A concise but informative overview of AI ethics and policy. -/- Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring homeowners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, and voters in liberal democracies? Authored by experts in fields (...) ranging from computer science and law to philosophy and cognitive science, this book offers a concise overview of moral, political, legal and economic implications of AI. It covers the basics of AI's latest permutation, machine learning, and considers issues such as transparency, bias, liability, privacy, and regulation. -/- Both business and government have integrated algorithmic decision support systems into their daily operations, and the book explores the implications for our lives as citizens. For example, do we take it on faith that a machine knows best in approving a patient's health insurance claim or a defendant's request for bail? What is the potential for manipulation by targeted political ads? How can the processes behind these technically sophisticated tools ever be transparent? The book discusses such issues as statistical definitions of fairness, legal and moral responsibility, the role of humans in machine learning decision systems, “nudging” algorithms and anonymized data, the effect of automation on the workplace, and AI as both regulatory tool and target. (shrink)

Central to the ethical concerns raised by the prospect of increasingly autonomous military robots are issues of responsibility. In this paper we examine different conceptions of autonomy within the discourse on these robots to bring into focus what is at stake when it comes to the autonomous nature of military robots. We argue that due to the metaphorical use of the concept of autonomy, the autonomy of robots is often treated as a black box in discussions about autonomous military robots. (...) When the black box is opened up and we see how autonomy is understood and ‘made’ by those involved in the design and development of robots, the responsibility questions change significantly. (shrink)

The prospect of increasingly autonomous military robots has raised concerns about the obfuscation of human responsibility. This papers argues that whether or not and to what extent human actors are and will be considered to be responsible for the behavior of robotic systems is and will be the outcome of ongoing negotiations between the various human actors involved. These negotiations are about what technologies should do and mean, but they are also about how responsibility should be interpreted and how it (...) can be best assigned or ascribed. The notion of responsibility practices, as the paper shows, provides a conceptual tool to examine these negotiations as well as the interplay between technological development and the ascription of responsibility. To illustrate the dynamics of responsibility practices the paper explores how the introduction of unmanned aerial vehicles has led to (re)negotiations about responsibility practices, focusing particularly on negotiations within the US Armed Forces. (shrink)

Artificial Intelligence (AI) technologies offer new ways of conducting decision-making tasks that influence the daily lives of citizens, such as coordinating traffic, energy distributions, and crowd flows. They can sort, rank, and prioritize the distribution of fines or public funds and resources. Many of the changes that AI technologies promise to bring to such tasks pertain to decisions that are collectively binding. When these technologies become part of critical infrastructures, such as energy networks, citizens are affected by these decisions whether (...) they like it or not, and they usually do not have much say in them. The democratic challenge for those working on AI technologies with collectively binding effects is both to _develop_ and _deploy_ technologies in such a way that the democratic legitimacy of the relevant decisions is safeguarded. In this paper, we develop a conceptual framework to help policymakers, project managers, innovators, and technologists to assess and develop approaches to democratize AI. This framework embraces a broad sociotechnical perspective that highlights the interactions between technology and the complexities and contingencies of the context in which these technologies are embedded. We start from the problem-based and practice-oriented approach to democracy theory as developed by political theorist Mark Warren. We build on this approach to describe practices that can enhance or challenge democracy in political systems and extend it to integrate a sociotechnical perspective and make the role of technology explicit. We then examine how AI technologies can play a role in these practices to improve or inhibit the democratic nature of political systems. We focus in particular on AI-supported political systems in the energy domain. (shrink)