Since computers entered into the mainstream in the 1960s, the efficiency with which data could be processed has raised regulatory questions. This is well understood with respect to privacy. Data that was notionally public – divorce proceedings, say – had long been protected through the “practical obscurity” of paper records. When such material was available in a single hard copy in a government office, the chances of one’s acquaintances or employer finding it was remote. Yet when it was computerised and made searchable through what ultimately became the Internet, such practical obscurity disappeared. Today, high-speed computing poses comparable challenges to existing regulatory models in areas from securities regulation to competition law, merely by enabling lawful activities – trading in stocks, or comparing and adjusting prices, say – to be undertaken more quickly than previously conceived possible. Many of these questions are practical rather than conceptual. Nevertheless, current approaches to slowing down such decision-making – through circuit-breakers to slow or stop trading, for example – are unlikely to address all of the problems raised by the speed of AI systems.