Thanks for the feedback, this is very helpful!
EA vs. CCC values: I think about prioritization as a 3-step process of choosing a cause, an intervention, and then a specific organization. EA, 80k Hours or Global priorities are focused especially on choosing causes (the most „meta“ activity), GiveWell and charity evaluators are focusing on the third step – recommending organizations. Copenhagen Consensus´ approach can be seen as a compatible middle step in this process – prioritizing between possible interventions and solutions (hopefully more and more in the most high-impact areas, being increasingly compatible with EA).
Discount rates: Yes, Copenhagen Consensus uses discount rates (3% and 5% in previous projects) I would argue especially because of the uncertainty about the future, and our comparative advantage in solving current issues. We are always open to discuss this with EA, especially considering projects in more developed countries.
X-risks: Our projects are done in three steps, that we value more or less equally: 1) stakeholder research (gathering 1000+ policy ideas and choosing the top 60-80 interventions to analyse), 2) cost benefit analyses on those interventions, and 3) media dissemination and public advocacy for the top priorities. I would expect x-risks to be considered in the research in developed country rather that in Bagladesh, Haiti or India. Interventions reducing x-risks will definitely be among the 1000+ policy ideas, and even if they don´t make it into the 60-80 intervention analysed, thinking about low-chance, extreme-impact effects is certainly something that should be included in all relevant cost-benefit analyses.
Meta: There is a substantial difficulty to reasonably calculate very broad long-term benefits. Cost-benefit ratio of “Improving institutional decision-making” would be almost impossible to calculate, but we will assess our own impact, and since this is exactly our goal, some interesting data might come up. It would be also helpful to analyse partial interventions such as anti-corruption or transparency, that should lead to better institutional decision-making as a result. There are other interventions with long-term effects, that might make it to the final round and EA would probably agree on, such as programs in mental health, giving homes, consumption of animal products (e.g. removing subsidies for factory farms), antibiotic resistance etc.
Advocacy challenges: The project intends to, of course, say the most true things. If some of the top priorities will be difficult to implement, politicians will simply choose not pay attention to them, but at least public awareness will be created. I don’t think there will be any extremely controversial interventions (in AI Safety, for example), that would make us consider not publishing it to protect the whole project from being ridiculed and discredited.
Public sentiment and preventing authoritarianism: Yes, we expect public sentiment to be a key driving factor for change (along with roundtables and presentations to politicians, political parties and members of budget committee), more so than in third-world countries. We are in touch with local media, that are influential in shaping public opinion. Implementing the best interventions would have great effects, but even if not implemented, we hope to move public discussion (that is always in conflict between different world-views) to a little bit more rational level, and open up as many eyes and educate as many minds as possible to think in bigger picture. That seems to be a good way to fight irrational populism, which has all sorts of bad impacts on the society.
Importance of robust policies vs. acceptable policies: This possible trade-off should be made in each analysis, the researcher should think if the specific intervention would make the most impact by making the connected policies more robust, or if the most impact can be done by, for example, increasing the funding for this intervention slowly, so that it´s acceptable by all sides and works best in the long run. This should ideally be encompassed in each cost-benefit ratio.
Preventing bad policies vs. improving good ones: We will look for policies that can have any of these effects, but we are not specifically looking for the existing bad policies. Improving good ones is not the goal either, we want to find policies that have great effects per each Koruna, but occupy unfairly bad position in the current equilibria—might be unpopular, underfunded, not yet well understood or not known by the public.
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I assume this is 3% real (adjusted for inflation) discount rate. This is actually similar to global per capita income growth. Since a dollar is worth less to a rich person (logarithmic utility), EAs are generally ok with discounting at the economic growth rate. This means we are valuing the utility of future generations the same as present generations.
And I would be happy if our prioritization research discusses other heuristics such as the ones that Denis (http://effective-altruism.com/ea/1lu/current_thinking_on_prioritization_2018/#interventions_1) or Michael (http://effective-altruism.com/ea/yp/evaluation_frameworks_or_when_importance/) propose.