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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204 resources
Reporting on a community campaign against a data center's water and energy use during a drought.
Why I recommend it: The clearest single story on what a data center costs the place it lands in.
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.
How Te Hiku Media built te reo Māori speech recognition while keeping control of the community's own data.
Why I recommend it: The best short piece I know on data sovereignty done well.
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 opensA 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.
Reporting 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.
An investigation into healthcare workers striking over conditions and automation in mental-health care.
Why I recommend it: A reminder that automation debates land hardest on care work.
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 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 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.
Worker-led research and mental-health resources by and for the data annotators who label the material AI systems learn from.
Why I recommend it: Written by the workers themselves, not about them.
An association organizing the data-labeling workforce behind AI training data around pay, conditions and recognition.
Why I recommend it: A concrete answer to "who actually built this model" — and what they were paid.
An advocacy organization working on the human cost of mineral extraction that supplies the global electronics and AI supply chain.
Why I recommend it: The hardware behind AI starts in mines — this is the part of the story most coverage skips.
A translation project built for Ethiopian and other underserved languages by researchers from those language communities.
Why I recommend it: What language AI looks like when the people who speak the language build it.
A free, openly licensed image library replacing glowing-robot stock art with pictures that show how AI systems actually work.
Why I recommend it: Use these instead of robot stock photos in any deck or post about AI.
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 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 body of writing and practice on computing that lasts — repairable hardware, small software, low energy use.
Why I recommend it: The counterweight to "more compute solves everything".
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.
