By: Daniel del Castillo, Chris Leong, and Kat Woods

We made a spreadsheet of resources for learning about AI safety. It was for internal purposes here at Nonlinear, but we thought it might be helpful to those interested in becoming safety researchers. 

Please let us know if you notice anything that we’re missing or that we need to update by commenting below. We’ll update the sheet in response to comments.

Highlights

There are a lot of courses and reading lists out there. If you’re new to the field, out of the ones we investigated, we recommend Richard Ngo’s curriculum of the AGI safety fundamentals program. It is a good mix of shorter, more structured, and more broad than most alternatives. You can register interest for their program when the next round starts or simply read through the reading list on your own.

We’d also like to highlight that there is a remote AI safety reading group that might be worth looking into if you’re feeling isolated during the pandemic.

About us: Nonlinear is a new AI alignment organization founded by Kat Woods and Emerson Spartz. We are a means-neutral organization, so are open to a wide variety of interventions that reduce existential and suffering risks. Our current top two research priorities are multipliers for existing talent and prizes for technical problems.

PS - Our autumn Research Analyst Internship is open for applications. Deadline is September 7th, midnight EDT. The application should take around ten minutes if your CV is already written.
 

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These aren't entirely about AI, but Brian Tomasik's Essays on Reducing Suffering and Tobias Baumann's articles on S-risks are also worth reading. They contain a lot of articles related to futurism and scenarios that could result in astronomical suffering. On the topic of AI alignment, Tomasik wrote this article on the risks of a "near miss" in AI alignment, and how a slightly misaligned AI may create far more suffering than a completely unaligned AI.

Nice initiative, thanks!

Plugging my own list of resources (last updated April 2020, next update before the end of the year).

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

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.