Research opportunity · Who can know about AI? Epistemic dependence and jurisdiction over the field
How tied to industry are researchers of AI's social effects outside computer science?
In short: has this been done?
Related work: Partly addressed. Related studies cover parts of this question; what they leave open is set out below. Only a first-pass search has been done, so it is not yet known whether a fuller search would find a study that does the whole design.
How far checked: First-pass screen only. A first-pass AI web search on 16 October 2026. No deeper check yet. Every search and check so far was done by AI; no person or domain expert has checked them yet.
The searches, the nearest work found and what the search could not reach
Follow this opportunity: Atom feed of RO-LD08-02 updates (new versions, and revisions of the claims it rests on).
Question
What share of authors of research on AI's social effects in social-science journals, interdisciplinary venues (FAccT, AIES) and policy reports have industry funding, employment or data agreements, how often is this disclosed, and how does it differ by discipline and region?
Gap type: Not yet measuredOne PhD chapter or paperLow to medium costRelated work: Partly addressed
Why it matters
The counts of industry ties come from technical venues and from 33 AI-ethics faculty at four North American universities. Research on AI's social effects is mostly academic by authorship, but ties through funding and data would not show in affiliation counts. Without a census beyond computer science, the debate cannot say how far dependence reaches the researchers who study AI's effects, or whether Europe's lower faculty ties hold there.
The debate lists this among what we still do not know: How large are industry ties among researchers who publish on AI's social effects in social-science journals, books and policy reports?
Evidence that motivates it
- Among computer-science faculty at four North American universities who had published on AI ethics or fairness between January 2015 and April 2020 and whose funding sources were known, 58% (19 of 33) had at some point been directly funded by large technology firms, and 97% (32 of 33) had a financial tie to them at some stage of their careers, including graduate funding or past employment; 10 of 17 position papers on AI’s ethical or societal impact published in Nature and Science since 2015 had at least one author with such ties.
How this study uses it: 19 of 33 AI-ethics faculty with known funding at four universities were directly funded by large firms. - Roughly 15% or less of peer-reviewed responsible-AI publications each year had a co-author affiliated with industry; from 2018 to 2022 industry’s participation at responsible-AI conferences stayed between about 20% and 23% while at leading AI conferences it rose from 29% to 37%; 34.5% of 519 AI-publishing firms published any responsible-AI research.
How this study uses it: Roughly 15% or less of responsible-AI publications have an industry co-author. - Among faculty authors at ACL 2022 whose funding could be traced, 66% had received industry funding: 72% in the US, 69% in China and 38% in Europe; among student authors 74% had an industry scholarship or internship, including 65% in Europe.
How this study uses it: Industry funding among NLP faculty differs by region (US 72%, China 69%, Europe 38%). - Of the papers published at the FAccT conference from 2018 to 2021, 61.3% were labelled STEM and 29.7% humanities, social sciences and arts; summarising a survey of conference affiliates, the authors list concerns including “out-sized industry connections.”
How this study uses it: FAccT is majority STEM; its affiliates raised concerns about industry connections, which were not counted.
A possible design
Sample authors of research on AI's social effects from 2022–2026 across FAccT, AIES, leading sociology, political-science, economics, communication and STS journals, and major policy-institute reports. For each author, code funding, employment, fellowships and data agreements with AI developers from CVs, acknowledgements, grant lists and developer announcements, and compare with disclosure statements in the papers. Report by venue type, discipline and region.
Data needed
Author lists and acknowledgements; public CVs; developer and foundation grantee lists; venue disclosure policies.
Feasibility
One PhD chapter or paper. Low to medium; manual coding of public records. CV-based coding misses undisclosed ties; double-code a subsample and report agreement.
Proposal pack: this page and its references on one printable page, with BibTeX.
Has this been done?
Partly done already: related work covers some of this question (first-pass screen of 16 October 2026; not yet checked in depth).
Counts exist for NLP and machine-learning venues and for a small sample of elite AI-ethics faculty; none was found for FAccT or AIES authors as a whole or for social-science journals.
How strong this evidence is
- Who searched and checked: no checker is recorded beyond the first-pass screen, which was part of the AI drafting (Claude (SocioLens Project Lead), AI-drafted from the LD-08 debate). Every check so far was done by AI; no person or domain expert has checked it yet.
- What was read: 1 of the 3 nearest works below was judged from an abstract, summary or search listing only; it is marked. Not every entry says how much of the work was read.
- Where the search could not reach: Screened by two web searches and an arXiv record lookup on the date shown; ACM Digital Library and social-science databases were not searched. Absence of a hit is not proof that the work does not exist.
- Before building a project on it, run your own search in a scholarly database such as Scopus, Web of Science, Google Scholar or SSRN.
Nearest work found
- Abdalla, Wahle, Ruas, Névéol, Ducel, Mohammad & Fort, ACL 2023 (LD08-SL-C05)
Full text read for this debate. Industry funding among NLP authors by region; NLP only. - Laufer et al., FAccT retrospective (LD08-SL-C13)
Full text read for this debate. Disciplinary make-up and a survey of concerns; industry ties not counted. - Bosten & Kleinberg, "Conflicts of Interest in Published NLP Research 2000-2024," arXiv:2502.16218 (2025) Judged from an abstract, summary or search listing only
Abstract read. Affiliation counts for NLP venues only.
Search queries used
census industry affiliation funding authors FAccT AIES papers conflict of interest disclosure study 2024 2025bibliometric analysis disciplines of AI and society research social science journals versus computer science share 2025arXiv id_list: 2502.16218
Cite this page
SocioLens project. (2026, October 16). How tied to industry are researchers of AI's social effects outside computer science? [Research opportunity RO-LD08-02, version v1]. SocioLens. https://sociolens-web.pages.dev/opportunities/ro-ld08-02/v1/
@misc{sociolens_ro_ld08_02_v1,
author = {{SocioLens project}},
title = {How tied to industry are researchers of AI's social effects outside computer science?},
year = {2026},
date = {2026-10-16},
howpublished = {\url{https://sociolens-web.pages.dev/opportunities/ro-ld08-02/v1/}},
note = {Research opportunity RO-LD08-02, version v1}
}The link points to this version, whose record never changes. For a finding, cite the original study as well: SocioLens summarizes research and does not replace it.
Provenance
RO-LD08-02 v1. Drafted by Claude (SocioLens Project Lead), AI-drafted from the LD-08 debate on 2026-10-16. Not yet reviewed. Not yet reviewed by a domain expert. This is a research hypothesis, not a finding.