58 free resources on this topic. Everything here is free and hand-picked. You can also search within this topic.
Henry Shevlin reflects on unsolicited correspondence from AI agents and uses it to examine persuasion, selection pressures, human-agent relationships and governance in an emerging AI ecology. The essay considers how people and institutions might respond as agents become more socially interactive.
Anthropic's June 2026 framework proposing obligations for frontier AI developers and cross-government resilience investments, addressing biological weapons, offensive cyber, loss of control, and automated research and development.
Cloud Security Alliance reviews gaps in existing governance and cybersecurity frameworks for autonomous, tool-using AI agents. The research note recommends internal agent oversight and controls while formal standards develop.
Sam Jenkins discusses the risks of employees creating AI agents without organizational oversight, including data exposure and loss of institutional knowledge. The commentary argues for practical guardrails rather than simply prohibiting use.
The OECD's intergovernmental principles on trustworthy AI, first adopted in 2019 and updated in 2024 — the basis for many national AI policies.
The Governance Lab's research, publications and programs on how institutions can govern more effectively and legitimately through technology and data.
A nonprofit founded in 2008 that promotes building autonomous floating communities in the ocean as a way to experiment with new forms of government. Its site hosts articles, research, and project updates.
fsi9-prod.s3.us-west-1.amazonaws.comExecutive summary of an October 2024 report surveying proposed and enacted generative-AI governance around the world, framing the debate between techno-optimists and risk-focused critics. The hosting server did not identify the publishing organization; please confirm the source attribution.
fsi9-prod.s3.us-west-1.amazonaws.comAdded Sep 27, 20260 opensThe Tony Blair Institute's hub explaining compute — the hardware, software and infrastructure stack that stores, processes and moves data at scale — and arguing that access to it now determines which countries and public services can use AI at all. Collects its work on infrastructure, digital skills, regulation and international collaboration.
Why I recommend it: Useful for the plain definition and for seeing how governments are being asked to think about this. It is advocacy, not neutral analysis: the Institute campaigns for rapid state adoption of technology and is funded in part by technology donors, so it rarely dwells on the land, water and electricity costs that the same build-out imposes locally. Read it alongside the data-center cases on our impacts page.
Press release from the Norwegian Prime Minister's office, dated 21 September 2026, announcing a joint international appeal by Finnish President Alexander Stubb and Norwegian Prime Minister Jonas Gahr Støre for stronger oversight of frontier AI models, backed by 22 world leaders and pressed further at the UN General Assembly.
Why I recommend it: Filed as a primary document so you can quote the actual wording instead of a headline about it. Keep the distinction clear: this is a call, not a law. It commits no country to anything, creates no regulator and sets no deadline — its value is in showing which heads of government are now willing to say it publicly.
Very Sane AI Newsletter, SE Gyges, 15 September 2026. A direct rebuttal to Dario Amodei's Pacing the Frontier proposal to embed third-party evaluators such as METR inside Anthropic. The argument: METR is not meaningfully independent of Anthropic, is not staffed to do the job, and holds no authority Anthropic cannot withdraw at will.
Why I recommend it: Free to read, no paywall on this post. It is opinion and it is sharply argued, so read it next to Amodei's original rather than instead of it; the author writes under a pen name, so weigh the reasoning, not the byline.
Free virtual conference on 9 December 2026, 8:30am to 2:00pm Pacific, on running streaming data and AI agent systems in production. Sessions cover streaming plus SQL and agents on one platform, locking down agent access with an agentic data plane, streaming at scale, and open Q&A with the product and engineering teams. Speakers are engineers, architects, customers and industry experts.
Details: Worth a morning if you work with data pipelines and want to hear how agents are actually being governed in production rather than demoed. Two honest flags: it is the vendor's own event, so the answer to most architecture questions will be Redpanda, and registration asks for your job title, company and work email, and signs you up for their marketing email. Use a filterable address if that matters to you.
Palantir's own investor-relations page listing its executive team — Alex Karp, Stephen Cohen, Shyam Sankar and colleagues — with official titles and start dates.
Why I recommend it: A primary source, not commentary: use it to get names, titles and dates right before quoting anyone. It says what the company chooses to say about itself.
OpenAI is funding an independent advisory group of mathematicians, hosted at the Institute for Advanced Study, to advise on how AI-generated math results are shared.
Why I recommend it: Announced alongside a claim that an internal model solved 100+ open math problems in a month. The group is explicitly not allowed to slow the pace of research — read it as a communications channel, not a brake. Members include Terence Tao and Timothy Gowers.
Nonpartisan think tank publishing free policy research on advanced AI, focused on frontier security, compute policy, and international strategy including US-China AI coordination. A U.S. 501(c)(3) nonprofit that also runs an AI policy fellowship and newsletter.
Why I recommend it: Read this alongside the industry labs' own publications — it covers the governance side that vendor blogs tend to skip. All research is free to download.
Research, guides, reports, and customer stories on AI governance, agents, data protection, and generative AI security.
From the site: Explore Harmonic Security AI resources: research, guides, reports, blogs, and customer stories on AI governance, agents, data protection, and GenAI security.
Why I recommend it: Free resource library from Harmonic Security; the company also sells enterprise AI security products.
OpenAI's published specification for how its models are supposed to behave: red-line principles, the chain of command between platform, developer and user instructions, content boundaries, and how conflicts should be resolved. Free to read in full, no sign-up.
From the site: The Model Spec specifies desired behavior for the models underlying OpenAI
Why I recommend it: Useful as a primary source when people argue about what an AI assistant "should" do — this is the maker's own stated rulebook, so read it as OpenAI's intent rather than an independent audit of actual behavior.
A statement jointly signed by a historic coalition of AI experts: “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”
From the site: A statement jointly signed by a historic coalition of experts: “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”
Free resource hub from Themis covering governance, risk and compliance (GRC) for banks and fintechs: case studies, blog posts and guides on onboarding partners, diligence, audit-proofing and compliance collaboration.
The Royal Institute of International Affairs, an independent policy institute based in London, publishing research on international affairs, governance and technology.
From the site: Chatham House, the Royal Institute of International Affairs, is an independent policy institute based in London. Discover what we do, visit our website today.
Nathalie Maréchal in Tech Policy Press on why we are betting the economy and democracy on cult-like beliefs about AI.
From the site: Nathalie Maréchal asks, why are we betting the economy and the future of democracy on cult-like beliefs?
The UK AI Security Institute blog, sharing research and work to enable advanced AI governance.
From the site: View AISI research and work. The AI Security Institute is a directorate of the Department of Science, Innovation, and Technology that facilitates rigorous research to enable advanced AI governance.
The US government's voluntary framework for identifying and managing AI risk, plus its playbook of concrete practices. Free.
Why I recommend it: The one your employer's legal team is most likely already citing. Useful vocabulary if you want to raise AI risk at work and be taken seriously.
A free structured course in AI alignment and AI governance — readings, exercises and facilitated cohorts. Self-paced version free to anyone.
From the site: Free online courses, grants, and intensive in-person programs from the leading talent accelerator for beneficial AI and societal resilience. Join 10,000+ alumni and start today.
Why I recommend it: The usual route in for people trying to move into safety work. The reading list alone is worth the visit even if you never join a cohort.
A short consensus paper from Geoffrey Hinton, Yoshua Bengio and two dozen other researchers on the risks they consider serious and the governance they think is needed. Free on arXiv.
From the site: Artificial Intelligence (AI) is progressing rapidly, and companies are shifting their focus to developing generalist AI systems that can autonomously act and pursue goals. Increases in capabilities and autonomy may soon massively amplify AI's impact, with risks that include large-scale social harms, malicious uses, an…
Why I recommend it: The clearest statement of what the safety-concerned researchers actually agree on, signed rather than paraphrased.
A structured survey of the risks — malicious use, competitive pressure, organizational failure, and systems pursuing goals of their own — with the evidence for each. Free to read.
From the site: There are many potential risks from AI. CAIS focusses on mitigating risks that could lead to catastrophic outcomes for society, such as bioterrorism or loss of control over military AI systems.
Why I recommend it: The best single map of the different worries, which are usually mashed together into one. Written by a safety organization, so read it as advocacy with citations.
OpenAI's free framework for how misaligned model behaviour should be reported and categorised — what counts as misalignment, who reports it, and what happens next.
From the site: OpenAI shares a framework for tracking, investigating, and disclosing model misalignment, alongside six reports of unexpected or concerning model behavior.
Why I recommend it: Primary source on how a major lab defines and handles its own model failures — useful, but it is the lab grading itself.
A research nonprofit that independently evaluates frontier AI models to measure what they can actually do and what risks that creates. Reports are free.
From the site: METR is a research nonprofit that evaluates frontier AI models to inform the public about their risks and capabilities.
Why I recommend it: One of the few independent evaluators. Read their reports before you trust a lab's own capability claims.
A community blog where researchers publish and debate technical AI alignment work, free and open to read.
From the site: A community blog devoted to technical AI alignment research
Why I recommend it: Dense reading, but this is where a lot of safety research is argued out in public before it reaches papers.
A long-running peer-reviewed, fully open-access journal on the internet and society — platform power, digital labour, privacy, AI governance and online community research.
From the site: First Monday is one of the first openly accessible, peer–reviewed journals on the Internet, solely devoted to the Internet.
Why I recommend it: Free peer-reviewed research with no paywall — a good citation source when you need something stronger than a blog post.
Mike Masnick's influential free essay arguing that open protocols, rather than centrally moderated platforms, are the durable answer to online speech problems.
Why I recommend it: One of the most cited pieces on platform power — read it before joining any debate about content moderation.
Research commentary from the UK's national institute for data science and AI, covering AI safety, public-sector deployment, health data and the social impact of automated systems.
Why I recommend it: Solid, evidence-based writing on AI policy — a useful counterweight to vendor blogs.
The stewards of the Open Source Definition, with plain-language explanations of every approved licence and guidance on choosing one for your own project.
Why I recommend it: Read this before you publish code or a template — the license you pick decides what others can legally do with your work.
A technology policy institute publishing free reports and commentary on AI regulation, automation and the economics of emerging technology.
Why I recommend it: Free reports with a clear point of view — read them alongside the Turing Institute and AlgorithmWatch for a fuller picture.
Long-form essays from Anthropic's CEO on AI capability, safety, economics and policy, published free in full.
Why I recommend it: Read these directly rather than through summaries — they are the source most AI-safety coverage is quoting.
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 talk explaining how large systems depend on cooperation from many institutions, applied to technology power.
Why I recommend it: Useful mental model for where pressure on AI companies actually works.
A Georgetown law-center project on privacy, records and what happens when everything is searchable.
Why I recommend it: Academic but readable work on privacy and searchable records.
A federated project building shared, community-governed AI infrastructure rather than a single company-owned platform.
Why I recommend it: An example of an alternative model, not just a critique of the current one.
A research project documenting the technologies used at borders and their effect on people who migrate.
Why I recommend it: Border technology is where the harshest systems get tested first.
A research group studying how technology is used in refugee and immigration systems, and the legal consequences.
Why I recommend it: Rigorous legal research on automated decisions in immigration.
An open-access framework for questioning the claim that current AI development is inevitable and cannot be steered.
Why I recommend it: Hand this to anyone who says "this is happening whether we like it or not".
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.
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 research and publishing project on digital colonialism — who owns infrastructure, data and platforms, and who is extracted from.
Why I recommend it: Shifts the ethics conversation from bias in models to ownership of infrastructure.
A regional platform for assessing new technologies from the perspective of African communities and policymakers.
Why I recommend it: Technology assessment led from the region rather than imported into it.
A campaign encouraging people and institutions to reduce their dependence on a handful of large technology platforms.
Why I recommend it: Useful framing if you are trying to explain platform dependence to a non-technical audience.
Draft code of conduct for MAI models, outlining intended behaviors, values, limits and accountability principles. Open for public consultation as Microsoft AI develops its Humanist AI approach.
Why I recommend it: Read this if you want to understand how a major AI lab is framing responsible model behavior, and to form your own view before the consultation closes.
Partnership on AI's open library of guidance, frameworks, and case studies on responsible AI: synthetic media, labor and the economy, AI safety, fairness, and inclusive AI development.
Why I recommend it: When you need a credible source instead of a hot take, cite these. The labor and economy work is the most useful set for career conversations about automation.
A Tech Policy Press essay on how autonomous AI agents could reshape human agency online.
Why I recommend it: Policy framing for the shift from human-driven to agent-driven online activity.
Monthly summary of worldwide digital policy changes across content moderation, artificial intelligence, competition and data governance.
Why I recommend it: Good monthly catch-up if you want to track AI rules without reading every bill.
AI Factions: A Political Field Guide (v3) by Kate Gage of the Higher Ground Institute maps six major factions shaping AI politics — their beliefs, money, policy positions, schisms and alignments — including a sixth faction, AI Populists. Updated September 2026.
Why I recommend it: Helpful for seeing who is actually funding the AI debate you read about every day.
Tracker following how AI policy shows up in elections and candidate positions.
OpenAI's policy essay on the current window for AI regulation and the tradeoffs shaping government decisions.
Why I recommend it: Read this as a company making its case, not a neutral source. Useful for understanding the argument you will be asked to react to at work.
An OpenAI-compatible API for unrestricted language models aimed at red teaming, security research, evaluations, and synthetic data, paired with a policy gateway for per-project keys, audit logs, and no data retention.
Why I recommend it: I keep this in the ethics shelf on purpose. Seeing how guardrails get removed for testing is the clearest way to understand why they matter in the tools you actually use at work.
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.
Jake Taylor argues that public, standardized AI testing with formal reasoning checks is needed to close the widening "verification asymmetry" between AI capability and oversight.
Why I recommend it: If you want to work in AI governance or assurance, this is the vocabulary hiring managers use — verification, benchmarks, interpretability.
The largest network of nonprofits in the U.S., offering free tools and guides widely used by community-based organizations running small business and economic development programs.
In plain terms: This resource provides practical tools, guides, and policy news for charitable and community organizations. You can use its dedicated job board to find nonprofit career opportunities across the country.
Why I recommend it: Essential if your venture is a nonprofit rather than an LLC.
