60 free resources on this topic. Everything here is free and hand-picked. You can also search within this topic.
A Nonhuman Minds project combining philosophy, empirical benchmarks and engagement with AI companies on how AI alignment work can account for the welfare of animals and, potentially, AI systems. It publishes candidate commitments for model specs and constitutions.
Communications of the ACM research article synthesizing a 44-person workshop on AI, accessibility, and employment for disabled workers. It covers employment gaps, AI errors and hallucinations in situations where accuracy is critical, AI-scored video interviews that can screen out workers with non-normative speech or movement, accessibility overlays that may not work as advertised, and accountability gaps when inaccessible tools come from third-party vendors. Free to read.
A 2020 AIES paper by Abeba Birhane and Jelle van Dijk arguing that the robot-rights debate distracts from the harms AI systems already do to people, especially marginalized groups.
A Harvard Business School Working Knowledge article by Avery Forman (June 8, 2026) on research by Livia Alfonsi. A study of about 5,500 people in Kenya before and during the COVID-19 pandemic found that financial stress made most participants more willing to cheat; the article covers steps companies can take to deter cheating and support employees. Free to read.
Neuroscientist Anil Seth argues against AI products designed to be indistinguishable from real people on video, warning of scams, exploited loneliness and a weakened ability to tell reality from fantasy.
Philosopher Henry Shevlin argues that even if experts agreed some AI systems were conscious, society might still deny them moral consideration — drawing on how people treat animals they know to be sentient.
Jeff Sebo (September 17, 2026) on whether AI systems could matter morally: consciousness, sentience and agency are three distinct ways something can count — and in AI, unlike in animals, they may not come as a package.
A publication of expert dialogue and debate on the impacts of artificial intelligence, with articles from specialists across a range of fields.
A crowd-submitted directory of examples where AI tools are reported to have helped people, such as ElevenLabs voices for people with speech loss, Brainomix stroke scans, and John Deere See and Spray herbicide reduction. Visitors can browse top and new entries and submit their own.
Arianna Huffington's TIME essay, published October 2, 2026, on keeping human-generated awe in view alongside AI's capabilities.
Dylan Matthews' 2014 Vox profile of a philosopher who argues that harming characters in video games raises genuine moral questions — an early popular look at the ethics of digital minds.
An NCDA Career Convergence article by Safaa Amer (Oct. 2026) on how AI tools are reshaping career coaching — expanding access and automating tasks — and the AI literacy and ethical practice coaches need to use them responsibly.
A paper by Margaret Mitchell, Avijit Ghosh, Alexandra Sasha Luccioni and Giada Pistilli arguing that fully autonomous AI agents should not be developed. Drawing on prior scientific literature and current product marketing, the authors delineate levels of AI agent autonomy and show that risks to people increase as users cede more control, with safety risks to human life among the most concerning.
Consortium evaluating AI systems through faith and ethics perspectives. The page blocked a full check, so this description is based on the site's name.
Personal site of Basil C. Puglisi, MPA, author of Governing AI and creator of the Factics method. Free essays and frameworks on AI governance, AI literacy and measurable digital strategy.
We0 article (July 2026) on philosopher Harvey Lederman's research on the Confucian thinker Wang Yangming and its connection to Anthropic's alignment work on Claude. Published on the blog of an AI website-builder company.
UNESCO's global standard on AI ethics, adopted by 193 countries in 2021, covering values, principles and policy action areas for ethical AI.
A 2024 open-access article in Big Data & Society by Kerry McInerney arguing that the "AI arms race" narrative between the United States and China is deeply racialized, building on "Clash of Civilizations" rhetoric and older anti-Asian tropes such as techno-Orientalism and the Yellow Peril. The author coins "Yellow Techno-Peril" and offers recommendations for policymakers, journalists, and media organizations. Free to read (open access).
Why I recommend it: The arms-race framing shows up constantly in AI coverage. This paper names what that framing carries with it and gives concrete guidance for talking about competition without the racialized baggage.
A July 2026 open-access article in the Cambridge Forum on Technology and Global Affairs by Elisabeth Siegel (University of Oxford) examining how "hybrid epistemic experts" — figures straddling technical expertise, corporate leadership, and policy influence, with Eric Schmidt as the central case — constructed and amplified the "U.S.–China AI Race" narrative between 2015 and 2023. The article raises concerns about democratic governance and the concentration of AI knowledge production in private hands. Free to read (open access).
Why I recommend it: Explains how the AI race narrative was built by people who sit in boardrooms and policy rooms at the same time. Read it alongside the Yellow Techno-Peril paper for two complementary critiques of the same framing.
University of Delaware article on what science fiction portrayals of AI can teach about real-world AI development and its societal questions.
Rutgers AI Ethics Lab's glossary entry on the ELIZA effect: the human tendency to read genuine understanding into a system that is only matching surface patterns, named after Joseph Weizenbaum's 1964 chatbot. Explains why it matters legally and ethically — people disclose more, attach emotionally, and decide based on false assumptions — and argues designs must not be built to imply empathy or consciousness.
Why I recommend it: Free, short, and from a university lab rather than a vendor — a good citation when you need a defensible definition. It is a working glossary, so entries carry a last-updated date and name no individual author; for the original argument, the further-reading link to Weizenbaum's 1976 book is free on the Internet Archive.
A project by educators and researchers sharing free curriculum, research and monthly programming that helps teachers and students question what a technology does to a classroom and a community, not just how to use it. Built on two stated assumptions: technologies are not neutral, and neither are the societies they enter.
Why I recommend it: Curriculum, book club and events are free; they also sell merchandise and offer paid professional development. Openly critical in stance, which is the point, so pair it with a source that argues the other way if you are writing policy.
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.
Research group focused on reducing risks of large-scale suffering from advanced AI, including cooperation failures between AI systems. Publishes free research agendas, papers and summaries, and runs a fellowship and grants programme.
From the site: We do research on how to best reduce suffering.
Why I recommend it: A niche corner of AI safety focused on suffering rather than extinction — useful if you want the full range of arguments, not just the headline ones.
Think tank writing on moral circle expansion — how societies decide which beings deserve moral consideration, including animals and potentially sentient AI systems. All posts, reports and survey data are free to read.
From the site: Sentience Institute is a interdisciplinary think tank researching long-term social and technological change, particularly moral circle expansion.
Why I recommend it: Takes questions most AI coverage skips — whether AI systems could ever warrant moral consideration — and treats them carefully rather than sensationally.
Online magazine of ideas and culture publishing long-form essays on philosophy, science, ethics, technology and society. Free to read.
From the site: Aeon is a magazine of ideas and culture. We publish in-depth essays from the world’s most incisive and ambitious thinkers, and a mix of original and curated videos — free to all.
Introductory resource hub for longtermism: explanations, FAQ, further reading and ways to get involved. Explores how protecting future generations can guide research, advocacy and policy today.
From the site: Longtermism is the view that positively influencing the long-run future is a key moral priority of our time.
Newsletter and blog covering transformative AI risk, AI alignment, forecasting, longtermism and how to navigate the century ahead. By Holden Karnofsky; posts are freely readable with an optional audio version.
From the site: For audio version, search for "Cold Takes Audio" in your podcast app
Academic site of Alice Crary, philosopher at The New School for Social Research and Oxford, writing on moral philosophy, feminism, critical theory, animal ethics and the legacy of positivism.
From the site: Alice Crary, University Distinguished Professor, NSSR
Site of Oxford philosopher Toby Ord, author of "The Precipice", with free papers and essays on existential risk and how to weigh long-term outcomes.
Why I recommend it: Several of his papers are downloadable free. Read him for the reasoning about risk, not for AI specifics.
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.
OpenAI's free alignment research hub, including reports documenting how its own models fail.
From the site: Research on aligning AI with human values and intent, and reports documenting model failures.
Why I recommend it: A lab publishing on its own safety work — valuable primary material, but not an independent audit.
A research institute publishing free books, articles and policy analysis on economics, technology and civil liberties from a market-liberal perspective.
From the site: Explore Independent Institute’s latest research, articles, and insights on policy, liberty, and economics. Stay informed with expert analysis and innovative solutions.
Why I recommend it: Openly ideological — read it alongside sources that argue the other side.
Eliezer Yudkowsky's collected essays on reasoning, bias and AI risk, free to read online in full.
From the site: Between 2006 and 2009, senior MIRI researcher Eliezer Yudkowsky wrote several hundred essays for the blogs Overcoming Bias and Less Wrong, collectively called
Why I recommend it: Long, opinionated and free. Read it for the thinking habits, not as settled fact.
Robin Hanson's long-running blog on why we believe and do what we do, and what our descendants might do — free to read.
From the site: This is a blog on why we believe and do what we do, why we pretend otherwise, how we might do better, and what our descendants might do, if they don't all die. Click to read Overcoming Bias, by Robin Hanson, a Substack publication with tens of thousands of subscribers.
Why I recommend it: Deliberately contrarian. Useful for pressure-testing your own assumptions.
The central free hub for effective altruism — essays, career guidance and research on how to do the most good with your time and money.
From the site: Effective altruism is a philosophy and a movement that asks the question: how can we do the most good with our time, money, and resources?
Why I recommend it: useful career thinking here, and a movement with real critics — read both.
A free academic paper examining whether effective altruism's focus on individual giving overlooks institutional and political change as the larger lever.
Why I recommend it: Useful counterweight if you have read the pro-EA material — it argues the case from inside academic philosophy rather than online debate.
A free explainer of Roko's Basilisk, the AI thought experiment about a hypothetical future superintelligence that would punish people who knew about it but did not help bring it into existence.
A free plain-language guide to online safety, digital personas, scams and self-defense in online spaces.
Why I recommend it: Share this with anyone who is nervous about putting themselves online for work.
Free journalism and analysis on nuclear risk, climate change and disruptive technologies including artificial intelligence, from the group behind the Doomsday Clock.
Why I recommend it: Good grounding if you want to argue about AI risk with facts rather than vibes.
A free, curated critical reading list on artificial intelligence from a computational cognitive scientist at Radboud University.
Why I recommend it: Read this before you repeat a claim about what AI can do.
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.
An open, freely shared company document setting out first principles for how a team uses AI in its work.
Why I recommend it: A useful template if your team needs its own AI ground rules.
A Substack essay from Prof. Pilyoung Kim on a recent study showing that warning users about sycophantic AI changes how they judge it — but not how much it shifts their views.
Why I recommend it: A sharp reminder that AI assistants can shape our opinions even when we know they are agreeing with us; relevant to anyone using AI for research or decisions.
A Substack essay from Ruben on privacy, data ownership, and the human side of digital trust.
Why I recommend it: Personal take on privacy that connects policy to everyday choices.
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.
A project exploring how to keep human values, agency and wellbeing at the center of technology.
Why I recommend it: Worth watching for anyone interested in human-centered tech policy and design.
Co-founder of the Center for Humane Technology; writes and speaks on technology's impact on attention and society.
Why I recommend it: A leading voice on humane technology and AI's societal effects.
Essay mapping the competing factions in the AI debate and what each one actually believes.
Why I recommend it: The clearest short explainer I have found for anyone confused by the AI shouting match.
A downloadable report from employee-rights firm Outten & Golden on trust in the workplace, covering surveillance, transparency, and worker protections.
Why I recommend it: Written by lawyers who represent employees, not employers. Worth reading before you sign anything that mentions monitoring.
Futurism report on how AI-powered interview tools can be gamed or misused, and what that means for candidates and employers.
Why I recommend it: Worth reading before you assume AI interview tools are neutral arbiters of talent.
An independent publication covering AI policy, safety, and the power dynamics of the AI industry.
Why I recommend it: Clear-eyed reporting on who is steering AI and why. I lean on it when the mainstream coverage feels like press releases.
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.
Research report analyzing 19,368 interviews to understand how generative AI is changing technical recruiting, integrity screening, and candidate evaluation norms.
Why I recommend it: This one matters for anyone hiring or being hired in tech right now. It surfaces the real tension between assistive AI tools and interview fairness.
Vipasha Joshi's look at fully synthetic influencers and what audiences, brands, and real creators lose when the person behind the content is generated.
Why I recommend it: Worth reading if you are building an audience. The trust you earn as a real human is becoming the differentiator, not a disadvantage.
Coverage of law firm founder John Morgan boasting on a podcast about camera-based monitoring of remote staff, after which 23 employees quit within the first week.
Why I recommend it: Monitoring policy is culture policy. Ask in interviews how remote work is measured - output or surveillance - and treat the answer as data about how you would be managed.
Trillions in compute commitments come due in 2027–2028. The Reset Wall reveals how the AI boom breaks, and when.
From the site: Trillions in compute commitments come due in 2027–2028. The Reset Wall reveals how the AI boom breaks, and when.
Why I recommend it: A clear-eyed look at where the AI build-out may hit a financing and infrastructure wall — useful context for anyone advising job seekers or founders betting on the sector.
Open-access book exploring the environmental and societal impacts of AI infrastructure — data centers, energy, labor, and the politics of large-scale computation.
From the site: Expanding Perspectives on Automation, Communication and Media
Why I recommend it: Open-access research on AI's physical footprint — great background for anyone advising on green tech, data-center careers, or responsible AI procurement.
An argument that humanities and social science training produces the judgment, ethics, and interpretive skill that technical teams need as software takes on more social consequence.
In plain terms: This interview explains why technology companies actively hire people with degrees in the humanities and social sciences. Use it to learn how your non-technical background and critical thinking skills can qualify you for tech industry jobs.
Why I recommend it: If you have a humanities degree and feel behind, this is your framing. Your degree is context and judgment, which technical teams are short on.
