Readable, high-signal books on how AI is built, deployed, governed, overhyped, and absorbed into work and culture.
“A deeply reported account of modern generative AI through OpenAI, labor, infrastructure, extraction, and institutional power.”
“A practical general-reader guide to working with AI as collaborator, coach, and cognitive tool.”
“A cognitive-science lens on how LLMs learned to talk and what that does and does not imply about machine intelligence.”
“Still one of the best sober explanations of what AI systems can do, where they fail, and why intelligence is hard.”
“A critical map of AI as material infrastructure: data, labor, minerals, classification, and power.”
“A still-relevant narrative account of bias, reward design, robustness, and the problem of aligning machine learning with human values.”