Download This PaperFraming Human-Automation Regulation: A New Modus Operandi from Cognitive Engineering
We Robot 2017 at Yale School of Law
64 Pages Posted: 28 Apr 2020
Date Written: March 23, 2017
Abstract
Human-automated systems are becoming ubiquitous in our society, from the one-on-one interactions of a driver and their automated vehicle to large-scale interactions of managing a world-wide network of commercial aircraft. Realizing the importance of effectively governing these human-automated systems, there been a recent renaissance of legal-ethical analysis of robotics and artificial-intelligence-based systems. As cognitive engineers, we authored this paper to embrace our responsibility to support effective governance of these human-automated systems. We believe that there are unique synergies between the cognitive engineers who shape human-automated systems by designing the technology, training, and operations, and the lawyers who design the rules, laws, and governance structures of these systems. To show how cognitive engineering can provide a foundation for effective governance, we define and address five essential questions regarding human-automated systems: 1) Complexity: What makes human-automation systems complex? 2) Definitions: How should we define and classify different types of human-autonomous systems? 3) Transparency: How do we determine and achieve the right levels of transparency for operators and regulators? 4) Accountability: How should we determine responsibility for the actions of human-automation systems? 5) Safety: How do human-automated systems fail? Our answers, drawn from the diverse domains related to cognitive engineering, show that care should be taken when making assumptions about human-automated systems, that cognitive engineering can provide a strong foundation for legal-ethical regulations of human-automated systems, and that there is still much work to be done by lawyers, ethicists, and technologists together.
Keywords: artificial intelligence, law, robotics, automation, autonomous, governance, policy, cognitive engineering
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