Traditionally, the manufacturer/operator of a machine is held (morally and legally) responsible for the consequences of its operation. Autonomous, learning machines, based on neural networks, genetic algorithms and agent architectures, create a new situation, where the manufacturer/operator of the machine is in principle not capable of predicting the future machine behaviour any more, and thus cannot be held morally responsible or liable for it. The society must decide between not using this kind of machine any more (which is not a (...) realistic option), or facing a responsibility gap, which cannot be bridged by traditional concepts of responsibility ascription. (shrink)

This study builds on the work of contemporary civic republicans, supplying a detailed analysis of the concept of domination absent in the familiar accounts of political freedom as non-domination.

In Hobbes, freedom of choice requires nonfrustration: the option you prefer must be accessible. In Berlin, it requires noninterference: every option, preferred or unpreferred, must be accessible—every door must be open. But Berlin’s argument against Hobbes suggests a parallel argument that freedom requires something stronger still: that each option be accessible and that no one have the power to block access; the doors should be open, and there should be no powerful doorkeepers. This is freedom as nondomination. The claim is (...) that freedom as noninterference is an unstable alternative between freedom as nonfrustration and freedom as nondomination. (shrink)

This is the first full-length presentation of a republican alternative to the liberal and communitarian theories that have dominated political philosophy in recent years. The latest addition to the acclaimed Oxford Political Theory series, Pettit's eloquent and compelling account opens with an examination of the traditional republican conception of freedom as non-domination, contrasting this with established negative and positive views of liberty. The first part of the book traces the rise and decline of this conception, displays its many attractions, and (...) makes a case for why it should still be regarded as a central political ideal. The second part of the book looks at what the implementation of the ideal would imply for substantive policy-making, constitutional and democratic design, regulatory control and the relation between state and civil society. Prominent in this account is a novel concept of democracy, under which government is exposed to systematic contestation, and a vision of relations between state and society founded upon civility and trust. Pettit's powerful and insightful new work offers not only a unified, theoretical overview of the many strands of republican ideas, but also a new and sophisticated perspective on studies in related fields including the history of ideas, jurisprudence, and criminology. (shrink)

Traditionally, the manufacturer/operator of a machine is held (morally and legally) responsible for the consequences of its operation. Autonomous, learning machines, based on neural networks, genetic algorithms and agent architectures, create a new situation, where the manufacturer/operator of the machine is in principle not capable of predicting the future machine behaviour any more, and thus cannot be held morally responsible or liable for it. The society must decide between not using this kind of machine any more (which is not a (...) realistic option), or facing a responsibility gap, which cannot be bridged by traditional concepts of responsibility ascription. (shrink)

The notion of “responsibility gap” with artificial intelligence (AI) was originally introduced in the philosophical debate to indicate the concern that “learning automata” may make more difficult or impossible to attribute moral culpability to persons for untoward events. Building on literature in moral and legal philosophy, and ethics of technology, the paper proposes a broader and more comprehensive analysis of the responsibility gap. The responsibility gap, it is argued, is not one problem but a set of at least four interconnected (...) problems – gaps in culpability, moral and public accountability, active responsibility—caused by different sources, some technical, other organisational, legal, ethical, and societal. Responsibility gaps may also happen with non-learning systems. The paper clarifies which aspect of AI may cause which gap in which form of responsibility, and why each of these gaps matter. It proposes a critical review of partial and non-satisfactory attempts to address the responsibility gap: those which present it as a new and intractable problem (“fatalism”), those which dismiss it as a false problem (“deflationism”), and those which reduce it to only one of its dimensions or sources and/or present it as a problem that can be solved by simply introducing new technical and/or legal tools (“solutionism”). The paper also outlines a more comprehensive approach to address the responsibility gaps with AI in their entirety, based on the idea of designing socio-technical systems for “meaningful human control", that is systems aligned with the relevant human reasons and capacities. (shrink)

Value Sensitive Design (VSD) is an established method for integrating values into technical design. It has been applied to different technologies and, more recently, to artificial intelligence (AI). We argue that AI poses a number of challenges specific to VSD that require a somewhat modified VSD approach. Machine learning (ML), in particular, poses two challenges. First, humans may not understand how an AI system learns certain things. This requires paying attention to values such as transparency, explicability, and accountability. Second, ML (...) may lead to AI systems adapting in ways that ‘disembody’ the values embedded in them. To address this, we propose a threefold modified VSD approach: 1) integrating a known set of VSD principles (AI4SG) as design norms from which more specific design requirements can be derived; 2) distinguishing between values that are promoted and respected by the design to ensure outcomes that not only do no harm but also contribute to good; and 3) extending the VSD process to encompass the whole life cycle of an AI technology in order to monitor unintended value consequences and redesign as needed. We illustrate our VSD for AI approach with an example use case of a SARS-CoV-2 contact tracing app. (shrink)

Current advances in research, development and application of artificial intelligence systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies. Designed as a semi-systematic evaluation, this paper analyzes and compares 22 guidelines, highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of AI ethics. Finally, (...) I also examine to what extent the respective ethical principles and values are implemented in the practice of research, development and application of AI systems—and how the effectiveness in the demands of AI ethics can be improved. (shrink)

Imagine you are walking through a park. Suddenly, a mugger points a gun at you, threatening to shoot you if you do not hand over your valuables. Is this an instance of domination? Many authors working within the neo-republican framework - including Philip Pettit himself - are inclined to say 'yes'. After all, the mugger case seems to be a paradigmatic example of what it means to be at someone's mercy. However, I argue that this conclusion is based on a (...) misleading, interactional account of domination that misconceives its structural character. Domination, I maintain, is a structurally constituted form of power. Whether the mugger in the park dominates you or not can only be established by analysing the wider power structures in which your interaction is embedded. (shrink)

This article introduces readers to the special issue on Selected Issues in the Ethics of Artificial Intelligence. In this paper, I make a case for a wider outlook on the ethics of AI. So far, much of the engagements with the subject have come from Euro-American scholars with obvious influences from Western epistemic traditions. I demonstrate that socio-cultural features influence our conceptions of ethics and in this case the ethics of AI. The goal of this special issue is to entertain (...) more diverse views, particularly those from Africa; it brings together six articles addressing pertinent issues in the ethics of AI. These articles address topics around artificial moral agency, patiency, personhood, social robotics, and the principle of explicability. These works offer unique contributions for and from an African perspective. I contend that a wider engagement with the ethics of AI is worthwhile as we anticipate a global deployment of artificial intelligence systems. (shrink)

Our focus is the dialectic relationship between personal, social, collective, and institutional powers; that is the Proteus-like nature of power; “how power produces power”, how one form of power founds another form of it. Even the magic, “count as”, performative power of institutional acts is given from the institution to the lay-agent, but hidden is given to the institution by the acceptance and conformity of the mass of people. We provide an ‘ontology’ of personal powers, deriving from them (plus the (...) interdependencies relations) the most important forms of power at the interpersonal level (‘comparative power’, ‘power-over’, rewarding power’, ‘power of influencing’, ‘negotiation power’, ‘collective power’, ‘deontic power’). In the second part, we discuss a more institutional notion of power, the process of ‘empowerment’ and its relation with ‘permission’. (shrink)