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Digital Colonialism and the Role of Local Intermediaries: Big Tech, Data Sovereignty and Human Rights in Africa
Research & Papers · paper
'Eugenics on steroids': the toxic and contested legacy of Oxford's Future of Humanity Institute
Technology & Ethics · Article
William Shockley: The Flawed Visionary Behind Silicon Valley
Technology & Ethics · Article
The Quality of Hire Predictor
Hiring Trends & Job Market Data · Tool
The Gentle Singularity
Technology & Ethics · Essay
WARNact.io — U.S. Layoff Tracker
Hiring Trends & Job Market Data · Tool
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Ask the library about workforce, startup, and technology trends
Answers come only from resources in this hub, with the sources listed underneath.
The Frist Center for Autism and Innovation at Vanderbilt University maintains this resource hub for employers and job seekers interested in neuroinclusive workplaces. It gathers tip sheets on managing autistic employees, the Neurodiversity @ Work and Autism @ Work playbooks developed with Disability:IN and University of Washington researchers, a six-module self-paced neurodiversity curriculum, profiles of companies with neurodiversity hiring programs such as Microsoft, SAP, EY, and JPMorgan Chase, and a section of resources for job seekers on preparing for employment. All materials are free to access.
A 2022 student post on Cornell's Networks course blog explaining Bayes' theorem and how it is used to update probabilities in AI systems such as spam filters and classifiers. Written by a student, not course staff.
MIT News covers Joy Buolamwini's Gender Shades research, which found three commercial facial-analysis programs had much higher error rates for darker-skinned women than for lighter-skinned men, and proposed a more balanced benchmark.
A Stanford research project page describing HomeBody, which gives vision-language models a humanoid robot body through persistent spatial memory and reusable skills, without training for each new environment. Results are the authors' own and include demo videos.
A library guide tracking major academic publishers' policies on AI use in research and writing, including rules on AI authorship, disclosure requirements and image generation, with links to each publisher's policy.
The hardware chapter of Stanford's annual AI Index report: data on AI chip performance, costs, and who controls the computing power behind modern AI.
Why I recommend it: Free to download. It's the institute's own synthesis, and some compute and investment figures come from data supplied by the companies being measured — the broad picture is reliable, the fine print less so.
Stanford HAI's annual flagship report tracking AI progress across research, the economy, education, policy, and public opinion. The 2025 edition compiles data on model capability, training costs, industry investment, and workforce effects, with downloadable charts and datasets.
Why I recommend it: Free to download from Stanford HAI. It is a self-published report from a university institute; figures are sourced within the report, but some industry-investment and capability numbers rely on data supplied by the companies being measured. Treat headline rankings as the report's own synthesis, not neutral fact.
Yale Insights on research by Yale SOM's Menaka Hampole and co-authors: when AI automates a task it fades from job descriptions, but workers often shift to other work and firms become more productive.
Why I recommend it: A readable summary of one study, written by the business school that produced it. Useful balance to "AI will take every job" headlines, but it is one data set, not the final word.
Funding page for Stanford Medicine's Upstream Research Center pilot grants, which back early-stage research on upstream causes of health such as work, income and community conditions.
Why I recommend it: Free to read and apply, but eligibility is limited — check whether you need a Stanford affiliation before spending time on an application.
Official site of MIT professor Sherry Turkle, who has spent decades studying how people relate to computers, phones and now AI companions. Books, talks and essays.
Why I recommend it: Start with her work on "artificial intimacy" if you want a careful, human-centerd counterweight to AI hype.
A roundup of 2026 hiring data — job openings, applications per role, skills-based hiring and time-to-hire — with the sources behind each figure.
Why I recommend it: Published by a university that sells degrees, so read the education-related claims with that in mind; check the linked original sources before quoting a number.
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.
The Institute for Advanced Study's free biographical page on John von Neumann, who joined its School of Mathematics at 30 — covering his work on quantum theory, game theory, the stored-program computer architecture nearly every machine still uses, and his wartime work.
Why I recommend it: Good background for anyone meeting "von Neumann architecture" for the first time. It is written by the institution that employed him, so it reads as tribute — his role in nuclear weapons work and his later strategic writing get far less space than the mathematics.
Stanford Digital Economy Lab working paper by Bharat Chandar and Bouke Klein Teeselink, separating what happens to jobs after a firm adopts generative AI into a company-wide productivity effect and changes in what specific kinds of workers are asked to do.
Why I recommend it: Free, with the full PDF on the page. It is a working paper dated 21 September 2026, meaning it has not been through peer review yet, so read it as early evidence. Useful because it does not answer 'will AI take jobs' — it asks which workers get asked to do more and which get asked to do less.
MIT Press's open-access programme: hundreds of scholarly books and journal articles you can read and download in full for free, legally, including work on computing, AI, economics and design.
Why I recommend it: Before you buy an academic book or hit a paywalled paper, check here and on the author's own page. Not the whole catalog is open, only the titles funded for it, so search the specific book rather than assuming.
The full report of MIT's Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training, published 13 August 2026 after five months of meetings and outreach. The committee — students, faculty from every school, and staff from the MIT Libraries and Teaching and Learning Lab — was charged with assessing current AI use, identifying teaching and assessment innovations, and proposing an AI use policy. It sets out eight guiding principles (be humble, be bold, put humanity front and centre, lean into learning, teach with intentionality, no one size fits all, augmentation not automation, think beyond the classroom) and three groups of recommendations. Free to read online and free to download, with appendices and an FAQ.
Why I recommend it: The most useful part is the principles section — 'augmentation not automation' and 'teach with intentionality' are phrases you can borrow directly when you have to argue an AI policy to a school, a manager or a client. Be straight about what it is, though: MIT examining MIT, written for a residential research university, so its recommendations do not transfer unchanged to a community college, a bootcamp or a workplace.
Stanford's Center for Research on Foundation Models runs HELM as a living benchmark for language and multimodal models. Rather than one score, it reports many models across many scenarios on multiple metrics — accuracy, calibration, robustness, fairness, bias, toxicity and efficiency — and publishes the leaderboards alongside the raw model outputs (predictions and prompts) so you can check a claim yourself instead of taking a number on trust. Separate leaderboards cover areas such as classic HELM, instruction-following, medical, legal and safety. All results and analysis are free to browse on the site, no account.
Why I recommend it: The place to go when a vendor quotes you a benchmark figure. HELM's real value is that it shows the prompts and the model's actual answers, so you can see what the score measured. Be aware of what it is not: it is a snapshot of the model versions and dates CRFM ran, so check the run date before comparing anything to a model released since, and a model missing from a leaderboard usually means nobody ran it, not that it failed.
Brookings' running collection of technology and innovation research, including AI policy, labour effects and governance. Free to read.
Why I recommend it: A steady source of policy research when you want something more careful than news coverage. Brookings is a think tank with its own funders and viewpoints.
Interdisciplinary Stanford research institute studying how digital technology and AI change work, productivity and shared prosperity, with public papers and data.
From the site: The Stanford Digital Economy Lab is an interdisciplinary research institute shaping a future where technology drives human well-being and shared prosperity.
Why I recommend it: Free to read. Useful when you want measured research on AI and jobs instead of headline claims — check the publication date on each paper, the field is moving fast.
Duke Law & Technology Review note by Alanna Potter examining why public benefit corporations appeal to technology companies and whether they meaningfully allow firms to prioritize social benefit alongside shareholder return. Free PDF.
#corporate governance#entrepreneurship#law#pbc#public benefit corporation#regulation#social responsibility#tech industry
Stanford professor who built ImageNet, co-directs Stanford's Human-Centered AI institute and co-founded the AI4ALL diversity pipeline program. Her faculty page collects the work; her Google Scholar list has the papers themselves.
From the site: Fei-Fei Li is part of Stanford Profiles, official site for faculty, postdocs, students and staff information (Expertise, Bio, Research, Publications, and more). The site facilitates research and collaboration in academic endeavors.
Why I recommend it: Start with ImageNet if you want to understand why the last decade of AI happened when it did. Google Scholar refuses automated visits, so that link may show no picture here.
MIT research group studying how digital technology and AI change work, wages and productivity, with published papers and reports.
From the site: The MIT Initiative on the Digital Economy (IDE) explores how people and businesses will work, interact, and prosper in the digital era.
Why I recommend it: This is measurement rather than prediction, which is rare in this subject. Go here when you want numbers on automation instead of opinions about it.
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.
News and recorded-talk archive from Berkeley's Simons Institute for the Theory of Computing, covering theory, cryptography and the maths under machine learning.
Why I recommend it: The recorded talks are free and often better than the paper. Skim the archive by program rather than by date.
Department site for one of the birthplaces of modern deep learning, with faculty pages, open research groups and course listings.
From the site: The University of Toronto
Why I recommend it: Where Hinton's group worked. Useful for finding the original papers and the people still there, rather than for courses you can enrol in.
MIT's combined catalogue of courses, programs and open learning materials across every department, with a filter for the free ones and for those offering certificates.
Why I recommend it: Use the "Free" filter first — there is an enormous amount of MIT teaching material at no cost, including full lecture notes and video.
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.
Stanford economist Charles I. Jones works out, in plain economic terms, how much money it would be worth spending to lower catastrophic risks from advanced AI — comparing it to the roughly 4 percent of GDP the U.S. effectively spent during Covid-19.
A CUNY initiative that integrates career connections into every stage of an undergraduate's journey, aiming to help more students graduate into careers with competitive salaries.
Why I recommend it: If you are a CUNY student or alumni adviser, this is the central hub for college-to-career programming across the system.
A free resource library from Harvard Law School's Program on Negotiation, with articles and guides on negotiation strategy, conflict resolution, and dealmaking.
Why I recommend it: The deepest free negotiation material I have found anywhere, and it is not limited to salary. Read one article before any offer conversation.
MIT economics working paper analyzing how automation technologies can be used to expand state surveillance and repression, and the economic conditions that make that more likely.
Why I recommend it: Dense, but the argument matters: the same tools sold as efficiency are also control tools. Read the introduction and conclusion first.
Harvard Ash Center essay arguing that generative AI adoption has been driven more by vendor hype and institutional pressure than measured results, with a look at what happens as expectations reset.
Why I recommend it: Useful counterweight when your employer says AI will replace your role next quarter. Ask what evidence they are working from.
Free, self-paced hands-on lab using ChatGPT, Claude, Gemini, NotebookLM, and Perplexity for real work tasks.
Why I recommend it: A recognizable university name on a free AI literacy course. Finish it with one work problem you solved using the tools so you have a story to tell.
Mentor-driven program for early-stage deep-tech and science startups run out of NYU Stern.
Why I recommend it: Best fit if you have real technical IP. Read the mentor list before applying and shape your application around who is actually in the room.
Harvard Business School AI Institute breakdown of new research on agentic AI: how autonomy and context integration shift the cost structure of knowledge work, expanding both productivity and the scope of what workers take on.
Why I recommend it: Read this before you assume AI just speeds up your current tasks. The useful takeaway for job seekers: agents lower the cost per step, so the valuable human skills become specifying goals clearly and verifying output. Practice describing outcomes, not keystrokes, and put "agent workflow design" language in your resume bullets.
MIT research lab exploring human-AI collaboration, alongside a joint fund with Berkman Klein supporting research on AI's ethical and governance challenges.
In plain terms: This academic research site shares news and projects focused on emerging technology, design, and artificial intelligence. You can explore articles on AI ethics and human collaboration, view new inventions, and find related job opportunities.
Why I recommend it: Browse their projects when you want to see what humane technology looks like in practice.
Harvard University center studying the ethics, governance, and societal impact of the internet and AI, and anchor institution for the Ethics and Governance of AI Fund.
In plain terms: This research center explores how artificial intelligence and the internet impact society, law, and ethics. You can read free policy publications, watch educational videos, find public events, and check for open job or fellowship opportunities.
Why I recommend it: Decades of open research and fellowships, much of it free to read.
Interdisciplinary Stanford institute advancing AI research, education, policy, and practice to improve the human condition, with strong ethics and governance focus.
In plain terms: This university center shares research, policy updates, and educational resources focused on artificial intelligence. You can browse an AI glossary, read industry reports, and explore professional courses or research fellowships.
Why I recommend it: Their policy briefs are readable and free — a good first stop if AI governance feels opaque.
MIT's resume guidance with samples by field, plus advice on translating technical projects and research into recruiter-readable bullets.
In plain terms: This guide from MIT outlines five practical steps for creating a clear, well-structured resume. You can use it to format your document, write strong bullet points about your accomplishments, and tailor your experience to specific job descriptions.
From the site: Five steps to writing a great resume. Your resume provides an overview of your experience and is often an employer's first impression of you.
Why I recommend it: Especially useful if your experience is projects and coursework rather than job titles.
UC Davis' resume walkthrough — building sections from scratch, describing experience with results, and adapting materials per role.
In plain terms: This guide shows you how to create a resume step by step. You can learn how to write each section, describe your work using results, and tailor your materials for specific jobs.
A tight pre-submission checklist from MIT — verify formatting, consistency, tense, and impact before you send a resume anywhere.
In plain terms: This practical checklist guides you through every section of a standard resume. Use it to check your formatting, proofread your verb tenses, and make sure your work experience shows clear results before applying.
From the site: Recruiters spend just a few seconds on average looking at a resume. Using a clear and consistent format helps.
Why I recommend it: Run this before every application. It catches what you stop seeing after the tenth draft.
Harvard's full undergraduate resume and cover letter handbook — formatting rules, action-verb lists, and annotated before/after examples across industries.
In plain terms: This guide provides formatting rules, action-verb lists, and sample resumes and cover letters across various industries. You can use the annotated before-and-after examples to write and format your own job applications.
Why I recommend it: The single best free resume handbook out there. Read the annotated examples twice.
Harvard Career Services' bullet-point resume template plus guidance on writing accomplishment statements that lead with impact.
In plain terms: This downloadable resume template is available in Microsoft Word and Google Docs formats. You can use its bullet-point layout to organize your experience and build a clear first draft.
From the site: Word (.docx) version. Accessible Word (.docx) version. Google Docs version. Use this bullet-point template to build out your first draft of your resume.
Stanford's step-by-step resume handout covering structure, section order, describing experience, and common formatting mistakes.
In plain terms: This guide walks you through the resume-writing process step by step. Use it to choose your section order, write clear descriptions of your experience, and avoid common formatting errors.
Stanford's full career resource hub — resume and cover letter handouts, interview prep, and industry guides, all free to the public.
In plain terms: This collection offers free guides, templates, and tools for every stage of the job search. You can use it to build your resume, write cover letters, explore different careers, and practice for upcoming interviews.
From the site: We have gathered a list of our favorite online career resources in one place. Whether you're exploring your career options, preparing to apply for jobs, or seeking to maximize your experience, you'll find valuable resources below to help you succeed.
UPenn's resume guide with samples across business, tech, nonprofit, and graduate-school paths, plus wording and layout standards.
In plain terms: This guide offers downloadable resume templates and section-by-section advice for different industries. You can customize the Word documents with your own experience and learn how to write effective bullet points.
From the site: Resume templates for Penn students that can be adjusted and customized across different fields and industries, each with guidance for every section.
Michigan's Career Center resume article — samples, section-by-section guidance, and tailoring advice for different industries.
In plain terms: This guide offers resume samples and step-by-step advice for writing each section. You can use it to build a clean resume and tailor your experience to specific industries.
Yale's guidance on specialized resume formats — federal, academic CV, consulting, tech, and nonprofit — and when each format is expected.
In plain terms: This guide explains how to format resumes for federal government positions, specific industries, and international jobs. You can use it to learn about the federal resume builder and find country-specific application advice.
From the site: Formats for federal government, academic, consulting, and other specialized resumes, including guidance on the USAJOBS resume builder.
Why I recommend it: Different sectors expect different formats. Match the format before you polish the words.
HBS podcast interview with the CEO of OneTen, a coalition of employers committed to hiring and advancing workers without four-year degrees into family-sustaining careers.
In plain terms: This podcast interview explains how major employers are shifting toward skills-based hiring instead of requiring college degrees. You can listen or read the transcript to learn how companies are opening career opportunities for workers without four-year degrees.
Why I recommend it: OneTen's employer coalition is a concrete target list. Search their partner companies when you job hunt.
Harvard Business School profile of Interapt, which trains and places people from economically overlooked regions into paid tech roles, with detail on how the earn-while-you-learn model is financed.
In plain terms: This interview explains how Interapt trains and places job seekers into paid technology roles without requiring a tech background. You can read it to understand how their apprenticeship model works and what they look for in applicants.
Why I recommend it: Proof that regional and rural talent gets hired when someone builds the bridge. Worth knowing if you are outside a tech hub.
A university overview of the durable skills a liberal arts education builds — writing, analysis, communication, adaptability — and how they map onto professional roles.
In plain terms: This article explains the practical skills a liberal arts degree builds, including clear writing, critical thinking, and adaptability. You can use it to see what employers look for and learn how to explain your broad background to hiring managers.
Why I recommend it: Translate each skill listed here into a bullet with a result attached. That is how a liberal arts degree stops sounding vague in interviews.
A free, clear PDF guide with strong resume samples for every experience level.
In plain terms: This resource provides free guides, formatting templates, and examples for resumes, CVs, and cover letters. You can review samples for different experience levels and download templates to write your own application materials.
From the site: A resume is a brief, informative document summarizing your abilities, education, and experience. It should highlight your strongest assets and differentiate you from other candidates. Used most …
Why I recommend it: Start here if you are staring at a blank page. Copy the structure, not the words.
