A novel’s opening image, a self-driving car ploughing into traffic, captures a legal and moral knot that has only tightened as automation spreads across transport and other parts of life. High-profile lawsuits and investigations have repeatedly forced the question of blame into the courtroom: juries and regulators are now weighing whether manufacturers, software designers or the human occupants bear responsibility when partially autonomous systems fail. According to reporting on recent cases, manufacturers have been found partly liable for crashes involving assisted driving systems, prompting large damage awards and renewed calls for clearer regulation. (Sources: AP; Time) Designers and vendors are wrestling with the limits of their products even as they rush them to market. Regulators and safety investigators have criticised inadequate safeguards in many early deployments of driver-assist and self-driving technology, and lawsuits allege that marketing sometimes overstates capability while failing to make operational constraints clear to users. Industry incidents have also revealed failures of transparency and reporting that regulators say must be addressed before broader roll-outs resume. (Sources: AP; Axios; AP) That legal friction is instructive for policymakers debating how to govern more general-purpose artificial intelligence. Past tech regulation has favoured a distributed model of accountability: governments set rules and standards, manufacturers must certify compliance, and users face conditional privileges and duties. But AI complicates that bargain because models are updated continuously, embedded across services and often opaque even to their creators. Recent enforcement actions against autonomous vehicle firms illustrate the difficulty of applying traditional compliance frameworks to software that learns and shifts over time. (Sources: AP; AP) The role of the human operator remains central in many failure narratives. Investigations of crashes involving assisted-driving modes repeatedly show inattentive or distracted people in control at the moment of impact, underscoring that delegating responsibility to software without adequate human–machine interfaces or clear operational limits creates risk. Those patterns underline why any regulatory approach to AI must combine obligations on creators with measures that make deployment conditions and user responsibilities explicit and enforceable. (Sources: AP; Axios) History offers a useful analogy. Automobiles were once treated with laissez-faire optimism until mounting deaths forced the creation of licensing regimes, safety standards and a culture of regulated behaviour. That shared framework, standards for vehicles, obligations on makers and rules for drivers, did not eliminate harm but it distributed duties in ways that reduced it. Policymakers should study that evolution while recognising AI’s added complexity: unlike cars, models can be copied, fine-tuned and redeployed globally in hours. (Sources: Time; Axios) Practical steps flow from these lessons. Greater transparency about capabilities and limits, meaningful independent testing and enforced incident reporting would make harms easier to spot and remedy. Voluntary trust marks that signal human-authored content or audited systems can help consumers, but experience with automated transport shows voluntary measures alone often fall short; regulatory teeth and litigation incentives have proven decisive in driving corporate change. (Sources: AP; AP) Responsibility for the harms and benefits of AI will ultimately be shared across designers, deployers, regulators and users. As one of the characters in Bruce Holsinger’s Culpability observes, "Als are not aliens from another world" "They are things of our all-too-human creation. [They] will only be as moral as we design them to be. Our morality in turn will be shaped by what we learn from them and how we adapt accordingly." Until societies set clearer limits and accountabilities, widespread deployment is a licence to err rather than a guarantee of progress. (Sources: AP; AP)

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