers, and so on.
For example: thousands of articles were written about the tragic and perilous way migrants would try to cross the Mediterranean to get to Europe. We all knew the facts. But few people acted. Then one photograph of a small boy who washed up dead on the beach almost single-handedly engaged millions of people to realise that this was inhumane, that we can't let this go on. (in the end, it's still going on). The photo was horrible and tragic, but was one of thousands of similar tragedies - yet this photo did more than all the numbers.
We could ask ourselves what kind of images might represent the dangers of AI in a similar emotional way. In 2001 A Space Odyssey, Stanley Kubrick achieved something like this. He captured the human experience of utter impotence to do anything against a very powerful AI. It was just one person, but we empathised with that person, just like we empathised with the tragic boy or with his parents and family.
What you're describing is how others have used this form of communication - very likely fine-tuned in focus groups - to find out how to make their message as impactful as possible, as emotional as possible.
EA's need to learn how to do this more. We need to separate the calm, logical discussion about what is the best course of action from the challenge of making our communication effective in bringing that about. There are some groups who do this quite well, but we are still amateurs compared to the (often bad guys) pushing alternative viewpoints using sophisticated psychology and analysis to fine-tune their messaging.
(full disclosure: this is part of what I'm studying for the project I'm doing for the BlueDot AI Safety course)