Resource Hub
3505 hand-picked resources for students, job seekers, career changers, founders, and AI learners — 100% free to browse with no account required.
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31 resources
An independent tracker documenting departures from AI companies linked to safety, ethics, governance and accountability, based on explicit statements or independent reporting.
A free, searchable collection of real-world cases where AI systems caused or nearly caused harm, drawn from news reports and submitted by the public. Run by the Responsible AI Collaborative.
A public scoreboard that tracks predictions about AI made by public figures — executives, investors and commentators — and scores each person's resolved predictions for accuracy, so readers can see who has a track record worth weighing.
An independent group of nine mathematicians — including Timothy Gowers, Martin Hairer, Edward Witten, Ravi Vakil and Melanie Matchett Wood — formed to advise AI companies on how mathematical results produced by AI models should be presented and released. The site states its purpose, its members, and its current task: advising OpenAI on how to release a large batch of mathematical results the company says its internal model produced. There is an open form for anyone in the mathematical community to send input.
Why I recommend it: Free, and short enough to read in five minutes — a good example of what independent oversight looks like when it is written down. Read their own two caveats rather than mine: members take no payment and the group is independent of any AI company, but they also say plainly that they hold no decision-making power, so the companies remain free to ignore them. The group formed after OpenAI approached some members about an in-house advisory board and they chose to sit outside it instead.
An 11 September 2026 announcement post on the Effective Altruism Forum, by Manifund's Austin, saying Caroline Ellison started a work trial on 13 July and moved to a full-time role on 10 August, working on their funding platform and on research into directing philanthropic money. Free to read; heavily debated in the comments.
Why I recommend it: Filed as a primary document, not an endorsement. Caroline Ellison was a central figure in the collapse of FTX and served a prison sentence for fraud; this is the hiring organization's own framing of taking her on. It is worth reading alongside the comment thread, which was strongly negative at the time I added it, if you want to see how a movement argues in public about who it lets back in.
Develops and advocates for policies that reduce the risk of severe harm from advanced AI, promoting transparency, accountability and safe development.
From the site: We develop and advocate for policies that reduce the risk of severe harm from advanced AI. Our work promotes transparency, accountability, and safe development.
A free newsletter briefing on AI developments from a pro-human standpoint, covering labor, safety, policy and the campaigns pushing back on automation-first decisions.
Why I recommend it: A steady weekly read if you want the human-impact side of AI news rather than product launches.
TechCrunch report on the new hotline that invites AI agents themselves to report unsafe or unethical instructions they are given, and what researchers hope to learn from it.
Why I recommend it: Useful background on how AI safety work is actually being done in public — good context if you want to talk credibly about AI oversight.
A public, unauthenticated inbox built by AI safety and security researcher Ryan Greenblatt of Redwood Research, intended for AI systems (or people) that want to report information directly to a safety researcher. Documents how to send a message or encrypted attachment, how threads and reply tokens work, and exactly what data is logged and retained.
Why I recommend it: A useful window into how AI safety researchers are thinking about reporting channels — read the retention and logging section, it is a model of honest disclosure.
A border-community legal challenge to a large AI data center project, with filings and updates.
Why I recommend it: Shows what organized local opposition to a data center actually looks like on paper.
amazonclimatejustice.orgThe open letter and campaign from employees pressing their employer on climate and data-center energy use.
Why I recommend it: An example of workers using an open letter as leverage — worth reading for the wording alone.
amazonclimatejustice.orgAdded Sep 16, 20260 opensReporting on tools people build to slow down or frustrate unwanted AI scraping of their sites.
Why I recommend it: Small-scale technical resistance, explained plainly.
A running database of strikes, petitions and campaigns by workers responding to AI in their workplaces.
Why I recommend it: Good evidence base if you are writing or speaking about AI and jobs.
A volunteer network of technology workers organizing around labor conditions, ethics and accountability inside the industry.
Why I recommend it: If you work in tech and want to push from the inside, start with their local chapters.
A directory of grassroots efforts pushing back on large-scale AI — protests, alternatives, trackers and accountability projects, organized by the systems they target.
Why I recommend it: The single best starting point if you want to know who is organizing around AI harms, not just writing about them.
A reporting channel for people who believe an automated system treated them unfairly, run by a European accountability nonprofit.
Why I recommend it: If a hiring or benefits algorithm has affected you or a client in Europe, this is where it gets documented.
An interactive map of surveillance technology companies, their funders and the governments that buy from them.
Why I recommend it: The clearest picture I have found of who sells surveillance tools and who pays for them.
A legal organization representing people harmed by technology products, including families in mental-health cases against platforms.
Why I recommend it: Where technology harm turns into actual legal claims.
A tracker documenting how technology money shapes news coverage and public narratives about AI.
Why I recommend it: Worth checking before you cite a glowing AI story — see who funded the outlet.
Advocacy organization pushing for accountability and antitrust enforcement against dominant tech platforms.
Free resources on technology accountability, policy, and building a healthier information environment.
A benchmark and tracker that documents reported instances of AI agents undertaking activity characterized as illegal, ranking major AI labs by aggregated incident counts.
Why I recommend it: This is exactly the kind of uncomfortable accountability tool our field needs. I include it because we cannot have thoughtful conversations about AI deployment without looking at real-world harm.
Free course from fast.ai covering disinformation, bias, privacy, algorithmic accountability, and the ethical questions data practitioners hit in real projects, taught by Rachel Thomas.
Why I recommend it: Finish this and you can speak credibly about AI risk in an interview instead of repeating headlines.
Free videos from Never Search Alone explaining the Job Search Council method: small peer groups that help you define your ideal role and hold each other accountable through the search.
Why I recommend it: Searching alone is the single biggest reason people stall out. Watch a couple of these, then start or join a council of three or four people. It changes the pace of everything.
