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Nathan_Barnard
Karma: 866
This is really useful context!
This looks fantastic, thanks for putting it together!
Thanks for your comment Ceb.
I think my case for more focus on good statistical work when looking at governance is that when doing good statistical work on interventions, we often find very high degrees of variation in effect sizes that are enough to justify the extra work of the intervention. I’m personally very unsure of the effect size of changes in liability law, soft law, and various corporate governance interventions on accident rates.
There’s been lots of great case study/best guess/expert consensus work on these questions which I think is often great and I’m very happy exists, but leaves me with large uncertainties about effect sizes, and so on the current margin, I want more good statistical work.
I think the case for good statistical work on areas like degree of misuse risk and forecasting is stronger because I think that people’s takes on these questions are pretty grounded in quite theoretical arguments (unlike governance interventions which are much more empirically grounded) that I think would benefit a lot from more grounded statistical work.
AI governance and strategy: a list of research agendas and work that could be done.
Article on the impact of new(ish) cystic fibrosis treatment
The Defence production act and AI policy
Thanks for writing this Charlie, this was great
This is great Matt! I think I’d be also be interested in work trying to estimate the effect sizes of this stuff, as well as research on optimal design.
China-AI forecasting
I think this is pretty cool
Examples of governments doing good in house (or contracted) technical research
Strongly there should be more explicit defences of this argument.
One way of doing this in a co-operative way might working on co-operative AI stuff, since it seems to increase the likelihood that misaligned AI goes well, or at least less badly.
Standard policy frameworks for AI governance
Yeah, I think a Bayesian perspective is really helpful here and this reply seems right.
Some heuristics I use for deciding how much I trust scientific results
I think overrated-underrated is useful because it’s trying to say whether we should be doing more or less of X on the margin. Often it’s much more useful to know whether something is good on the current margin rather than on average.
There isn’t only one notion of utility—utility in decision theory is different to utility in ethics. Utility in decision theory can indeed be derived from choices over lotteries and is incomparable between individuals (without further assumptions) and is equivalent under positive affine transformation because it’s just representing choices.
Utility in moral philosophy refers to value and typically refers to the value of experiences (as opposed to other conceptions of the good like satisfaction of preferences), is comparable between individuals without further assumptions and isn’t equivalent under positive affine transformation.
An individual’s utility (on either of the definitions) may or may not be changed by the political process.
Consider a new far-right party entering the political sphere. They successfully changed political conversations to be more anti-immigration and have lots of focus on immigrant men committing sexual violence.
A voter exposed to these new political conversations has their choice behaviour changed because they now feel more angry towards immigrants and want to hurt them, rather than because they think that more restrictive immigration policies would make them personally safer, for instance.
This same voter also has utility—in the moral philosophy sense—changed by the new political conversation. Now they feel sadistic pleasure when they hear about immigrants being deported on the news, leading to better subjective experiences when they see immigrants being deported.
I strongly reject the claim that we should imagine voters as exclusively deciding how to vote in terms of the personal benefits they derive in expectation from policies. I think people support capital punishment mostly because it fits with their inbuilt sense of justice rather than because they think it benefits them.
We could (probably) represent this voter as being an expected utility maximiser where they have positive utility from capital punishment, in the decision theory sense. This is a different claim from the claim that a voter expects their subjective experiences to be more positively valenced when there’s capital punishment.
I’m afraid I can’t comment on what ignorance factors do or do not account for under Bayesian regret without rereading the paper, but it’s of course possible that they do account for that disparity between actual and assumed preferences.
My views here are just deferring to gender scholars I respect.
Based
I essentially agree with the basic point of this post—and think it was a great post!
I have some what feel like nitpicks about the specific story that you told that and I’m sort of confused about how much they matter. My guess is that this actually is a counterargument to the point being made in the post and imply that trapped priors are less of a problem than the example used in the post would imply.
I think that the broadly libertarian view and Scandinavian-style social democracy views are much more similar than this post gives them credit for. In particular, they agree on the crucial importance of liberal democracy that prevents elites (in the 19th-century traditional agricultural elites) from using the state to engage in rent-seeking. I remember reading a list of demands of the German Social Democratic party in the 1870s (before it had moderated) that read a list of liberal democratic demands—secret ballot, free speech, expansion of the power of democratically elected Reichstag etc. These two strands of modern liberal thought also agreed on a liberal epistemology that should be used to try to systematically improve society from a broadly utilitarian perspective—the London School of Economics was founded by 4 Fabian Society members to further this aim!
I think this cashes out in the Effective Samaritans and the Libertarian side of EA (although the Libertains side of EA is pretty unusually libertarian) pursuing pretty similar projects when trying to use non-randomista means for development. For instance, my guess is that both would support increasing state capacity in low-income countries to improve the basic nightwatchman functions of the state, reducing corruption, protecting liberties and the integrity of elections, and removing regulation that that represent elite rent-seeking. Of course they’ll be some differences in emphasis—the Effective Samarations might have a particular theory of change around using unions to coordinate labour to push for political change—but these seem relatively minor compared to the core things both agree are important. Byran Caplan and Robin Hanson are genuinely unusually libertarian even amongst broadly free-market economists, but typically both utilitarian-motivated libertarians and social democrats would be interested in building at least a basic welfare state in low-income countries.
I think we actually in practice see this convergence between liberal social democrats and broadly utilitarian libertarians in the broadly unified policy agendas of Ezra Klien’s abundance agenda and lots of EA-Rationalist adjacent Libertarians like a focus on making it easier to build houses in highly productive cities, reducing barrier to immigration to rich countries, increased public funding of R&D and improving state capacity, particularly around extremely ambitious projects like operation warp speed.