This was great fun, and I enjoyed contributing to it!

I'm really excited to see this survey idea getting developed. Congratulations to the Rethink team on securing funding for this! 

A few questions on design, content and purpose:

• Who are the users for this survey, how will they be involved with the design, and how will findings be communicated with them?
  • In previous living / repeated survey work that I've done (SCRUB COVID-19), having research users involved in the design was crucial for it to influence their decision-making. This also got complex when the survey became successful and there were different groups of research users, all of whom had different needs
  • Because "what gets measured, gets managed", there is a risk / opportunity in who decides which questions should be included in order to measure "awareness and attitudes towards EA and longtermism". 
• Will data, materials, code and documentation from the survey be made available for replication, international adaptation, and secondary analysis? 
  • This could include anonymised data, Qualtrics survey instruments, R code, Google docs of data documentation, etc
  • Secondary analysis could significantly boost the current and long-term value of the project by opening it up to other interested researchers to explore hypotheses relevant to EA
  • Providing materials and good code & documentation can help international replication and adapation. 
• Was there a particular reason to choose a monthly cycle for the survey? Do you have an end date in mind or are you hoping to continue indefinitely?
  • Do you anticipate that attitudes and beliefs would change that rapidly? In other successful 'pulse' style national surveys, it's more common to see yearly or even less frequent measurement (here's one great example of a longitudinal values survey from New Zealand)
  • Is there capacity to effectively design, conduct, analyse, and communicate at this pace? In previous work I've found that this cycle - especially in communicating with / managing research users, survey panel companies, etc - can become exhausting, especially if the idea is to run the survey indefinitely. 

In terms of specific questions to add, my main thought is to include behavioural items, not just attitudes and beliefs. 

• Ways of measuring this  could include "investigated the effectiveness of a charity before donating on the last occasion you had a chance", or "donated to effective charity in past 12 months", or "number of days in the past week that you ate only plant-based products (no meat, seafood, dairy or eggs)

Through the SCRUB COVID-19 project, we (several of us at Ready) ran a survey of 1700 Australians every 3 weeks for about 15 months (2020-2021) in close consultation with state policymakers and their research users. Please reach out if you'd like to discuss / share experiences.

Thanks for this Sean! I think work like this is exceptionally useful as introductory information for busy people who are likely to pattern match "advanced AI" to "terminator" or "beyond time horizon".

One piece of feedback I'll offer is to encourage you to consider whether it's possible to link narrow AI ethics concerns to AGI alignment in a way that your last point, "there is work that can be done" shows how current efforts to address narrow AI issues can be linked to AGI. This is especially relevant for governance. This could help people understand why it's important to address AGI issues now, rather than waiting until narrow AI ethics is "fixed" (a misperception I've seen a few times).

Great to see this initiative, Vael. I can think of several project ideas that could use this dataset of interviews with researchers.

Edit:

1. Analyse transcripts to identify behaviours that researchers and you describe as safe or unsafe, and identify influences on those behaviours (this would need validation with follow up work). Outcome would be an initial answer to the concrete question "who needs to do what differently to improve AI safety in research, and how"

2. Use the actors identified in the interviews to create a system/actor map to help understand flows of influence and information. Outcome: a better understanding of power dynamics of the system and opportunities for influence.

3. With information about the researchers themselves (especially of there are 90+), could begin to create a typology / segmentation to try and understand which types are more open / closed to discussions of safety, and why. Outcome: a strategy for outreach or further work to change decision making and behaviour towards AI safety.

Thanks for cross posting this Peter. I may be biased but I think this is a great initiative.

Do you have any info about the kinds of people who are reading a newsletter like this? Eg, are they mostly EAs who are interested in behaviour science, or mostly behaviour scientists who are interested in EA?

Akhil, thanks for this post. Your post happened to coincide with an email I received about a new article and associated webinar, "Centring Equity in Collective Impact". You and others in this space might find it relevant:

• link to webinar: https://fsg.zoom.us/webinar/register/WN_8BnpDWUeR_OdM7A_k7iebQ
• link to article: https://ssir.org/articles/entry/centering_equity_in_collective_impact

I use Feedly to follow several RSS feeds, including everything from the EA forum, LessWrong, etc. This lets me read more EA-adjacent/aligned content than if I visited each website infrequently because Feedly has an easy to use app on my phone.  

I liken it to a 'fire hose' in that I get everything, including all the personal blogs and low-effort content that would otherwise be hidden by the website sorting algorithm. There's also no (displayed) information in Feedly about the number or content of comments - instead I need to open each interesting post to find out if someone has commented on it. 

For some posts, the post content is the most valuable. In other posts, the commentary is the most valuable, and Feedly/RSS does a bad job of exposing this value to me easily. I also find that engagement is highest within the first 1-2 days of a post, but takes several hours to start. 

All of this is to say that I think the 'right' feed is probably still something like one or more RSS feeds - especially given their interoperability and ease of use - but that the user experience is likely to be highly variable depending on their needs and appetite for other- vs self-curation of what is in the feed.

Thanks for this list. Your EA group link for Focusmate just goes to the generic dashboard. Do you have an updated link you can share?

If you're comfortable sharing these resources on prioritisation and coordination, please also let me know about them.

I'm a researcher based in Australia and have some experience working with open/meta science. Happy to talk this through with you if helpful, precommitting to not take any of your money.

Quick answers, most of which are not one off, donation target ideas but instead would require a fair amount of setup and maintenance.

• $250,000 would be enough to support a program for disseminating open / meta science practices in Australian graduate students (within a broad discipline), if you had a trusted person to administrate it.

• you could have a prize for best open access paper published by a non PhD

• you could fund a conference such as AIMOS https://aimos.community/ (I have no affiliation and no knowledge of how effective this is)

• you could ask the Centre for open science people how to effectively spend the money