Learning Resources
Curated courses, tutorials, books, and videos to accelerate your AI journey.
The Tech Coup: How to Save Democracy from Silicon Valley
Other · Marietje Schaake
Marietje Schaake's 2024 book argues that the concentration of AI and platform power in a small number of US technology companies represents a structural threat to democratic governance — not a future risk, but a present condition. Drawing on her decade as a European Parliament member working on digital policy, she makes the case for why voluntary commitments and self-regulation have failed, what effective binding regulation looks like, and why Europe's approach to AI governance — despite its imperfections — is closer to the right answer than the US hands-off model. Essential reading for anyone working on EU AI Act compliance who wants to understand the political economy behind the regulation.
Unmasking AI: My Mission to Protect What Is Human in a World of Machines
Other · Joy Buolamwini
Joy Buolamwini's 2023 book is part memoir, part technical analysis, part manifesto. Starting from her discovery that facial recognition systems failed to detect her face until she wore a white mask, she traces how AI bias is created, how it is obscured, and what it takes to contest it. The book covers Gender Shades, the regulatory debates that followed, and the broader question of who AI is built for. Buolamwini's writing is accessible without being simplified — she explains the technical mechanisms of bias clearly while maintaining the human stakes at the centre.
Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence
Other · Kate Crawford
Kate Crawford's 2021 book examines AI as a material system rather than a software abstraction — tracing the physical infrastructure of AI from lithium mines in Nevada to Amazon fulfilment centres to facial recognition deployments in schools. The argument is that AI is not an intangible technology but one built on extraction: of minerals, of labour, of data, of attention. For AI governance practitioners, this book provides the structural framing that most compliance frameworks omit: who bears the costs of AI development and who captures the benefits are governance questions as much as technical ones.
Human Compatible: Artificial Intelligence and the Problem of Control
Other · Stuart Russell
Stuart Russell's 2019 book is the clearest technical statement of why AI alignment is a genuine research problem, written by the author of the standard AI textbook. Russell argues that the conventional model of AI — specify an objective, build a system that maximises it — is fundamentally broken because it is impossible to fully specify human values in a machine-readable form. His proposed alternative: AI systems designed to be uncertain about human preferences and to seek human input rather than act autonomously on assumed objectives. Required reading before engaging with EU AI Act human oversight requirements — the regulation's language reflects precisely the concerns Russell articulates.