Authors: Jess Riedel and Angelica Deibel
Cross-posted to EA Forum

In this post we present the first public version of our bibliographic database of research on the safety of transformative artificial intelligence (TAI). The primary motivations for assembling this database were to:

Aid potential donors in assessing organizations focusing on TAI safety by collecting and analyzing their research output.
Assemble a comprehensive bibliographic database that can be used as a base for future projects, such as a living review of the field.

The database contains research works motivated by, and substantively informing, the challenge of ensuring the safety of TAI, including both technical and meta topics. This initial version of the database has attempted comprehensive coverage only for traditionally formatted research produced in 2016-2020 by organizations with a significant safety focus (~360 items). The database also has significant but non-comprehensive coverage (~570 items) of earlier years, less traditional formats (e.g., blog posts), and non-safety-focused organizations. Usefully, we also have citation counts for essentially all the items for which that is applicable.

The core database takes the form of a Zotero library. Snapshots are also available as Google Sheet, CSV, and Zotero RDF. (Compact version for easier human reading: Google Sheet, CSV.)

The rest of this post describes the composition of the database in more detail and presents some high-level quantitative analysis of the contents. In particular, our analysis includes:

Lists of the most cited TAI safety research for each of the past few years (Tables 2 and 3)
A chart showing how written TAI safety research output has changed since 2016 (Figure 1).
A visualization of the degree of collaboration on TAI safety between different research organizations (Table 4).
A chart showing how the format of written research varied between organizations, e.g., manuscripts vs. journal articles vs. white papers (Figure 2).
A comparison of the number of citations that different organizations have accumulated (Figure 4).

In 2020 we observe a year-over-year drop in technical safety research, but not meta safety research, which we do not understand (Figure 1). We suggest some possible causes, but without a convincing explanation we must caution against drawing strong conclusions from any of our data.

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