I think some of the AI safety policy community has over-indexed on the visual model of the “Overton Window” and under-indexed on alternatives like the “ratchet effect,” “poisoning the well,” “clown attacks,” and other models where proposing radical changes can make you, your allies, and your ideas look unreasonable (edit to add: whereas successfully proposing minor changes achieves hard-to-reverse progress, making ideal policy look more reasonable).
I’m not familiar with a lot of systematic empirical evidence on either side, but it seems to me like the more effective actors in the DC establishment overall are much more in the habit of looking for small wins that are both good in themselves and shrink the size of the ask for their ideal policy than of pushing for their ideal vision and then making concessions. Possibly an ideal ecosystem has both strategies, but it seems possible that at least some versions of “Overton Window-moving” strategies executed in practice have larger negative effects via associating their “side” with unreasonable-sounding ideas in the minds of very bandwidth-constrained policymakers, who strongly lean on signals of credibility and consensus when quickly evaluating policy options, than the positive effects of increasing the odds of ideal policy and improving the framing for non-ideal but pretty good policies.
In theory, the Overton Window model is just a description of what ideas are taken seriously, so it can indeed accommodate backfire effects where you argue for an idea “outside the window” and this actually makes the window narrower. But I think the visual imagery of “windows” actually struggles to accommodate this—when was the last time you tried to open a window and accidentally closed it instead? -- and as a result, people who rely on this model are more likely to underrate these kinds of consequences.
Would be interested in empirical evidence on this question (ideally actual studies from psych, political science, sociology, econ, etc literatures, rather than specific case studies due to reference class tennis type issues).
These are plausible concerns, but I don’t think they match what I see as a longtime DC person.
We know that the legislative branch is less productive in the US than it has been in any modern period, and fewer bills get passed (many different metrics for this, but one is https://www.reuters.com/graphics/USA-CONGRESS/PRODUCTIVITY/egpbabmkwvq/) . Those bills that do get passed tend to be bigger swings as a result—either a) transformative legislation (e.g., Obamacare, Trump tax cuts and COVID super-relief, Biden Inflation Reduction Act and CHIPS) or b) big omnibus “must-pass” bills like FAA reauthorization, into which many small proposals get added in.
I also disagree with the claim that policymakers focus on credibility and consensus generally, except perhaps in the executive branch to some degree. (You want many executive actions to be noncontroversial “faithfully executing the laws” stuff, but I don’t see that as “policymaking” in the sense you describe it.)
In either of those, it seems like the current legislative “meta” favors bigger policy asks, not small wins, and I’m having trouble of thinking of anyone I know who’s impactful in DC who has adopted the opposite strategy. What are examples of the small wins that you’re thinking of as being the current meta?
Agree with lots of this– a few misc thoughts [hastily written]:
I think the Overton Window frame ends up getting people to focus too much on the dimension “how radical is my ask”– in practice, things are usually much more complicated than this. In my opinion, a preferable frame is something like “who is my target audience and what might they find helpful.” If you’re talking to someone who makes it clear that they will not support X, it’s silly to keep on talking about X. But I think the “target audience first” approach ends up helping people reason in a more sophisticated way about what kinds of ideas are worth bringing up. As an example, in my experience so far, many policymakers are curious to learn more about intelligence explosion scenarios and misalignment scenarios (the more “radical” and “speculative” threat models).
I don’t think it’s clear that the more effective actors in DC tend to be those who look for small wins. Outside of the AIS community, there sure do seem to be a lot of successful organizations that take hard-line positions and (presumably) get a lot of their power/influence from the ideological purity that they possess & communicate. Whether or not these organizations end up having more or less influence than the more “centrist” groups is, in my view, not a settled question & probably varies a lot by domain. In AI safety in particular, I think my main claim is something like “pretty much no group– whether radical or centrist– has had tangible wins. When I look at the small set of tangible wins, it seems like the groups involved were across the spectrum of “reasonableness.”
The more I interact with policymakers, the more I’m updating toward something like “poisoning the well doesn’t come from having radical beliefs– poisoning the well comes from lamer things like being dumb or uninformed, wasting peoples’ time, not understanding how the political process works, not having tangible things you want someone to do, explaining ideas poorly, being rude or disrespectful, etc.” I’ve asked ~20-40 policymakers (outside of the AIS bubble) things like “what sorts of things annoy you about meetings” or “what tends to make meetings feel like a waste of your time”, and no one ever says “people come in with ideas that are too radical.” The closest thing I’ve heard is people saying that they dislike it when groups fail to understand why things aren’t able to happen (like, someone comes in thinking their idea is great, but then they fail to understand that their idea needs approval from committee A and appropriations person B and then they’re upset about why things are moving slowly). It seems to me like many policy folks (especially staffers and exec branch subject experts) are genuinely interested in learning more about the beliefs and worldviews that have been prematurely labeled as “radical” or “unreasonable” (or perhaps such labels were appropriate before chatGPT but no longer are).
A reminder that those who are opposed to regulation have strong incentives to make it seem like basically-any-regulation is radical/unreasonable. An extremely common tactic is for industry and its allies to make common-sense regulation seem radical/crazy/authoritarian & argue that actually the people proposing strong policies are just making everyone look bad & argue that actually we should all rally behind [insert thing that isn’t a real policy.] (I admit this argument is a bit general, and indeed I’ve made it before, so I won’t harp on it here. Also I don’t think this is what Trevor is doing– it is indeed possible to raise serious discussions about “poisoning the well” even if one believes that the cultural and economic incentives disproportionately elevate such points).
In the context of AI safety, it seems to me like the most high-influence Overton Window moves have been positive– and in fact I would go as far as to say strongly positive. Examples that come to mind include the CAIS statement, FLI pause letter, Hinton leaving Google, Bengio’s writings/speeches about rogue AI & loss of control, Ian Hogarth’s piece about the race to god-like AI, and even Yudkowsky’s TIME article.
I think some of our judgments here depend on underlying threat models and an underlying sense of optimism vs. pessimism. If one things that labs making voluntary agreements/promises and NIST contributing to the development of voluntary standards are quite excellent ways to reduce AI risk, then the groups that have helped make this happen deserve a lot of credit. If one thinks that much more is needed to meaningfully reduce xrisk, then the groups that are raising awareness about the nature of the problem, making high-quality arguments about threat models, and advocating for stronger policies deserve a lot of credit.
I agree that more research on this could be useful. But I think it would be most valuable to focus less on “is X in the Overton Window” and more on “is X written/explained well and does it seem to have clear implications for the target stakeholders?”
Re: how over-emphasis on “how radical is my ask” vs “what my target audience might find helpful” and generally the importance of making your case well regardless of how radical it is, that makes sense. Though notably the more radical your proposal is (or more unfamiliar your threat models are), the higher the bar for explaining it well, so these do seem related.
Re: more effective actors looking for small wins, I agree that it’s not clear, but yeah, seems like we are likely to get into some reference class tennis here. “A lot of successful organizations that take hard-line positions and (presumably) get a lot of their power/influence from the ideological purity that they possess & communicate”? Maybe, but I think of like, the agriculture lobby, who just sort of quietly make friends with everybody and keep getting 11-figure subsidies every year, in a way that (I think) resulted more from gradual ratcheting than making a huge ask. “Pretty much no group– whether radical or centrist– has had tangible wins” seems wrong in light of the EU AI Act (where I think both a “radical” FLI and a bunch of non-radical orgs were probably important) and the US executive order (I’m not sure which strategy is best credited there, but I think most people would have counted the policies contained within it as “minor asks” relative to licensing, pausing, etc). But yeah I agree that there are groups along the whole spectrum that probably deserve credit.
Re: poisoning the well, again, radical-ness and being dumb/uninformed are of course separable but the bar rises the more radical you get, in part because more radical policy asks strongly correlate with more complicated procedural asks; tweaking ECRA is both non-radical and procedurally simple, creating a new agency to license training runs is both outside the DC Overton Window and very procedurally complicated.
Re: incentives, I agree that this is a good thing to track, but like, “people who oppose X are incentivized to downplay the reasons to do X” is just a fully general counterargument. Unless you’re talking about financial conflicts of interest, but there are also financial incentives for orgs pursuing a “radical” strategy to downplay boring real-world constraints, as well as social incentives (e.g. on LessWrong IMO) to downplay boring these constraints and cognitive biases against thinking your preferred strategy has big downsides.
I agree that the CAIS statement, Hinton leaving Google, and Bengio and Hogarth’s writing have been great. I think that these are all in a highly distinct category from proposing specific actors take specific radical actions (unless I’m misremembering the Hogarth piece). Yudkowsky’s TIME article, on the other hand, definitely counts as an Overton Window move, and I’m surprised that you think this has had net positive effects. I regularly hear “bombing datacenters” as an example of a clearly extreme policy idea, sometimes in a context that sounds like it maybe made the less-radical idea seem more reasonable, but sometimes as evidence that the “doomers” want to do crazy things and we shouldn’t listen to them, and often as evidence that they are at least socially clumsy, don’t understand how politics works, etc, which is related to the things you list as the stuff that actually poisons the well. (I’m confused about the sign of the FLI letter as we’ve discussed.)
I’m not sure optimism vs pessimism is a crux, except in very short, like, 3-year timelines. It’s true that optimists are more likely to value small wins, so I guess narrowly I agree that a ratchet strategy looks strictly better for optimists, but if you think big radical changes are needed, the question remains of whether you’re more likely to get there via asking for the radical change now or looking for smaller wins to build on over time. If there simply isn’t time to build on these wins, then yes, better to take a 2% shot at the policy that you actually think will work; but even in 5-year timelines I think you’re better positioned to get what you ultimately want by 2029 if you get a little bit of what you want in 2024 and 2026 (ideally while other groups also make clear cases for the threat models and develop the policy asks, etc.). Another piece this overlooks is the information and infrastructure built by the minor policy changes. A big part of the argument for the reporting requirements in the EO was that there is now going to be an office in the US government that is in the business of collecting critical information about frontier AI models and figuring out how to synthesize it to the rest of government, that has the legal authority to do this, and both the office and the legal authority can now be expanded rather than created, and there will now be lots of individuals who are experienced in dealing with this information in the government context, and it will seem natural that the government should know this information. I think if we had only been developing and advocating for ideal policy, this would not have happened (though I imagine that this is not in fact what you’re suggesting the community do!).
Unless you’re talking about financial conflicts of interest, but there are also financial incentives for orgs pursuing a “radical” strategy to downplay boring real-world constraints, as well as social incentives (e.g. on LessWrong IMO) to downplay boring these constraints and cognitive biases against thinking your preferred strategy has big downsides.
It’s not just that problem though, they will likely be biased to think that their policy is helpful for safety of AI at all, and this is a point that sometimes gets forgotten.
But correct on the fact that Akash’s argument is fully general.
Ingroup losing status? Few things are more prone to distorted perception than that.
And I think this makes sense (e.g. Simler’s Social Status: Down the Rabbit Hole which you’ve probably read), if you define “AI Safety” as “people who think that superintelligence is serious business or will be some day”.
The psych dynamic that I find helpful to point out here is Yud’s Is That Your True Rejection post from ~16 years ago. A person who hears about superintelligence for the first time will often respond to their double-take at the concept by spamming random justifications for why that’s not a problem (which, notably, feels like legitimate reasoning to that person, even though it’s not). An AI-safety-minded person becomes wary of being effectively attacked by high-status people immediately turning into what is basically a weaponized justification machine, and develops a deep drive wanting that not to happen. Then justifications ensue for wanting that to happen less frequently in the world, because deep down humans really don’t want their social status to be put at risk (via denunciation) on a regular basis like that. These sorts of deep drives are pretty opaque to us humans but their real world consequences are very strong.
Something that seems more helpful than playing whack-a-mole whenever this issue comes up is having more people in AI policy putting more time into improving perspective. I don’t see shorter paths to increasing the number of people-prepared-to-handle-unexpected-complexity than giving people a broader and more general thinking capacity for thoughtfully reacting to the sorts of complex curveballs that you get in the real world. Rationalist fiction like HPMOR is great for this, as well as others e.g. Three Worlds Collide, Unsong, Worth the Candle, Worm (list of top rated ones here). With the caveat, of course, that doing well in the real world is less like the bite-sized easy-to-understand events in ratfic, and more like spotting errors in the methodology section of a study or making money playing poker.
I think, given the circumstances, it’s plausibly very valuable e.g. for people already spending much of their free time on social media or watching stuff like The Office, Garfield reruns, WWI and Cold War documentaries, etc, to only spend ~90% as much time doing that and refocusing ~10% to ratfic instead, and maybe see if they can find it in themselves to want to shift more of their leisure time to that sort of passive/ambient/automatic self-improvement productivity.
I’m not a decel, but the way this stuff often is resolved is that there are crazy people that aren’t taken seriously by the managerial class but that are very loud and make obnoxious asks. Think the evangelicals against abortion or the Columbia protestors.
Then there is some elite, part of the managerial class, that makes reasonable policy claims. For Abortion, this is Mitch McConnel, being disciplined over a long period of time in choosing the correct judges. For Palestine, this is Blinken and his State Department bureaucracy.
The problem with decels is that theoretically they are part of the managerial class themselves. Or at least, they act like they are. They call themselves rationalists, read Eliezer and Scott Alexander, and what not. But the problem is that it’s very hard for an uninterested third party to take seriously these Overton Window bogous claims from people that were supposed to be measured, part of the managerial class.
You need to split. There are the crazy ones that people don’t take seriously, but will move the managerial class. And there are the serious people that EA Money will send to D.C. to work at Blumenthal’s office. This person needs to make small policy requests that will sabotage IA, without looking so. And slowly, you get policy wins and you can sabotage the whole effort.
I think some of the AI safety policy community has over-indexed on the visual model of the “Overton Window” and under-indexed on alternatives like the “ratchet effect,” “poisoning the well,” “clown attacks,” and other models where proposing radical changes can make you, your allies, and your ideas look unreasonable (edit to add: whereas successfully proposing minor changes achieves hard-to-reverse progress, making ideal policy look more reasonable).
I’m not familiar with a lot of systematic empirical evidence on either side, but it seems to me like the more effective actors in the DC establishment overall are much more in the habit of looking for small wins that are both good in themselves and shrink the size of the ask for their ideal policy than of pushing for their ideal vision and then making concessions. Possibly an ideal ecosystem has both strategies, but it seems possible that at least some versions of “Overton Window-moving” strategies executed in practice have larger negative effects via associating their “side” with unreasonable-sounding ideas in the minds of very bandwidth-constrained policymakers, who strongly lean on signals of credibility and consensus when quickly evaluating policy options, than the positive effects of increasing the odds of ideal policy and improving the framing for non-ideal but pretty good policies.
In theory, the Overton Window model is just a description of what ideas are taken seriously, so it can indeed accommodate backfire effects where you argue for an idea “outside the window” and this actually makes the window narrower. But I think the visual imagery of “windows” actually struggles to accommodate this—when was the last time you tried to open a window and accidentally closed it instead? -- and as a result, people who rely on this model are more likely to underrate these kinds of consequences.
Would be interested in empirical evidence on this question (ideally actual studies from psych, political science, sociology, econ, etc literatures, rather than specific case studies due to reference class tennis type issues).
These are plausible concerns, but I don’t think they match what I see as a longtime DC person.
We know that the legislative branch is less productive in the US than it has been in any modern period, and fewer bills get passed (many different metrics for this, but one is https://www.reuters.com/graphics/USA-CONGRESS/PRODUCTIVITY/egpbabmkwvq/) . Those bills that do get passed tend to be bigger swings as a result—either a) transformative legislation (e.g., Obamacare, Trump tax cuts and COVID super-relief, Biden Inflation Reduction Act and CHIPS) or b) big omnibus “must-pass” bills like FAA reauthorization, into which many small proposals get added in.
I also disagree with the claim that policymakers focus on credibility and consensus generally, except perhaps in the executive branch to some degree. (You want many executive actions to be noncontroversial “faithfully executing the laws” stuff, but I don’t see that as “policymaking” in the sense you describe it.)
In either of those, it seems like the current legislative “meta” favors bigger policy asks, not small wins, and I’m having trouble of thinking of anyone I know who’s impactful in DC who has adopted the opposite strategy. What are examples of the small wins that you’re thinking of as being the current meta?
Agree with lots of this– a few misc thoughts [hastily written]:
I think the Overton Window frame ends up getting people to focus too much on the dimension “how radical is my ask”– in practice, things are usually much more complicated than this. In my opinion, a preferable frame is something like “who is my target audience and what might they find helpful.” If you’re talking to someone who makes it clear that they will not support X, it’s silly to keep on talking about X. But I think the “target audience first” approach ends up helping people reason in a more sophisticated way about what kinds of ideas are worth bringing up. As an example, in my experience so far, many policymakers are curious to learn more about intelligence explosion scenarios and misalignment scenarios (the more “radical” and “speculative” threat models).
I don’t think it’s clear that the more effective actors in DC tend to be those who look for small wins. Outside of the AIS community, there sure do seem to be a lot of successful organizations that take hard-line positions and (presumably) get a lot of their power/influence from the ideological purity that they possess & communicate. Whether or not these organizations end up having more or less influence than the more “centrist” groups is, in my view, not a settled question & probably varies a lot by domain. In AI safety in particular, I think my main claim is something like “pretty much no group– whether radical or centrist– has had tangible wins. When I look at the small set of tangible wins, it seems like the groups involved were across the spectrum of “reasonableness.”
The more I interact with policymakers, the more I’m updating toward something like “poisoning the well doesn’t come from having radical beliefs– poisoning the well comes from lamer things like being dumb or uninformed, wasting peoples’ time, not understanding how the political process works, not having tangible things you want someone to do, explaining ideas poorly, being rude or disrespectful, etc.” I’ve asked ~20-40 policymakers (outside of the AIS bubble) things like “what sorts of things annoy you about meetings” or “what tends to make meetings feel like a waste of your time”, and no one ever says “people come in with ideas that are too radical.” The closest thing I’ve heard is people saying that they dislike it when groups fail to understand why things aren’t able to happen (like, someone comes in thinking their idea is great, but then they fail to understand that their idea needs approval from committee A and appropriations person B and then they’re upset about why things are moving slowly). It seems to me like many policy folks (especially staffers and exec branch subject experts) are genuinely interested in learning more about the beliefs and worldviews that have been prematurely labeled as “radical” or “unreasonable” (or perhaps such labels were appropriate before chatGPT but no longer are).
A reminder that those who are opposed to regulation have strong incentives to make it seem like basically-any-regulation is radical/unreasonable. An extremely common tactic is for industry and its allies to make common-sense regulation seem radical/crazy/authoritarian & argue that actually the people proposing strong policies are just making everyone look bad & argue that actually we should all rally behind [insert thing that isn’t a real policy.] (I admit this argument is a bit general, and indeed I’ve made it before, so I won’t harp on it here. Also I don’t think this is what Trevor is doing– it is indeed possible to raise serious discussions about “poisoning the well” even if one believes that the cultural and economic incentives disproportionately elevate such points).
In the context of AI safety, it seems to me like the most high-influence Overton Window moves have been positive– and in fact I would go as far as to say strongly positive. Examples that come to mind include the CAIS statement, FLI pause letter, Hinton leaving Google, Bengio’s writings/speeches about rogue AI & loss of control, Ian Hogarth’s piece about the race to god-like AI, and even Yudkowsky’s TIME article.
I think some of our judgments here depend on underlying threat models and an underlying sense of optimism vs. pessimism. If one things that labs making voluntary agreements/promises and NIST contributing to the development of voluntary standards are quite excellent ways to reduce AI risk, then the groups that have helped make this happen deserve a lot of credit. If one thinks that much more is needed to meaningfully reduce xrisk, then the groups that are raising awareness about the nature of the problem, making high-quality arguments about threat models, and advocating for stronger policies deserve a lot of credit.
I agree that more research on this could be useful. But I think it would be most valuable to focus less on “is X in the Overton Window” and more on “is X written/explained well and does it seem to have clear implications for the target stakeholders?”
Quick reactions:
Re: how over-emphasis on “how radical is my ask” vs “what my target audience might find helpful” and generally the importance of making your case well regardless of how radical it is, that makes sense. Though notably the more radical your proposal is (or more unfamiliar your threat models are), the higher the bar for explaining it well, so these do seem related.
Re: more effective actors looking for small wins, I agree that it’s not clear, but yeah, seems like we are likely to get into some reference class tennis here. “A lot of successful organizations that take hard-line positions and (presumably) get a lot of their power/influence from the ideological purity that they possess & communicate”? Maybe, but I think of like, the agriculture lobby, who just sort of quietly make friends with everybody and keep getting 11-figure subsidies every year, in a way that (I think) resulted more from gradual ratcheting than making a huge ask. “Pretty much no group– whether radical or centrist– has had tangible wins” seems wrong in light of the EU AI Act (where I think both a “radical” FLI and a bunch of non-radical orgs were probably important) and the US executive order (I’m not sure which strategy is best credited there, but I think most people would have counted the policies contained within it as “minor asks” relative to licensing, pausing, etc). But yeah I agree that there are groups along the whole spectrum that probably deserve credit.
Re: poisoning the well, again, radical-ness and being dumb/uninformed are of course separable but the bar rises the more radical you get, in part because more radical policy asks strongly correlate with more complicated procedural asks; tweaking ECRA is both non-radical and procedurally simple, creating a new agency to license training runs is both outside the DC Overton Window and very procedurally complicated.
Re: incentives, I agree that this is a good thing to track, but like, “people who oppose X are incentivized to downplay the reasons to do X” is just a fully general counterargument. Unless you’re talking about financial conflicts of interest, but there are also financial incentives for orgs pursuing a “radical” strategy to downplay boring real-world constraints, as well as social incentives (e.g. on LessWrong IMO) to downplay boring these constraints and cognitive biases against thinking your preferred strategy has big downsides.
I agree that the CAIS statement, Hinton leaving Google, and Bengio and Hogarth’s writing have been great. I think that these are all in a highly distinct category from proposing specific actors take specific radical actions (unless I’m misremembering the Hogarth piece). Yudkowsky’s TIME article, on the other hand, definitely counts as an Overton Window move, and I’m surprised that you think this has had net positive effects. I regularly hear “bombing datacenters” as an example of a clearly extreme policy idea, sometimes in a context that sounds like it maybe made the less-radical idea seem more reasonable, but sometimes as evidence that the “doomers” want to do crazy things and we shouldn’t listen to them, and often as evidence that they are at least socially clumsy, don’t understand how politics works, etc, which is related to the things you list as the stuff that actually poisons the well. (I’m confused about the sign of the FLI letter as we’ve discussed.)
I’m not sure optimism vs pessimism is a crux, except in very short, like, 3-year timelines. It’s true that optimists are more likely to value small wins, so I guess narrowly I agree that a ratchet strategy looks strictly better for optimists, but if you think big radical changes are needed, the question remains of whether you’re more likely to get there via asking for the radical change now or looking for smaller wins to build on over time. If there simply isn’t time to build on these wins, then yes, better to take a 2% shot at the policy that you actually think will work; but even in 5-year timelines I think you’re better positioned to get what you ultimately want by 2029 if you get a little bit of what you want in 2024 and 2026 (ideally while other groups also make clear cases for the threat models and develop the policy asks, etc.). Another piece this overlooks is the information and infrastructure built by the minor policy changes. A big part of the argument for the reporting requirements in the EO was that there is now going to be an office in the US government that is in the business of collecting critical information about frontier AI models and figuring out how to synthesize it to the rest of government, that has the legal authority to do this, and both the office and the legal authority can now be expanded rather than created, and there will now be lots of individuals who are experienced in dealing with this information in the government context, and it will seem natural that the government should know this information. I think if we had only been developing and advocating for ideal policy, this would not have happened (though I imagine that this is not in fact what you’re suggesting the community do!).
It’s not just that problem though, they will likely be biased to think that their policy is helpful for safety of AI at all, and this is a point that sometimes gets forgotten.
But correct on the fact that Akash’s argument is fully general.
Recently, John Wentworth wrote:
And I think this makes sense (e.g. Simler’s Social Status: Down the Rabbit Hole which you’ve probably read), if you define “AI Safety” as “people who think that superintelligence is serious business or will be some day”.
The psych dynamic that I find helpful to point out here is Yud’s Is That Your True Rejection post from ~16 years ago. A person who hears about superintelligence for the first time will often respond to their double-take at the concept by spamming random justifications for why that’s not a problem (which, notably, feels like legitimate reasoning to that person, even though it’s not). An AI-safety-minded person becomes wary of being effectively attacked by high-status people immediately turning into what is basically a weaponized justification machine, and develops a deep drive wanting that not to happen. Then justifications ensue for wanting that to happen less frequently in the world, because deep down humans really don’t want their social status to be put at risk (via denunciation) on a regular basis like that. These sorts of deep drives are pretty opaque to us humans but their real world consequences are very strong.
Something that seems more helpful than playing whack-a-mole whenever this issue comes up is having more people in AI policy putting more time into improving perspective. I don’t see shorter paths to increasing the number of people-prepared-to-handle-unexpected-complexity than giving people a broader and more general thinking capacity for thoughtfully reacting to the sorts of complex curveballs that you get in the real world. Rationalist fiction like HPMOR is great for this, as well as others e.g. Three Worlds Collide, Unsong, Worth the Candle, Worm (list of top rated ones here). With the caveat, of course, that doing well in the real world is less like the bite-sized easy-to-understand events in ratfic, and more like spotting errors in the methodology section of a study or making money playing poker.
I think, given the circumstances, it’s plausibly very valuable e.g. for people already spending much of their free time on social media or watching stuff like The Office, Garfield reruns, WWI and Cold War documentaries, etc, to only spend ~90% as much time doing that and refocusing ~10% to ratfic instead, and maybe see if they can find it in themselves to want to shift more of their leisure time to that sort of passive/ambient/automatic self-improvement productivity.
I’m not a decel, but the way this stuff often is resolved is that there are crazy people that aren’t taken seriously by the managerial class but that are very loud and make obnoxious asks. Think the evangelicals against abortion or the Columbia protestors.
Then there is some elite, part of the managerial class, that makes reasonable policy claims. For Abortion, this is Mitch McConnel, being disciplined over a long period of time in choosing the correct judges. For Palestine, this is Blinken and his State Department bureaucracy.
The problem with decels is that theoretically they are part of the managerial class themselves. Or at least, they act like they are. They call themselves rationalists, read Eliezer and Scott Alexander, and what not. But the problem is that it’s very hard for an uninterested third party to take seriously these Overton Window bogous claims from people that were supposed to be measured, part of the managerial class.
You need to split. There are the crazy ones that people don’t take seriously, but will move the managerial class. And there are the serious people that EA Money will send to D.C. to work at Blumenthal’s office. This person needs to make small policy requests that will sabotage IA, without looking so. And slowly, you get policy wins and you can sabotage the whole effort.