MichaelA

Karma: 7,898

I’m Michael Aird, a Staff Researcher at Rethink Priorities, Research Scholar at the Future of Humanity Institute, and guest manager at the Effective Altruism Infrastructure Fund. Opinions expressed are my own. You can give me anonymous feedback at this link.

With Rethink, I’m currently mostly working on nuclear risk research. I might in future work on topics related to what I’m calling “Politics, Policy, and Security from a Broad Longtermist Perspective”.

Previously, I did longtermist macrostrategy research for Convergence Analysis and then for the Center on Long-Term Risk. More on my background here.

I also post to LessWrong sometimes.

If you think you or I could benefit from us talking, feel free to message me or schedule a call. For people interested in doing EA-related research/writing, testing their fit for that, “getting up to speed” on EA/longtermist topics, or writing for the Forum, I also recommend this post.

MichaelA 26 Sep 2021 18:52 UTC
2 points
on: Propose and vote on potential tags
Independent impressions or something like that
We already have Discussion norms and Epistemic deference, so I think there’s probably no real need for this as a tag. But I think a wiki entry outlining the concept could be good. The content could be closely based on my post of the same name and/or the things linked to at the bottom of that post.

MichaelA 26 Sep 2021 18:46 UTC
2 points
in reply to: Lukas_Finnveden’s comment on: MichaelA’s Shortform
Thanks for the suggestion—I’ve now gone ahead and made that top-level post :)

Independent impressions

MichaelA26 Sep 2021 18:43 UTC

27 points

0 comments1 min readEA link

MichaelA 26 Sep 2021 18:33 UTC
2 points
on: List of AI safety courses and resources
Haven’t checked out your spreadsheet, but I do think these sorts of collections are good things to create! And on that note, I’ll mention my Collection of AI governance reading lists, syllabi, etc. (so that’s for AI governance, not technical AI safety stuff). I suggest people who want to read it read the doc version, but I’ll also copy the full contents into this comment for convenience.
What is this doc, and why did I make it?
AI governance is a large, complex, important area that intersects with a vast array of other fields. Unfortunately, it’s only fairly recently that this area started receiving substantial attention, especially from specialists with a focus on existential risks and/or the long-term future. And as far as I’m aware there aren’t yet any canonical, high-quality textbooks or online courses on the topic.[1] It seems to me that this means this is an area where well-curated and well-structured reading lists, syllabi, or similar can be especially useful, helping to fill the role that textbooks otherwise could.[2]
Fortunately, when I started looking for relevant reading lists and syllabi, I was surprised by how many there were. So I decided to try to collect them all in one place. I also tried to put them in very roughly descending order of how useful I’d guess they’d be to a randomly chosen EA-aligned person interested in learning about AI governance.
I think this might help myself, my colleagues, and others who are trying to “get up to speed”, for the reasons given in the following footnote.[3]
I might later turn this doc into a proper post on the EA Forum.
See also EA syllabi and teaching materials and Courses on longtermism.
How can you help
- Please comment if you know of anything potentially relevant which I haven’t included!
- Please comment if you have opinions on anything listed!
The actual collection
- September AGI safety fundamentals curriculum—Richard Ngo
- Alignment Newsletter Database—Rohin Shah
  - This is more relevant to technical AI safety than to AI governance, but some categories are pretty relevant to AI governance, especially “AI strategy and policy”, “Forecasting”, and “Field building”
- AI Governance Reading List—SERI 2021 Summer—Mauricio Baker
  - Mauricio had also previously made a syllabus on the same topics: AI Governance Syllabus ’21.docx
- Governance of AI Reading List – Oxford Spring 2020 - Markus Anderljung
- Reading Guide for the Global Politics of Artificial Intelligence—Allan Dafoe
  - I’m guessing other lists made by people associated with GovAI already draw on and superseded this, but I don’t know
- “Resources” section from Guide to working in artificial intelligence policy and strategy − 80,000 Hours
  - Note: I think the only book from there that’s available on Audible UK is The Second Machine Age.
    But the description of the book sounds to me kind-of basic and not especially longtermism-relevant.
- AI policy introductory reading list—Niel Bowerman (I think)
- Governance of AI—Some suggested readings [v0.5, shared] - Ashwin Acharya
  - Drawn on for SERI’s reading list
- Artificial Intelligence and International Security Syllabus [public] - Remco Zwetsloot, 2018 (I think)
- Books and lecture series relevant to AI governance—me and commenters
- Section on “Unaligned artificial intelligence” from Syllabus — The Precipice
  - Tangential critique: I personally think that it’s problematic and misleading that both The Precipice and this syllabus use the heading “unaligned artificial intelligence” while seeming to imply that this covers all key aspects of AI risk, since I think this obscures some risk pathways.
- AI Policy Readings Draft.docx—EA Oxford
  - Drawn on for SERI’s reading list
- My post Crucial questions for longtermists includes a structured list of questions related to the “Value of, and best approaches to, work related to AI”, and this associated doc contains readings related to each of those questions
  - I haven’t updated this much since 2020
  - Questions listed there include:
    Is it possible to build an artificial general intelligence (AGI) and/or transformative AI (TAI) system? Is humanity likely to do so?
    What form(s) is TAI likely to take? What are the implications of that? (E.g., AGI agents vs comprehensive AI services)
    What will the timeline of AI developments be?
    How much should longtermists’ prioritise AI?
    What forms might an AI catastrophe take? How likely is each?
    What are the best approaches to reducing AI risk or increasing AI benefits?
- Good resources for getting a high-level understanding of AI risk—Michael Aird
- AI governance intro readings—Felipe Calero
- Luke Muehlhauser’s 2013 and 2014 lists of books he’d listened to recently
  - I think many/most of these books were chosen for “seem[ing] likely to have passages relevant to the question of how well policy-makers will deal with AGI”
  - Many/most of these aren’t available as audiobooks; Luke turned them into audiobooks himself
- A Contra AI FOOM Reading List – Magnus Vinding
  - Described in SERI’s reading list as a “List of arguments (of varied quality) against ‘fast takeoff’”
- List of resources on AI and agency—Ben Pace
- You could also use research agendas related to AI governance as reading lists, by following the sources they cite on various topics. Relevant agendas include:
  - (Note that I haven’t checked how well each of these agendas would work for this purpose. This list is taken from my central directory for open research questions.)
  - The Centre for the Governance of AI’s research agenda − 2018
  - Some AI Governance Research Ideas—the Centre for the Governance of AI, 2021
  - Promising research projects—AI Impacts, 2018
    They also made a list in 2015; I haven’t checked how much they overlap
  - Cooperation, Conflict, and Transformative Artificial Intelligence (the Center on Long-Term Risk’s research agenda) - Jesse Clifton, 2019
  - Open Problems in Cooperative AI—Dafoe et al., 2020
  - Problems in AI Alignment that philosophers could potentially contribute to—Wei Dai, 2019
  - Problems in AI risk that economists could potentially contribute to—Michael Aird, 2021
  - Technical AGI safety research outside AI—Richard Ngo, 2019
  - Artificial Intelligence and Global Security Initiative Research Agenda—Centre for a New American Security, no date
  - A survey of research questions for robust and beneficial AI—Future of Life Institute, no date
  - “studies which could illuminate our strategic situation with regard to superintelligence”—Luke Muehlhauser, 2014 (he also made a list in 2012)
  - A shift in arguments for AI risk—Tom Sittler, 2019
  - Longtermist AI policy projects for economists—Risto Uuk (this doc was originally just made for Risto’s own use, so the ideas shouldn’t be taken as high-confidence recommendations to anyone else)
- Annotated Bibliography of Recommended Materials—CHAI
  - I think this is much more focused on technical AI safety than AI governance
- Some Rethink Priorities staff may soon make a long, tiered reading list tailored to the AI governance project ideas we may work on. If it seems to me that this would be useful to other people, I might add a link to a version of it here.
- There may be additional relevant reading lists / syllabi / sections in the links given here: EA syllabi and teaching materials—EA Forum
  - And here Courses on longtermism | Pablo’s miscellany
- I think there was also a short reading list associated with the EA In-Depth Fellowship
- A related category to reading lists is newsletters that provide summaries and commentary of a bunch of research outputs. E.g.:
  - Rohin’s
  - Jack Clarke’s
  - CSET’s
  - …
- Mauricio Baker suggested that I or people reading this doc might also be interested in “syllabi aimed at aspiring AI technical safety researchers, such as this one: Technical AI Safety Reading List. I have a vague sense that engaging with some of this content has been helpful for my having a better broad sense of what’s going on with AI safety, which seems helpful for governance.”
- Some parts of Krakovna’s AI safety resources and Maini’s AI Reading List may be quite useful for AI governance people, though I think they’re more relevant for technical AI safety people
My thanks to everyone who made these lists, as well as to Mauricio Baker for pointing me to some of the lists.
Footnotes
[1] Though there are various presumably high-quality textbooks or courses with some relevance, some high-quality non-textbook books on the topic, some in-person courses that might be high-quality (I haven’t participated in them), and some things that fill somewhat similar roles (like EA seminar series, reading groups, or fellowships).
[2] See also Research Debt and Suggestion: EAs should post more summaries and collections.
[3]
- This collection should make it easier to find additional reading lists, syllabi, etc., and thus easier to find additional readings that have been evaluated as especially worth reading in general, especially worth reading on a given topic, and/or especially good as introductory resources.
- This collection should make it easier to find and focus on reading lists, syllabi, etc. that are better and/or more relevant to one’s specific needs.
  - To help with this, please comment on this doc if you have opinions about anything listed.
- Even before or without engaging with the actual items included in a given reading list, syllabus, or similar, engaging with the structure and commentary in that document itself could help one understand what the important components, divisions, concepts, etc. within AI governance are. And this collection should help people find more, better, and/or more relevant such documents.

MichaelA 25 Sep 2021 8:30 UTC
3 points
in reply to: Benjamin_Todd’s comment on: Some global catastrophic risk estimates
Late to the thread, but one further thing I’d note is that it’s entirely possible for multiple different global catastrophe scenarios to occur by 2100. E.g., a global catastrophe in 2030 due to nuclear conflict and another in 2060 due to bioengineering. From a skim, I think the relevant Metaculus questions are about “by 2100” rather than “the first global catastrophe by 2100″, so they’re not mutually exclusive.
So if it was the case that the individual questions added to 14% and the total question added to 14% (which Christian’s answer suggests it isn’t, but I haven’t checked), that wouldn’t necessarily mean a ~0% chance of catastrophe from something else (though it’s at least weak evidence of that, e.g. because if the total question had a forecast twice as high as the sum of the individual questions, that would be evidence in favour of the likelihood of some other catastrophe).

MichaelA 25 Sep 2021 6:33 UTC
3 points
in reply to: Vael Gates’s comment on: A central directory for open research questions
Thanks for the heads up—I’ve now added a link to your doc and changed the date for the CNAS agenda :)

MichaelA 22 Sep 2021 11:04 UTC
3 points
on: An analysis of Metaculus predictions of future EA resources, 2025 and 2030
This suggests that binary questions more easily attract forecasts, which was my intuition already, and seems relevant to future efforts to write questions—if they can be turned into binary questions without too much loss of value, this might be preferable for getting more attention from forecasters.
1. Do you have a sense of why this is the case? Is it typically easier/faster to make binary than continuous forecasts? Are there any other mechanisms?
2. Do you have a sense of how strong that effect might tend to be? Like whether it can typically be expected to increase the number of forecasters by 50%, 100%, 200%, etc. relative to how many would’ve forecasted on the equivalent continuous questions?

MichaelA 22 Sep 2021 9:27 UTC
8 points
on: MichaelA’s Shortform
Collection of collections of resources relevant to (research) management, mentorship, training, etc.
(See the linked doc for the most up-to-date version of this.)
The scope of this doc is fairly broad and nebulous. This is not The Definitive Collection of collections of resources on these topics—it’s just the relevant things that I (Michael Aird) happen to have made or know of.
- Management & mentoring—EA Forum
- Management-related books [shared] - me
- Meeting templates for mentors/managers [shared] - me
- Goal-setting templates or processes [shared] - me
- Readings and notes on how to do high-impact research—me
- Readings and notes on how to do high-quality, efficient research—me
- Readings and notes on how to write/communicate well—me
- Resources—Effective Thesis
- Tips On Doing Impactful Research—Effective Thesis
- SERI Research Proposal Generation Tips 2021 - SERI
- Research Training Programs—EA Forum Wiki
- Review of SRF 2019 - Max Daniel and/or Rose Hadshar of FHI
  - See also Review of FHI’s Summer Research Fellowship 2020
- Research project planning templates/resources [shared]
- Resource library of the Management Center
  - This is a non-EA nonprofit that provides management training and resources to other nonprofits
  - I and several other Rethink Priorities staff did their management training. I thought it was fairly useful (though with some flaws).
- Some quick reflections on mentoring from Max Daniel
Here are some things that are “internal” or that I don’t have permission to share, but that I might be able to make shareable versions of, share after asking permission, or talk to people about, if someone is interested::
- Summary and commentary on the book Managing to Change the World—someone at RP
- “Management / org structure things RP could consider”—me
- “Aspects of CLR’s SRF which RP’s internship could draw on”—me
- My Anki cards on Getting Things Done—me
- “RSP Personal Review: Meta doc”—someone who was at FHI
- Performance review templates collected at the bottom of the FHI doc “Performance feedback—Meta doc”—someone who was at FHI
- Quick notes on management—someone at RP
Finally, here are my notes on relevant books (though each of these links isn’t really a “collection”):
- Notes on Mochary’s “The Great CEO Within” (2019)
- [more to be added later]

MichaelA 22 Sep 2021 9:20 UTC
2 points
on: MichaelA’s Shortform
Collection of AI governance reading lists, syllabi, etc.
This is a doc I made, and I suggest reading the doc rather than shortform version (assuming you want to read this at all). But here it is copied out anyway:
What is this doc, and why did I make it?
AI governance is a large, complex, important area that intersects with a vast array of other fields. Unfortunately, it’s only fairly recently that this area started receiving substantial attention, especially from specialists with a focus on existential risks and/or the long-term future. And as far as I’m aware there aren’t yet any canonical, high-quality textbooks or online courses on the topic.[1] It seems to me that this means this is an area where well-curated and well-structured reading lists, syllabi, or similar can be especially useful, helping to fill the role that textbooks otherwise could.[2]
Fortunately, when I started looking for relevant reading lists and syllabi, I was surprised by how many there were. So I decided to try to collect them all in one place. I also tried to put them in very roughly descending order of how useful I’d guess they’d be to a randomly chosen EA-aligned person interested in learning about AI governance.
I think this might help myself, my colleagues, and others who are trying to “get up to speed”, for the reasons given in the following footnote.[3]
I might later turn this doc into a proper post on the EA Forum.
See also EA syllabi and teaching materials and Courses on longtermism.
How can you help
- Please comment if you know of anything potentially relevant which I haven’t included!
- Please comment if you have opinions on anything listed!
The actual collection
- September AGI safety fundamentals curriculum—Richard Ngo
- Alignment Newsletter Database—Rohin Shah
  - This is more relevant to technical AI safety than to AI governance, but some categories are pretty relevant to AI governance, especially “AI strategy and policy”, “Forecasting”, and “Field building”
- AI Governance Reading List—SERI 2021 Summer—Mauricio Baker
  - Mauricio had also previously made a syllabus on the same topics: AI Governance Syllabus ’21.docx
- Governance of AI Reading List – Oxford Spring 2020 - Markus Anderljung
- Reading Guide for the Global Politics of Artificial Intelligence—Allan Dafoe
  - I’m guessing other lists made by people associated with GovAI already draw on and superseded this, but I don’t know
- “Resources” section from Guide to working in artificial intelligence policy and strategy − 80,000 Hours
  - Note: I think the only book from there that’s available on Audible UK is The Second Machine Age.
    But the description of the book sounds to me kind-of basic and not especially longtermism-relevant.
- AI policy introductory reading list—Niel Bowerman (I think)
- Governance of AI—Some suggested readings [v0.5, shared] - Ashwin Acharya
  - Drawn on for SERI’s reading list
- Artificial Intelligence and International Security Syllabus [public] - Remco Zwetsloot, 2018 (I think)
- Books and lecture series relevant to AI governance—me and commenters
- Section on “Unaligned artificial intelligence” from Syllabus — The Precipice
  - Tangential critique: I personally think that it’s problematic and misleading that both The Precipice and this syllabus use the heading “unaligned artificial intelligence” while seeming to imply that this covers all key aspects of AI risk, since I think this obscures some risk pathways.
- AI Policy Readings Draft.docx—EA Oxford
  - Drawn on for SERI’s reading list
- My post Crucial questions for longtermists includes a structured list of questions related to the “Value of, and best approaches to, work related to AI”, and this associated doc contains readings related to each of those questions
  - I haven’t updated this much since 2020
  - Questions listed there include:
    Is it possible to build an artificial general intelligence (AGI) and/or transformative AI (TAI) system? Is humanity likely to do so?
    What form(s) is TAI likely to take? What are the implications of that? (E.g., AGI agents vs comprehensive AI services)
    What will the timeline of AI developments be?
    How much should longtermists’ prioritise AI?
    What forms might an AI catastrophe take? How likely is each?
    What are the best approaches to reducing AI risk or increasing AI benefits?
- Good resources for getting a high-level understanding of AI risk—Michael Aird
- AI governance intro readings—Felipe Calero
- Luke Muehlhauser’s 2013 and 2014 lists of books he’d listened to recently
  - I think many/most of these books were chosen for “seem[ing] likely to have passages relevant to the question of how well policy-makers will deal with AGI”
  - Many/most of these aren’t available as audiobooks; Luke turned them into audiobooks himself
- A Contra AI FOOM Reading List – Magnus Vinding
  - Described in SERI’s reading list as a “List of arguments (of varied quality) against ‘fast takeoff’”
- List of resources on AI and agency—Ben Pace
- You could also use research agendas related to AI governance as reading lists, by following the sources they cite on various topics. Relevant agendas include:
  - (Note that I haven’t checked how well each of these agendas would work for this purpose. This list is taken from my central directory for open research questions.)
  - The Centre for the Governance of AI’s research agenda − 2018
  - Some AI Governance Research Ideas—the Centre for the Governance of AI, 2021
  - Promising research projects—AI Impacts, 2018
    They also made a list in 2015; I haven’t checked how much they overlap
  - Cooperation, Conflict, and Transformative Artificial Intelligence (the Center on Long-Term Risk’s research agenda) - Jesse Clifton, 2019
  - Open Problems in Cooperative AI—Dafoe et al., 2020
  - Problems in AI Alignment that philosophers could potentially contribute to—Wei Dai, 2019
  - Problems in AI risk that economists could potentially contribute to—Michael Aird, 2021
  - Technical AGI safety research outside AI—Richard Ngo, 2019
  - Artificial Intelligence and Global Security Initiative Research Agenda—Centre for a New American Security, no date
  - A survey of research questions for robust and beneficial AI—Future of Life Institute, no date
  - “studies which could illuminate our strategic situation with regard to superintelligence”—Luke Muehlhauser, 2014 (he also made a list in 2012)
  - A shift in arguments for AI risk—Tom Sittler, 2019
  - Longtermist AI policy projects for economists—Risto Uuk (this doc was originally just made for Risto’s own use, so the ideas shouldn’t be taken as high-confidence recommendations to anyone else)
- Annotated Bibliography of Recommended Materials—CHAI
  - I think this is much more focused on technical AI safety than AI governance
- Some Rethink Priorities staff may soon make a long, tiered reading list tailored to the AI governance project ideas we may work on. If it seems to me that this would be useful to other people, I might add a link to a version of it here.
- There may be additional relevant reading lists / syllabi / sections in the links given here: EA syllabi and teaching materials—EA Forum
  - And here Courses on longtermism | Pablo’s miscellany
- I think there was also a short reading list associated with the EA In-Depth Fellowship
- A related category to reading lists is newsletters that provide summaries and commentary of a bunch of research outputs. E.g.:
  - Rohin’s
  - Jack Clarke’s
  - CSET’s
  - …
- Mauricio Baker suggested that I or people reading this doc might also be interested in “syllabi aimed at aspiring AI technical safety researchers, such as this one: Technical AI Safety Reading List. I have a vague sense that engaging with some of this content has been helpful for my having a better broad sense of what’s going on with AI safety, which seems helpful for governance.”
- Some parts of Krakovna’s AI safety resources and Maini’s AI Reading List may be quite useful for AI governance people, though I think they’re more relevant for technical AI safety people
My thanks to everyone who made these lists, as well as to Mauricio Baker for pointing me to some of the lists.
Footnotes
[1] Though there are various presumably high-quality textbooks or courses with some relevance, some high-quality non-textbook books on the topic, some in-person courses that might be high-quality (I haven’t participated in them), and some things that fill somewhat similar roles (like EA seminar series, reading groups, or fellowships).
[2] See also Research Debt and Suggestion: EAs should post more summaries and collections.
[3]
- This collection should make it easier to find additional reading lists, syllabi, etc., and thus easier to find additional readings that have been evaluated as especially worth reading in general, especially worth reading on a given topic, and/or especially good as introductory resources.
- This collection should make it easier to find and focus on reading lists, syllabi, etc. that are better and/or more relevant to one’s specific needs.
  - To help with this, please comment on this doc if you have opinions about anything listed.
- Even before or without engaging with the actual items included in a given reading list, syllabus, or similar, engaging with the structure and commentary in that document itself could help one understand what the important components, divisions, concepts, etc. within AI governance are. And this collection should help people find more, better, and/or more relevant such documents.

MichaelA 20 Sep 2021 7:47 UTC
3 points
in reply to: Vael Gates’s comment on: A central directory for open research questions
Thanks! I’ve now added the first of those two :)

MichaelA 15 Sep 2021 15:04 UTC
3 points
on: Ethics of existential risk
I think this is probably worth citing here, but I’ve only read the abstract myself: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2807377

MichaelA 12 Sep 2021 17:27 UTC
2 points
in reply to: Locke_USA’s comment on: Improving EAs’ use of non-EA options for research training, credentials, testing fit, etc.
Nice, thanks for that info! I’ll check out that post soon, and might reach out to you with questions at some point.

MichaelA 11 Sep 2021 14:06 UTC
4 points
on: Think tanks
I think it’d be good for someone to read/skim the relevant 80k article and write some entry text based on that.
I think it’d also be good to list/discuss EA, EA-adjacent, or especially-EA-relevant think tanks, such as Rethink Priorities, CSET, and NTI.

Improving EAs’ use of non-EA options for research training, credentials, testing fit, etc.

MichaelA11 Sep 2021 13:52 UTC

22 points

2 comments8 min readEA link

MichaelA 11 Sep 2021 12:52 UTC
2 points
in reply to: MichaelA’s comment on: Management & mentoring
I have in mind that this entry (or this pair of entries) would cover roughly people management and mentoring, rather than also covering specifically project management, operations management, or other management-y things. Maybe that should be clarified in the entry text. Or maybe it’d be best to just accept a broader sense of “management” as the scope here.

MichaelA 11 Sep 2021 12:49 UTC
2 points
on: Management & mentoring
I included WANBAM in the Related entries, but I think using org tags like that is somewhat uncommon and I think it’d be fair enough if someone wanted to remove that.

MichaelA 11 Sep 2021 11:58 UTC
2 points
on: Management & mentoring
It’d be good to discuss the things this survey https://forum.effectivealtruism.org/posts/TpoeJ9A2G5Sipxfit/ea-leaders-forum-survey-on-ea-priorities-data-and-analysis says about management

MichaelA 11 Sep 2021 11:52 UTC
2 points
in reply to: Pablo’s comment on: Propose and vote on potential tags
Ok, I’ve now made this, for now going with just one entry called Management & mentoring, but flagging on the Discussion page that that could be changed later.

MichaelA 11 Sep 2021 11:50 UTC
4 points
on: Management & mentoring
My original proposal:
Management/mentoring, or just one of those terms, or People management, or something like that
This tag could be applied to many posts currently tagged Org strategy, Scalably using labour, Operations, research training programs, Constraints in effective altruism, WANBAM, and effective altruism hiring. But this topic seems sufficiently distinct from those topics and sufficiently important to warrant its own entry.
Pablo’s response:
Sounds good. I haven’t reviewed the relevant posts, so I don’t have a clear sense of whether “management” or “mentoring” is a better choice; the latter seems preferable other things equal, since “management” is quite a vague term, but this is only one consideration. In principle, I could see a case for having two separate entries, depending on how many relevant posts there are and how much they differ. I would suggest that you go ahead and do what makes most sense to you, since you seem to have already looked at this material and probably have better intuitions. Otherwise I can take a closer look myself in the coming days.
I didn’t have a very strong reason for ultimately going with Management & mentoring, and am fine for it to be split into two or maybe renamed if someone has reason to think that that’s be better.

MichaelA 10 Sep 2021 14:44 UTC
4 points
on: Propose and vote on potential tags
Management/mentoring, or just one of those terms, or People management, or something like that
This tag could be applied to many posts currently tagged Org strategy, Scalably using labour, Operations, research training programs, Constraints in effective altruism, WANBAM, and effective altruism hiring. But this topic seems sufficiently distinct from those topics and sufficiently important to warrant its own entry.

MichaelA

In­de­pen­dent impressions

What is this doc, and why did I make it?

How can you help

The actual collection

Collection of collections of resources relevant to (research) management, mentorship, training, etc.

Collection of AI governance reading lists, syllabi, etc.

What is this doc, and why did I make it?

How can you help

The actual collection

Im­prov­ing EAs’ use of non-EA op­tions for re­search train­ing, cre­den­tials, test­ing fit, etc.

Independent impressions

Improving EAs’ use of non-EA options for research training, credentials, testing fit, etc.