Seeds of Science is a new journal (funded through Scott Alexander's ACX grants program) that publishes speculative or non-traditional articles on scientific topics. Peer review is conducted through community-based voting and commenting by a diverse network of reviewers (or "gardeners" as we call them). 

We just sent out an article for review - "What are the Red Flags for Neural Network Suffering?" - that may be of interest to some in the EA community (also cross-posted on LW), so I wanted to see if anyone would be interested in joining us a gardener to review the article. It is free to join and anyone is welcome (we currently have gardeners from all levels of academia and outside of it). Participation is entirely voluntary - we send you submitted articles and you can choose to vote/comment or abstain without notification (so it's no worries if you don't plan on reviewing very often but just want to take a look here and there at what kinds of articles people are submitting). Another unique feature of the journal is that comments are published along with the article after the main text. 

To register, you can fill out this google form. From there, it's pretty self-explanatory - I will add you to the mailing list and send you an email that includes the manuscript, our publication criteria, and a simple review form for recording votes/comments.

Happy to answer any questions about the journal through email or in the comments below. Here is the abstract for the article. 

What are the Red Flags for Neural Suffering?

By [redacted] and [redacted]

Abstract:

Which kind of evidence would we need to see to believe that artificial neural networks can suffer? We review neuroscience literature, investigate behavioral arguments and propose high-level considerations that could shift our beliefs. Of these three approaches, we believe that high-level considerations, i.e. understanding under which circumstances suffering arises as an optimal training strategy, is the most promising. Our main finding, however, is that the understanding of artificial suffering is very limited and should likely get more attention. 
 

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