Free eBook: The Cambridge Handbook of the Law, Ethics and Policy of Artificial Intelligence
Newsletter Issue 62: A practical review of legal, ethical, and sectoral insights from The Cambridge Handbook of AI Law, Ethics, and Policy.
Artificial intelligence is changing how decisions are made in classrooms, hospitals, banks, courtrooms, and even conflict zones. This newsletter unpacks key takeaways from The Cambridge Handbook of the Law, Ethics and Policy of Artificial Intelligence, a collection that shows where law is catching up, where it is falling behind, and where careful thinking is urgently needed.
A Comprehensive Look at AI’s Legal Foundations
If one thing is clear from The Cambridge Handbook of the Law, Ethics and Policy of Artificial Intelligence, it is that the law on AI is extensively growing beyond the reach of regulators.
This intelligent book offers a clear tour through the minefield of legal issues raised by AI systems that increasingly operate in both public and private decision-making spaces.
The opening part of the Handbook gives readers a brisk yet substantial orientation, grounding every later legal discussion in technical detail, philosophical reflection, and an unapologetically practical ethics agenda.
Chapter 1 offers an insider tour of machine learning and reasoning, with Wannes Meert and colleagues stressing that trustworthy systems rely on rigorous testing for fairness, robustness, and explainability; their reminder that an elevator that never reaches the third floor counts as unfair makes the doctrine of equal treatment feel pleasantly concrete .
The same authors underline that no grand unified theory of artificial intelligence exists, which is music to the ears of lawyers who enjoy exploiting uncertainty for fun and legislative profit.
Vincent Müller then dives into the foundations of intelligence in Chapter 2, sliding between grand research dreams and the engineering reality that currently answers to the name technical artificial intelligence.
Müller’s observation that massive progress since 2015 still leaves the future of the field in glorious limbo will put a grin on every policy maker’s face.
Chapters 3 through 6 pivot to ethics, each author politely refusing to lecture the reader in abstract virtue and instead suggesting tools that regulators can actually deploy.
Buijsman, Klenk, and van den Hoven champion design for values, arguing that virtue ethics, deontology, and consequentialism remain useful but need translation into engineering checklists and interdisciplinary audits.
Their message is refreshingly pragmatic: ethics will not descend from ivory towers; it must be wired into product requirements and procurement contracts before the first line of code passes review.
Naudts and Vedder in Chapter 4 politely questions the myth that statistical neutrality equals justice.
They distinguish procedural fairness, which asks whether the pipeline treats individuals consistently, from substantive fairness, which inspects outcomes and asks whether society can live with them.
Most usefully for lawyers, they reject techno-solutionism and invite readers to examine the messy institutional context in which algorithms operate.
Chapters 5 asks who is responsible when autonomous systems misfire.
Lauwaert and Oimann dismantle the so called responsibility gap and cheerfully conclude that developers and users carry moral and legal duties even when control fizzles at the point of execution.
Their epileptic driver example illustrates that existing doctrines of foreseeability and risk already do the heavy lifting; the absence of a natural person in control does not grant immunity.
For the compliance officer this is both comforting and terrifying, because ignorance is rarely an affordable strategy.
Hasselbalch and Van Wynsberghe take readers to the sustainability frontier in Chapter 6.
They balance enthusiasm for artificial intelligence that optimises resource use against hard numbers on carbon emissions and supply chain extraction, then propose a sustainable approach that threads environmental, social, and governance objectives into algorithm life cycles.
Their verdict? An energy hungry AI model that undermines privacy still fails any serious public interest test.
Pierre Dewitte reminds us that every AI lifecycle decision must survive purpose limitation transparency and a someday inevitable Data Protection Impact Assessment.
He also points out that the Regulation was written to outlive fashions in engineering which explains why its open-ended clauses still bite even when data scientists insist that everything is anonymised.
Jan De Bruyne and Wannes Ooms deliver a sound tour of tort law headaches ranging from whether pure software can be classed as a defective product to the awkward reality that an automated vacuum cleaner might injure a passer-by without any human fingertip on a controller.
The chapter’s concluding takeaway is refreshingly direct liability rules already exist but legislators must polish definitions of fault and defect before a courtroom circus arrives.
Friso Bostoen invites readers to the economic arena where algorithmic pricing bots communicate with each other in milliseconds and competition authorities wonder if tacit collusion can be proved.
The chapter shows that restrictive agreements vertical or horizontal remain actionable and that abuse of dominance will still catch exclusionary or exploitative conduct.
Yet, it concedes that evidential burdens grow whenever market power hides behind machine-generated strategies.
Evelyne Terryn and Sylvia Martos Marquez list toolkits that ranges from the Unfair Commercial Practices Directive to the new Digital Services Act and explain how design nudges or outright dark patterns can trigger enforcement even when the interface looks delightfully pastel.
Their table of instruments ends with the AI Act itself confirming that consumer protection is fully intertwined with general safety rules and that user trust is a regulatory objective.
Intellectual property scholars note that patent and copyright regimes must handle both AI-enabled creativity and the code that powers it while the World Intellectual Property Organization collects global submissions at record pace, a statistic that underlines how urgently rights holders want predictable answers on inventorship originality and text-and-data mining.
Nathalie Smuha and Karen Yeung describe a layered statute that labels systems as unacceptable high or limited risk, demands technical documentation and fondly promises that harmonisation will preserve fundamental values.
Yet they warn that implementation will decide whether these aspirations travel from recital to reality and they hint that supervisory authorities will need big budgets to match their new workload.
The Handbook’s authors confirm that in education, the priority remains human development, not full automation, so any system that crunches homework data must serve pedagogy first.
They remind readers that fairness in adaptive learning tools is impossible without patient examination of training sets, interface nudges, and teacher workload.
They insist that ethical goals and didactical values belong in the same design brief, a message that looks mundane until one recalls how often procurement teams forget to invite parents and students to the table.
The chapter’s authors also tease policy makers with the admission that continual moral reflection will be needed long after the procurement contract is signed, because interests among learners, teachers, vendors, and regulators will drift over time and only an iterative governance loop will keep the system trustworthy.
That warning carries extra punch given the current rush to deploy graduation-prediction dashboards, many of which still treat correlation as destiny, so readers should expect regulators soon to ask for evidence that developers balanced data-driven accuracy against student autonomy.
Newsrooms, streaming services, and public broadcasters appear more animated, because the Media chapter gleefully lists every possibility from automated subtitles to generative first drafts, then pivots to the heavy part where freedom of expression, pluralism, and data protection demand safeguards that are both tough and transparent.
Editors are encouraged to treat recommender algorithms as editorial decisions that carry public interest obligations, meaning relevance scores must never become hidden gatekeepers for civic debate, and the forthcoming Digital Services Act and AI Act will supply auditors with new flashlights when they inspect disinformation filters.
The authors underline that productivity gains cannot justify opacity, so expect compliance teams to document training corpora, bias tests, and appeals procedures with the same care once reserved for libel checks, which is excellent news for lawyers who enjoy producing long annexes yet disastrous for interns hoping to finish early on Friday.
Verhenneman explains that clinical records still mix structured codes with long narrative notes, so any clinical decision AI system must either push clinicians toward fuller coding or invest in natural language parsing.
Universal vocabularies such as HL7 remain a necessity and the author adds that the machine rarely needs a patient’s name, only a stable link between observations and the right body on the ward.
Secondary use is encouraged, yet the GDPR demands pseudonymisation, careful purpose specification and a frank conversation about whether the hospital acts as data custodian rather than data owner, with patient autonomy setting the outer guardrails.
Langenbucher notes that banks already feed vast histories of accounts, trades and social signals into models that rank credit, flag money laundering and steer microsecond market orders.
The chapter calls this plain information processing and decision making, yet the legal tone is firm: even a AI chat bot suggesting investments inherits MiFID obligations, and a regulator using pattern recognition to hunt insider dealing must still justify false positives.
High frequency traders may quote latency in nanoseconds, but accountability will still be written in months on a supervisory calendar.
The chapter ends with a warning that ill-tested models can accelerate systemic shocks long before prudential ratios catch up.
Workplace analysis is equally pragmatic. Ponce Del Castillo and Taes map five main functions of algorithmic management: allocating shifts, setting piece rates, monitoring every click or wrist flick, benchmarking output and even terminating contracts when metrics slide.
The authors show that such systems quantify people at scale, inviting discrimination and eroding social protection if left unchecked.
Data minimisation and transparency rights under the GDPR help, but classic labour measures also matter: collective bargaining, works councils, and the new EU Platform Work Directive.
Their verdict is blunt yet optimistic; legal tools already exist, but unions and regulators must keep pace with vendor updates and corporate experiments.
Smuha’s public administration survey widens the lens, listing real tax, welfare and immigration tools that already influence life chances.
The author proposes constitutional review, data protection discipline and sector specific AI rules as a combined defence.
Yordanova reviews the core principles of international humanitarian law: distinction, proportionality, prohibition of unnecessary suffering and a duty of humanity.
She then underlines that lethal autonomous weapon systems would still need meaningful human control to meet these yardsticks and that lesser tools, from target recognition to logistics routing, raise compliance puzzles of their own.
The chapter’s practical takeaway is that military procurement must embed legal engineers long before deployment and that export controls will soon mirror dual-use regimes for cryptography and drones.
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