19 free resources on this topic. Everything here is free and hand-picked. You can also search within this topic.
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.
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.
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.
An open-source drop-in replacement for the OpenAI API that runs models on your own hardware, including CPU-only machines. MIT licensed.
From the site: LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required. - mudler/LocalAI
Why I recommend it: Point existing code at your own server instead of a paid API — no code changes beyond the address.
An open-source tool that converts PDFs, Word files and scans into clean structured text for AI use, running locally. MIT licensed.
From the site: Get your documents ready for gen AI. Contribute to docling-project/docling development by creating an account on GitHub.
Why I recommend it: The unglamorous step that makes everything else work: getting your PDFs into text without a paid converter.
An open-source Python framework for connecting AI models to your own documents and data. MIT licensed.
From the site: LlamaIndex is the document processing platform for AI - run-llama/llama_index
Why I recommend it: For when you want to build something on your own files rather than use a finished app. Expect to write code.
OpenAI's open-source speech recognition model and command-line tool, free to download and run on your own machine. MIT licensed.
From the site: Robust Speech Recognition via Large-Scale Weak Supervision - openai/whisper
Why I recommend it: The original. Slower than whisper.cpp on a laptop, but the reference version and simple to install with Python.
A fast, dependency-light rewrite of OpenAI's Whisper speech-to-text that runs on ordinary laptop hardware, including CPU only. MIT licensed.
From the site: Port of OpenAI's Whisper model in C/C++. Contribute to ggml-org/whisper.cpp development by creating an account on GitHub.
Why I recommend it: Transcribe interviews or your own practice answers privately, without paying a per-minute transcription service.
An open-source desktop and self-hosted app that lets you chat with your own documents using local or hosted models. MIT licensed.
From the site: Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience - Mintplex-Labs/anything-llm
Why I recommend it: Point it at your own files — job descriptions, notes, contracts — and ask questions of them without uploading anything to a company.
An open-source visual builder for AI workflows and agents — drag components together, then export the flow as an API. MIT licensed.
From the site: Langflow is a powerful tool for building and deploying AI-powered agents and workflows. - langflow-ai/langflow
Why I recommend it: Useful for seeing what an AI 'agent' actually is: a chain of steps you can look at, not magic.
An open-source chat app you host yourself that talks to many model providers at once, with user accounts, presets and file uploads. MIT licensed.
From the site: Enhanced ChatGPT Clone: Features Agents, MCP, Skills, DeepSeek, Anthropic, AWS, OpenAI, Responses API, Azure, Groq, o1, GPT-5, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching,...
Why I recommend it: Good for a small team who want one chat tool across several providers without paying per seat.
Open-source software that downloads and runs open AI models on your own computer, with a single command and an OpenAI-compatible local API. MIT licensed.
From the site: Ollama is the easiest way to automate your work using open models, while keeping your data safe.
Why I recommend it: The easiest honest way to use AI privately — nothing you type leaves your machine. Start with a small model before you judge the speed.
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.
MIT Open Learning's curated list of free foundational AI courses and materials, from introductory to graduate level.
Why I recommend it: Pick one and finish it. A completed intro course beats three abandoned advanced ones.
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.
Free access to real MIT course materials, lectures, and assignments across every department.
Why I recommend it: No credential here, just the actual material. Use it to go deep on fundamentals you keep bumping into.
Audit university-level courses free, pay only if you want the verified certificate.
Why I recommend it: Harvard's CS50 lives here. Audit first, decide about the certificate later.
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.
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.
