Regulating the Algorithm

A Plain-English Guide to AI Laws in the UK, EU & US (The World of AI: Understanding Tomorrow, Today)

De: Julian Vexley

Narrado por: Steven Randolph

Regulating the Algorithm is a clear, practical guide to the fast-moving world of AI laws in the UK, EU, and United States. Written in plain language for business leaders, policy teams, lawyers, technologists, founders, and anyone who needs to turn principles into practice, it cuts through hype and legal jargon to explain what the new rules actually mean, why they were created, and how to comply without slowing innovation. Julian Vexley shows how three competing models are reshaping the global landscape: Europe’s risk-based AI Act, the United Kingdom’s pro-innovation, regulator-led approach, and the United States’ patchwork of executive orders, federal agency guidance, and ambitious state laws. You will learn how these frameworks define high-risk systems, mandate transparency, demand human oversight, govern data and model documentation, and draw hard lines around unacceptable uses. Just as important, you will see where the regimes overlap, where they diverge, and where the grey areas hide.

The book begins with why regulation is needed now, grounding the debate in real impacts: bias and discrimination, safety and reliability, deepfakes and misinformation, privacy and surveillance, IP and model training, security and export controls, liability and accountability. From there, Vexley maps each jurisdiction in turn. The EU chapters explain obligations across the AI lifecycle, conformity assessment, post-market monitoring, incident reporting, and penalties. The UK chapters translate high-level principles into the day-to-day expectations of sector regulators and show how “responsible innovation” works in practice. The US chapters decode federal directives and agency playbooks while making sense of state-level rules on biometrics, automated decision systems, privacy, and transparency.

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Makes Sense of the Fragmented US Landscape

The US regulatory environment can feel chaotic, but this book brings order to it. The discussion of executive orders, agency guidance, and state laws helped me understand how companies can navigate compliance even without a single federal AI statute.

Clear, Calm, and Free of Legal Jargon

As a non-lawyer working in tech, I appreciated how accessible this book is. The author explains regulatory obligations without drowning the reader in citations. It made AI compliance feel manageable rather than intimidating, which is rare in this field.

Exactly What Business Leaders Need Right Now

Regulating the Algorithm translates abstract policy debates into concrete guidance. The focus on real-world risks—bias, safety, transparency, and accountability—makes it relevant to executives and product teams alike. It’s not theoretical; it’s a handbook for decisions happening today.

A Practical Map Through Global AI Regulation

This book succeeds where many legal texts fail: it explains complex AI regulations in plain, usable language. I especially valued the side-by-side comparison of the EU, UK, and US approaches, which helped me understand not just the rules, but how to operationalize compliance without stalling innovation.

A Balanced View of Innovation and Oversight

What sets this book apart is its balanced tone. It doesn’t frame regulation as an obstacle but as a framework for trustworthy innovation. The UK’s pro-innovation approach is especially well explained and contrasted with the EU’s more prescriptive model.