The most widely used open-source framework for building and training AI models, with free tutorials, documentation and pre-trained models. Most AI research papers today are built on it.
Why I recommend it: Free and open source, now governed by the Linux Foundation's PyTorch Foundation — but Meta created it and remains its biggest contributor, so its direction still reflects big-tech priorities.
Google's open-source framework for building and training AI models, with free guides and pre-trained models. Once the industry standard, it's now used less in new research than PyTorch but still powers many production systems.
Why I recommend it: Free and open source, but it's a Google project — its development priorities follow Google's. For a new learner, PyTorch is the more common starting point in 2026.
Five plain-language protections people should expect from automated systems — safe systems, protection from discrimination, data privacy, notice and explanation, and a human alternative — each with a section on what organisations should do.
From the site: Among the great challenges posed to democracy today is the use of technology, data, and automated systems in ways that threaten the rights of the American public. Too often, these tools are used to limit our opportunities and prevent our access to critical resources or services. These problems are well documented. In…
Why I recommend it: Led by Alondra Nelson at the White House science office in 2022. It was never binding and has since been removed from whitehouse.gov, so this link goes to the official archive — still the clearest short statement of what people are owed.
NCDA article offering an Ability, Connection, and Expression framework for finding the real barrier behind a stalled search.
Why I recommend it: Details: run yourself through the three gaps before applying to more jobs — skills, network, or storytelling. The fix is different for each.
