Comment author: SiebeRozendal 02 January 2018 03:59:10PM *  0 points [-]

This is an interesting project! I am wondering how valuable you have found it, and whether there are any plans for further development. I can imagine that it would be valuable to

  • Increase complexity to increase robustness of the model, but then find some balance between robustness and user-friendliness, perhaps by allowing users to view the model on different 'levels' of complexity.
  • Use some form of crowd-sourcing to get much more reliable estimates, ideally weighted by expertise or forecasting ability.
  • Incorporate some insights from the moral uncertainty literature, so that low probability of something being very bad (e.g. wild animal suffering, or insect suffering) are given appropriate weight.

However, I have no idea how feasible this is, and imagine it would require many and valuable resources (lots of time, money, and capable researchers). Do you already have thoughts on this?

P.S. The link is missing for part IV

Comment author: Milan_Griffes 29 November 2017 04:08:29AM *  1 point [-]

Thanks for the thoughtful comment :-)

This seems like a case of what Greaves calls simple cluelessness.

I'm fuzzy on Greaves' distinction between simple & complex cluelessness. Greaves uses the notion of "systematic tendency" to draw out complex cluelessness from simple, but "This talk of ‘having some reasons’ and ‘systematic tendencies’ is not as precise as one would like;" (from p. 9 of Greaves 2016).

Perhaps it comes down to symmetry. When we notice that for every imagined consequence, there is an equal & opposite consequence that feels about as likely, we can consider our cluelessness "simple." But when we can't do this, our cluelessness is complex.

This criterion is unsatisfyingly subjective though, because it relies on our assessing the equal-opposite consequence as "about as likely," plus relying on whether we are able to imagine an equal-opposite consequence or not.

Comment author: SiebeRozendal 02 January 2018 01:48:26PM 0 points [-]

I take Greaves' distinction between simple and complex cluelessness to be in the symmetry (just as you seem to do). However, I believe that this symmetry consists in that we are evaluating the same consequences following from either an act A, or a refraining of act A. For every story of long-term consequences happening from performing act A, there is a parallel story of these consequences C happening from refraining to do A. Thus, we can invoke a specific Principle of Indifference, where we take the probabilities of the options to be equal, reflecting our ignorance. Thus, P(C|A) = P(C|~A), where C is a story of some long-term consequences of either performing or refraining from doing A.

In complex cases, this symmetry does not exist, because we're trying to compare different consequences (C1, C2, .., Cn) resulting from the same act.

Comment author: SiebeRozendal 18 December 2017 03:46:08PM *  2 points [-]

Very exciting to read about this, especially the research agenda! I will definitely consult it when deciding on a topic for my master's thesis in philosophy.

I have a few questions about the strategy (Not sure if this is the best medium for these questions, but I didn't know where else);

  • a) Are you planning to be the central hub of EA-relevant academics?
  • b) What do you think about the Santa Fe Institute's model of a core group of resident academics, and a larger group of affiliated researchers who regularly visit?
  • c) Are you planning on incorporating more fields in the future, such as behavioural economics or complexity theory, and how do you decide on where to expand in?
  • d) Where can I find more information about GPI's strategy, and are you planning on publishing it to the EA Forum?

Btw, on p. 26 of the agenda there's an unfinished sentence: "How important is the distinction between ‘sequence’ thinking and ‘cluster’ thinking? What’s "

Comment author: SiebeRozendal 18 December 2017 02:56:36PM *  2 points [-]

Thanks for these findings! Especially looking forward to see the strategic analysis.

Some small remarks:

  1. Surprised to see that not many people use when the average boost is 21% to attendance. In Groningen it's definitely helping us, especially with some more diverse participants than our personal networks (although repeated attendance seems lower for people coming through
  2. The graph under 'Practical support and new ideas' is wrong, it's the same as the one above.
  3. Percentages would have been a little nicer to read than numbers, as the number of respondents varied

A random idea to help groups: A checklist with 'easy to do stuff that improves groups'/low hanging fruit, that groups can go through to evaluate themselves. On the list could be things such as (or whatever else you think works best):

  • Automated sign ups for mailing list
  • group
  • Website

If it's being used, it can be supplemented with short walkthrough or links to how-to's.