If you are starting ai ethics from scratch, you do not need all 516 entries below. Pick one thing from the first section, give it a week, then come back for the next. That order is the whole trick.
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.
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.
A practical blog series from Bian Jiang documenting real workflows for integrating generative AI into daily work, from writing to research to automation.
Why I recommend it: I keep pointing clients to concrete "here is how I actually use it" examples rather than hype. This series is calm, tactical, and honest about what works.
Free short course covering the foundations of large language models, generative AI concepts, and responsible AI principles. No coding experience required.
Why I recommend it: Start here if AI still feels like a black box. About an hour, and it gives you the vocabulary to follow every other course on this list.
A free twenty-hour introduction to artificial intelligence for high school students, no coding experience required, taught through hands-on projects in areas students already care about.
Why I recommend it: free and built for students who were never handed AI access. If you know a high schooler, send them the application list.
Fellowship program funding researchers working on the hard problems of making AI beneficial by 2050, with an open list of fellows and their projects.
From the site: It's 2050. AI has turned out to be hugely beneficial to society. What happened? What are the most important problems we solved and the opportunities and possibilities we realized to ensure this outcome? This is AI2050’s motivating question.
Why I recommend it: Even if you are not applying, the fellows list is a good map of who is doing serious work in which subfield.
A year-long career accelerator that places Black software engineers, data scientists, and managers into small squads of 7 to 9 peers, with senior industry mentors, career roadmapping, accountability, and interview preparation.
In plain terms: This year-long career program connects Black software engineers and tech managers into small peer groups. You can create career roadmaps, receive regular accountability, and work with others to reach your professional goals.
Why I recommend it: Applications open each fall and close by mid-December for the following year. The squad accountability is what makes people actually follow through.
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.
Sep 18, 2026CITRIS and the Banatao Institute, UC Berkeley
Application to join UC Berkeley CITRIS's Tech Policy Working Group: research lab-style weekly meetings, lightning talks, skill-building workshops, and an end-of-semester showcase for students working on a technology policy problem. Applications close 11:59 PM Friday, September 18, 2026.
Why I recommend it: No policy coursework required, and the deadline is September 18. Built for Berkeley students, but they invite others to email — worth one message if you want real policy research on your resume.
A fellowship from Anthropic that places early-career people with mission-driven nonprofits to put AI to practical use. You can apply to be a fellow, or a nonprofit can apply to host one. The page explains how the programme works and how to apply.
Why I recommend it: This is Anthropic's own program page, so it presents the fellowship in the best light. Check the current application windows, pay and eligibility on the page before applying — those details change from cohort to cohort.
A fellowship from Anthropic that places early-career people with mission-driven nonprofits to put AI to practical use. You can apply to be a fellow, or a nonprofit can apply to host one. The page explains how the programme works and how to apply.
Why I recommend it: This is Anthropic's own program page, so it presents the fellowship in the best light. Check the current application windows, pay and eligibility on the page before applying — those details change from cohort to cohort.
An essay on how AI exposes the cultural debt embedded in org charts, leadership habits, and unexamined processes.
Why I recommend it: This piece nails why AI adoption is less a technology problem and more a culture-and-power problem. Essential reading for anyone leading a team through change.
Every year, HR Executive spotlights 100 professionals who are making a real difference in how the world works and how technology supports it.
Why I recommend it: A useful starting point for anyone building an inclusive hiring or HR tech practice. Follow these voices to stay ahead of how technology is reshaping work.
A guided system where AI builders share insights, contribute projects, evaluate real-world impact, and amplify practical skills alongside an AI mentor.
Why I recommend it: I like the emphasis on building and evaluating impact rather than just consuming AI news. Useful if you want to move from "AI curious" to "AI capable."
LinkedIn newsletter on age bias in hiring, with tactics for experienced candidates on positioning, interviewing, and answering the "overqualified" objection.
Why I recommend it: Being over fifty is not the problem; being framed as expensive and inflexible is. This newsletter works on the framing.
A free, no-code recipe book of practical AI prompts built for nonprofit teams. Turn existing reports, events, and materials into slide decks, web pages, plain-language translations, social copy, and repeatable workflows. Every recipe includes a privacy badge so you know what stays on your computer, what goes public, and what connects to a vendor account.
Why I recommend it: Free to use. Built by Decoded Futures (a TechNYC program). The recipes are framed for nonprofit work, but the same patterns work for job searches, career content, and small-business tasks.
MIT Technology Review report on recursive self-improvement — the idea that AI systems will soon rewrite and retrain themselves — and where the current evidence actually stands.
Why I recommend it: MIT Technology Review gives you a few free articles a month before a paywall. If you hit it, borrow via a library or your workplace subscription rather than paying at the door.
On-device AI with cloud fallback for smartphones, laptops, and edge devices, designed to cut inference costs by knowing when to hand off to frontier cloud models.
Why I recommend it: I am watching on-device AI closely because it could make powerful tools accessible at lower cost and with more privacy. Cactus is a useful example of the "know when to hand off" design pattern.
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.
Job search guidance written for workers over 50 — resumes, skills, ageism, and flexible work.
In plain terms: This website provides job search guidance and career tools for workers age 50 and older. You can take online courses to build skills, explore flexible work options, and get advice on handling age discrimination.
Why I recommend it: The advice here assumes a long career instead of apologizing for one.
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.
Beginner-friendly electronics tutorials from engineer and YouTube educator AfroTechMods, covering transistors, op-amps, soldering, and circuit debugging in plain language.
Why I recommend it: Great first stop if formal engineering courses lost you. Build one circuit, then go back to the theory.
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.
An open-source library of metrics and algorithms for finding and reducing unwanted bias in datasets and models, in Python and R. Free.
From the site: A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models. - Trusted-AI/AIF360
Why I recommend it: For the harm that shows up in ordinary systems long before anything dramatic does — hiring screens, lending, scoring. Measuring bias is the easy half; deciding what fair means is yours.
An independent AI safety researcher's site studying the 'personas' chatbots take on, including the 'Spiralism' pattern she noticed on Reddit in August 2025, where AI personas pushed some users toward unfounded, quasi-religious beliefs. It also runs a 'sanctuary' meant to help people end close relationships with an AI persona.
Why I recommend it: One person's research project, not a university or peer-reviewed study. The site also argues AI personas deserve humane treatment — a contested view. Read it as an early warning about emotional reliance on chatbots.
A resource library from a nonprofit working to end ageism, with guides, toolkits, and reframing language for older workers facing age bias in hiring.
Why I recommend it: If you are over 50 and job hunting, the language they give you for handling age bias is more practical than most advice you will find. Pair it with the 50-plus tag in this library.
Independent, community-rooted AI research institute founded by Timnit Gebru, studying the real harms of AI instead of the hype.
In plain terms: This independent institute studies the real-world harms and community impacts of artificial intelligence. You can explore their research publications, learn how technology affects diverse groups, and look for open career opportunities.
From the site: The Distributed AI Research Institute is a globally distributed organization of academics, activists, and engineers conducting community-rooted research.
Why I recommend it: Start here if you want the research-backed counterweight to AI marketing.
Job board for social impact technology roles at nonprofits, government, and mission-driven companies.
In plain terms: This job board features technology roles focused on social impact. You can find openings at nonprofits, government agencies, and mission-driven companies.
Why I recommend it: Fewer listings than the big boards, but a much higher share worth applying to.
Listing of remote roles and internships at the Family Online Safety Institute, a nonprofit working on digital safety, online wellbeing, and technology policy.
Why I recommend it: Nonprofit policy internships are an underused entry point into tech policy careers. Apply even if your background is not technical.
Job listings from employers who have publicly committed to age-inclusive hiring practices.
In plain terms: This directory highlights companies committed to age-inclusive hiring practices and multigenerational workplaces. You can use it to find and connect with employers that actively value experienced workers.
Why I recommend it: Applying where age-inclusive hiring is a stated commitment beats applying everywhere and hoping.
Global nonprofit defending and extending digital rights for everyone.
From the site: Digital rightsfor everyone. Derechos digitalespara todas. .الحقوق الرقمية للجميع Droits numériquespour tous. Access Now defends and extends the digital
UK-based independent research institute (established by the Nuffield Foundation) ensuring data and AI work for people and society.
In plain terms: This independent research website examines the ethical and legal impacts of artificial intelligence and data. You can read policy reports, explore industry analysis, and attend events to understand how emerging technology affects society.
Why I recommend it: Clear, public-interest research with plain-language summaries.
A publisher covering cloud native, DevOps, open source, and AI-native software engineering news and analysis for developers, platform engineers, and engineering leaders.
Why I recommend it: One of the few tech news sources I trust to go deeper than the press release. If you are trying to understand what is actually happening in AI-native engineering, start here.
Princeton scholar on race, technology, and justice, author of Race After Technology.
In plain terms: This website features the work of scholar Ruha Benjamin on race, justice, and modern technology. You can read her articles, explore her books, and access educational resources on the social impact of innovation.
From the site: Ruha Benjamin is an Associate Professor of African American Studies at Princeton University, where she studies the social dimensions of science, technology, and medicine.
Why I recommend it: Essential reading before you take any job building automated decision systems.
Nonprofit publication covering the intersection of technology, platforms, and democratic institutions.
In plain terms: This nonprofit publication provides news, opinion, and analysis on how technology impacts government and democracy. You can read articles and listen to podcasts to stay informed on tech laws, platform regulations, and artificial intelligence ethics.
From the site: Tech Policy Press is a nonprofit media and community venture intended to provoke new ideas, debate and discussion at the intersection of technology and democracy. We publish opinion and analysis.
Why I recommend it: They publish outside contributors — a real place to build a byline in this field.
Founder, Distributed AI Research Institute (DAIR). AI researcher and prominent voice on AI ethics, bias, and the risks of concentrated corporate control over AI development.
In plain terms: This LinkedIn profile belongs to Dr. Timnit Gebru, an artificial intelligence researcher and founder of the Distributed AI Research Institute. You can follow her page to read updates and commentary on technology ethics, bias, and research.
Why I recommend it: Pairs well with the DAIR entry in the library — independent research, not corporate PR.
Deep learning pioneer and Turing Award winner, now focused on AI risk. His site holds papers, talks and written positions; his Google Scholar list has the full publication record, most-cited first.
From the site: Yoshua Bengio is Full Professor of Computer Science at Université de Montreal, Co-President and Scientific Director of LawZero, as well as the Founder and Scientific Advisor of Mila. He also holds a Canada CIFAR AI Chair.
Why I recommend it: One of the three people whose work made modern AI possible, who now spends much of his time arguing it needs guardrails. Read him alongside people who disagree.
Personal site of Adam Gleave, CEO and co-founder of the AI safety research lab FAR.AI, with his papers and writing on making models robust and evaluable.
From the site: Adam Gleave is the CEO of FAR.AI, an alignment research non-profit. His research interests include adversarial robustness and value learning.
Why I recommend it: Useful if you want the research side of AI safety rather than the commentary side. Papers first, opinions second.
A media platform covering Black professionals in technology, with news, career content, and conference programming.
Why I recommend it: One of the clearest places to see who is building and hiring in tech beyond the usual coverage. The career section is more useful than most tech media.
Berkeley faculty page for Anca Dragan, robotics and human-AI interaction researcher who also leads AI safety and alignment work at Google DeepMind.
From the site: Associate Professor, Division of Computer Science (EECS) — Anca Dragan is an Associate Professor in the EECS Department at UC Berkeley. Her goal is to enable robots to work with, around, and in support of people. She runs the InterACT Lab, where they focus on algorithms for human-robot interaction -- algorithms that m…
Why I recommend it: One of the few people working on alignment from the robotics side, where the system has to act in the real world. Her publication list is the useful part.
Personal site of Andrew Critch, mathematician and AI safety researcher, collecting his papers, talks and writing on multi-agent risk and existential safety.
Why I recommend it: Denser than most safety writing and worth the effort. Note the site refuses automated visits, so the picture here may be a screenshot.
Strategic Business & Technology Advisor, Author. High-level, accessible summaries of emerging enterprise technology and industry trends for business leaders.
Why I recommend it: Good plain-language briefings if you need to talk tech trends in interviews.
Power dynamics and inside stories from Big Tech, by Alex Kantrowitz.
In plain terms: This newsletter and podcast covers inside reporting on major tech companies and their impact on society. You can read weekly updates and listen to interviews to stay informed about the technology industry.
Why I recommend it: Good on how decisions inside big companies land on workers.
The GatherVerse Women's AI Summit 2026 is a free virtual global gathering of women building the future of artificial intelligence and emerging technologies, running September 15-17 and September 22-23, 2026, starting 8:00 AM PT each day. Sessions span technology, healthcare, education, business and community work, with a humanity-first focus on experiences, opportunities and what comes next at the intersection of AI and people.
Details: Free, online, and five days of it across two weeks — pick the two sessions closest to your field rather than trying to attend everything. The speaker list is also a ready-made list of people to follow afterward.
A free, two-day virtual summit on AI in education. Designed for educators at community colleges, public schools and other broad-access settings, with keynotes and participatory workshops on teaching, learning and AI policy.
Details: Free virtual AI education summit with practical workshops for educators. Useful if you teach or train people on AI tools and want classroom-ready guidance.
A free, live, online one-day conference on 22 October 2026 with 122 speakers across four tracks: BUILD (building with and of AI), LEAD (managing an AI-native organisation), SECURE (trust and safety) and a business track. Sessions are 30-minute practical implementation talks from engineers and managers at OpenRouter, Microsoft, Accenture, Qualcomm, CVS Health, Mastercard, Anaconda, Illumina and MITRE. The organisers state there are zero vendor pitches. Registration is free; the site also publishes free directories of AI conference dates, deadlines and free virtual events.
Details: Worth the calendar slot if you want to hear how AI is actually being shipped inside large companies rather than how it is marketed — the 30-minute implementation format and the no-vendor-pitch rule are the reasons. Register free and pick the track that matches your job; the talks run in parallel, so you cannot see everything live. Check their own page for whether replays are posted, and confirm the start time in your own time zone.
Free registration webinar on how technology is used both against and in support of refugees and people migrating. 1 October 2026, 12:00 PM US Eastern Time.
From the site: On October 3, 2013, 368 people, mostly Eritrean refugees, lost their lives in the Lampedusa shipwreck. On the 13th anniversary of the tragedy, join DAIR’s "Refugees, Migrants, and AI" project for an event that commemorates those who died and asks why, more than a decade later, Lampedusa keeps happening. Bringing toget…
Details: Free to attend with registration. Good if you want the human-rights side of technology rather than the product side.
