John Bridge

156London, UKJoined Oct 2021


Pronouns: he/him

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Contact me at: johnmichaelbridge[at]gmail[dot]com

Epistemic status: Uncertain and speculative. I try not to caveat my claims too much because it makes everything harder to read. If I've worded something too strongly, feel free to ask for clarification.


Towards a Worldwide, Wateright Windfall Clause


NB: One reason this might be tractable is that lots of non-EA folks are working on data protection already, and we could leverage their expertise.

Focusing more on data governance:

GovAI now has a full-time researcher working on compute governance. Chinchilla's Wild Implications suggests that access to data might also be a crucial leverage point for AI development. However, from what I can tell, there are no EAs working full time on how data protection regulations might help slow or direct AI progress. This seems like a pretty big gap in the field.

What's going on here? I can see two possible answers:

  • Folks have suggested that compute is relatively to govern (eg). Someone might have looked into this and decided data is just too hard to control, and we're better off putting our time into compute.
  • Someone might already be working on this that I just haven't heard of.

If anyone has an answer to this I'd love to know!

No Plans for Misaligned AI:

This talk by Jade Leung got me thinking - I've never seen a plan for what we do if AGI turns out misaligned. 

The default assumption seems to be something like "well, there's no point planning for that, because we'll all be powerless and screwed". This seems mistaken to me. It's not clear that we'll be so powerless that we have absolutely no ability to encourage a trajectory change, particularly in a slow takeoff scenario. Given that most people weight alleviating suffering higher than promoting pleasure, this is especially valuable work in expectation as it might help us change outcomes from 'very, very bad world' to 'slightly negative' world. This also seems pretty tractable - I'd expect ~10hrs thinking about this could help us come up with a very barebones playbook.

Why isn't this being done? I think there are a few reasons:

  • Like suffering focused ethics, it's depressing.
  • It seems particularly speculative - most of the 'humanity becomes disempowered by AGI' scenarios look pretty sci-fi. So serious academics don't want to consider it.
  • People assume, mistakenly IMO, that we're just totally screwed if AI is misaligned.

Longtermist legal work seems particularly susceptible to the Cannonball Problem, for a few reasons:

  • Changes to hard law are difficult to reverse - legislatures rarely consider issues more than a couple times every ten years, and the judiciary takes even longer. 
  • At the same time, legal measures which once looked good can quickly become ineffectual due to shifts in underlying political, social or economic circumstances. 
  • Taken together, this means that bad laws have a long time to do a lot of harm, so we need to be careful when putting new rules on the books.
  • This is worsened by the fact that we don’t know what ideal longtermist governance looks like. In a world of transformative AI, it’s hard to tell if the rule of law will mean very much at all. If sovereign states aren’t powerful enough to act as leviathans, it’s hard to see why influential actors wouldn’t just revert to power politics.

Underlying all of this are huge, unanswered questions in political philosophy about where we want to end up. A lack of knowledge about our final destination makes it harder to come up with ways to get there.

I think this goes some way to explaining why longtermist lawyers only have a few concrete policy asks right now despite admirable efforts from LPP, GovAI and others.

The Cannonball Problem:

Doing longtermist AI policy work feels a little like aiming heavy artillery with a blindfold on. We can’t see our target, we’ve no idea how hard to push the barrel in any one direction, we don't know how long the fuse is, we can’t stop the cannonball once it’s in motion, and we could do some serious damage if we get things wrong.

Taking each of your points in turn:

  1. Okay. Thanks for clarifying that for me - I think we agree more than I expected, because I'm pretty in favour of their institutional design work.
  2. I think you're right that we have a disagreement w/r/t scope and implications, but it's not clear to me to what extent this is also just a difference in 'vibe' which might dissolve if we discussed specific implications. In any case, I'll take a look at that paper.

I have a couple thoughts on this.

First - if you're talking about nearer-term questions, like 'What's the right governance structure for a contemporary AI developer to ensure its board acts in the common interest?' or 'How can we help workers reskill after being displaced from the transport industry' then I agree that doesn't seem too strange. However, I don't see how this would differ from the work that folks at places LPP and Gov.AI are doing already.

Second - if you're talking about longer-term ideal governance questions, I  reckon even relatively mundane topics are likely to seem pretty weird when studied in a longtermist context, because the bottom line for researchers will be how contemporary governance affects future generations. 

To use your example of the future of work, an important question in that topic might be whether and when we should attribute legal personhood to digital labourers, with the bottom line concerning the effect of any such policy on the moral expansiveness of future societies. The very act of supposing that digital workers as smart as humans will one day exist is relatively weird, let alone considering their legal status, let further alone discussing the potential ethics of a digital civilisation. 

This is of course a single, cherry-picked example, but I think that most papers justifying specific positive visions of the future will need to consider the impact of these intermediate positive worlds on the longterm future, which will appear weird and uncomfortably utopian. Meanwhile, I suspect that work with a negative focus ('How can we prevent an arms race with China?') or a more limited scope ('How can we use data protection regulations to prevent bad actors from accessing sensitive datasets?') doesn't require this sort of abstract speculation, suggesting that research into ideal AI governance carries reputational hazards that others forms of safety/governance work do not. I'm particularly concerned that this will open up AI governance to more hit-pieces of this variety, turning off potential collaborators whose first interaction with longtermism is bad faith critique. 

Thanks for this Rory, I'm excited to see what else you have to say on this topic.

One thing I think this post is missing is a more detailed response to the 'ideal governance as weird' criticism. You write that 'weird ideal governance theories may well be ineffective', but I would suggest that almost all fleshed-out theories of ideal AI governance will be inescapably weird, because most plausible post-trasformative AI worlds are deeply unfamiliar by nature.

A good intuition pump for this is to consider how weird modern Western society would seem to people from 1,000 years ago. We currently live in secular market-based democratic states run by a multiracial, multigender coalition of individuals whose primary form of communication is the instantaneous exchange of text via glowing, beeping machines. If you went back in time and tried to explain this world to an inhabitant of a mediaeval European theocratic monarchy, even to a member of the educated elite, they would be utterly baffled. How could society maintain order if the head of state was not blue-blooded and divinely ordained? How could peasants (particularly female ones) even learn to read and write, let alone effectively perform intellectual jobs? How could a society so dependent on usury avoid punishment by God in the form of floods, plagues or famines?

Even on the most conservative assumptions about AI capabilities, we can expect advanced AI to transform society at least as much as it has changed in the last 1,000 years. At a minimum, it promises to eliminate most productive employment, significantly extend our lifetimes, allow us to intricately surveil each and every member of society, and to drastically increase the material resources available to each person. A world with these four changes alone seems radically different and unfamiliar to our own, meaning any theory about its governance is going to seem weird. Throw in ideas like digital people and space colonisation and you're jumping right off the weirdness deep end.

Of course, weirdness isn't per se a reason not to go ahead with investigation into this topic, but I think the Wildeford post you cited is on the right track when it comes to weirdness points. AI Safety and Governance already struggles for respectability, so if you're advocating for more EA resources to be dedicated to the area I think you need to give a more thorough justification for why it won't discredit the field.

Also strong upvote. I think nearly 100% of the leftist critiques of EA I've seen are pretty crappy, but I also think it's relatively fertile ground. 

For example, I suspect (with low confidence) that there is a community blindspot when it comes to the impact of racial dynamics on the tractability of different interventions, particularly in animal rights and global health.[1] I expect that this is driven by a combination of wanting to avoid controversy, a focus on easily quantifiable issues, the fact that few members of the community have a sociology or anthropology background, and (rightly) recognising that every issue can't just be boiled down to racism.

  1. ^

    See, for eg, my comment here.

I'm a bit late to the party on this one, but I'd be interested to find out how differential treatment of indigenous groups in countries where snakebites are most prevalent impacts the tractability of any interventions. I don't have any strong opinions about how significant this issue is, but I would tentatively suggest that a basket of 'ethnic inequality issues' should be considered a third 'prong' in the analysis of why snakebites kill and maim so many people, and could substantially impact our cost-effectiveness estimates.


The WHO report linked by OP notes that, in many communities, over 3/4 of snakebite victims choose traditional medicine or spiritual healers instead of hospital treatment. I don't think this is a result of either of the two big issues that the OP identifies - it doesn't seem to stem from difficulty with diagnosis or cost of treatment, so much as being a thorny problem resulting from structural ethnic inequalities in developing countries.

I'm most familiar with the healthcare context of Amazonian nations, where deeply embedded beliefs around traditional medicine and general suspicion of mestizo-run governments can make it more difficult to administer healthcare to indigenous rainforest communities, low indigenous voter turnout reduces the incentives of elected officials to do anything about poor health outcomes, and discriminatory attitudes towards indigenous people can make health crises appear less salient to decisionmakers. Given that indigenous groups in developing countries almost universally receive worse healthcare treatment, and given that much indigenous land is in regions with high vulnerability to snake envenoming,[1] I wouldn't be surprised if this issue generalised outside of Amazonia.

Depending on the size of the effect here, this could considerably impact assessments of tractability. For example, if developing country governments won't pay for the interventions, it might be difficult to fund long-term antivenom distribution networks. Alternatively, if indigenous groups don't trust radio communications, communicating health interventions could be particularly difficult. Also, given the fact that 'indigenous' is a poorly-defined term which refers to a host of totally unrelated peoples, it might be difficult to generalise or scale community interventions.


  1. ^

    Study here (which I've not read).

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