Since it appeared in 1971, John Rawls's A Theory of Justice has become a classic. The author has now revised the original edition to clear up a number of difficulties he and others have found in the original book. Rawls aims to express an essential part of the common core of the democratic tradition--justice as fairness--and to provide an alternative to utilitarianism, which had dominated the Anglo-Saxon tradition of political thought since the nineteenth century. Rawls substitutes the ideal of the (...) social contract as a more satisfactory account of the basic rights and liberties of citizens as free and equal persons. "Each person," writes Rawls, "possesses an inviolability founded on justice that even the welfare of society as a whole cannot override." Advancing the ideas of Rousseau, Kant, Emerson, and Lincoln, Rawls's theory is as powerful today as it was when first published. (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)

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences (...) affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms. (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)

Artificial Intelligence (AI) is already having a major impact on society. As a result, many organizations have launched a wide range of initiatives to establish ethical principles for the adoption of socially beneficial AI. Unfortunately, the sheer volume of proposed principles threatens to overwhelm and confuse. How might this problem of ‘principle proliferation’ be solved? In this paper, we report the results of a fine-grained analysis of several of the highest-profile sets of ethical principles for AI. We assess whether these (...) principles converge upon a set of agreed-upon principles, or diverge, with significant disagreement over what constitutes ‘ethical AI.’ Our analysis finds a high degree of overlap among the sets of principles we analyze. We then identify an overarching framework consisting of five core principles for ethical AI. Four of them are core principles commonly used in bioethics: beneficence, non-maleficence, autonomy, and justice. On the basis of our comparative analysis, we argue that a new principle is needed in addition: explicability, understood as incorporating both the epistemological sense of intelligibility (as an answer to the question ‘how does it work?’) and in the ethical sense of accountability (as an answer to the question: ‘who is responsible for the way it works?’). In the ensuing discussion, we note the limitations and assess the implications of this ethical framework for future efforts to create laws, rules, technical standards, and best practices for ethical AI in a wide range of contexts. (shrink)

Artificial intelligence (AI) and robotics are digital technologies that will have significant impact on the development of humanity in the near future. They have raised fundamental questions about what we should do with these systems, what the systems themselves should do, what risks they involve, and how we can control these. - After the Introduction to the field (§1), the main themes (§2) of this article are: Ethical issues that arise with AI systems as objects, i.e., tools made and used (...) by humans. This includes issues of privacy (§2.1) and manipulation (§2.2), opacity (§2.3) and bias (§2.4), human-robot interaction (§2.5), employment (§2.6), and the effects of autonomy (§2.7). Then AI systems as subjects, i.e., ethics for the AI systems themselves in machine ethics (§2.8) and artificial moral agency (§2.9). Finally, the problem of a possible future AI superintelligence leading to a “singularity” (§2.10). We close with a remark on the vision of AI (§3). - For each section within these themes, we provide a general explanation of the ethical issues, outline existing positions and arguments, then analyse how these play out with current technologies and finally, what policy consequences may be drawn. (shrink)

The debate about the ethical implications of Artificial Intelligence dates from the 1960s :741–742, 1960; Wiener in Cybernetics: or control and communication in the animal and the machine, MIT Press, New York, 1961). However, in recent years symbolic AI has been complemented and sometimes replaced by Neural Networks and Machine Learning techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such a debate has primarily focused on principles—the (...) ‘what’ of AI ethics —rather than on practices, the ‘how.’ Awareness of the potential issues is increasing at a fast rate, but the AI community’s ability to take action to mitigate the associated risks is still at its infancy. Our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers apply ethics at each stage of the Machine Learning development pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs. (shrink)

This book articulates a systematic vision of an international legal system grounded in the commitment to justice for all persons. It provides a probing exploration of the moral issues involved in disputes about secession, ethno-national conflict, "the right of self-determination of peoples," human rights, and the legitimacy of the international legal system itself. Buchanan advances vigorous criticisms of the central dogmas of international relations and international law, arguing that the international legal system should make justice, not simply peace among states, (...) a primary goal, and rejecting the view that it is permissible for a state to conduct its foreign policies exclusively according to what is in the "national interest." He also shows that the only alternatives are not rigid adherence to existing international law or lawless chaos in which the world's one superpower pursues its own interests without constraints. This book not only criticizes the existing international legal order, but also offers morally defensible and practicable principles for reforming it. Justice, Legitimacy, and Self-Determination will find a broad readership in political science, international law, and political philosophy. (shrink)

The capacity to collect and analyse data is growing exponentially. Referred to as ‘Big Data’, this scientific, social and technological trend has helped create destabilising amounts of information, which can challenge accepted social and ethical norms. Big Data remains a fuzzy idea, emerging across social, scientific, and business contexts sometimes seemingly related only by the gigantic size of the datasets being considered. As is often the case with the cutting edge of scientific and technological progress, understanding of the ethical implications (...) of Big Data lags behind. In order to bridge such a gap, this article systematically and comprehensively analyses academic literature concerning the ethical implications of Big Data, providing a watershed for future ethical investigations and regulations. Particular attention is paid to biomedical Big Data due to the inherent sensitivity of medical information. By means of a meta-analysis of the literature, a thematic narrative is provided to guide ethicists, data scientists, regulators and other stakeholders through what is already known or hypothesised about the ethical risks of this emerging and innovative phenomenon. Five key areas of concern are identified: informed consent, privacy, ownership, epistemology and objectivity, and ‘Big Data Divides’ created between those who have or lack the necessary resources to analyse increasingly large datasets. Critical gaps in the treatment of these themes are identified with suggestions for future research. Six additional areas of concern are then suggested which, although related have not yet attracted extensive debate in the existing literature. It is argued that they will require much closer scrutiny in the immediate future: the dangers of ignoring group-level ethical harms; the importance of epistemology in assessing the ethics of Big Data; the changing nature of fiduciary relationships that become increasingly data saturated; the need to distinguish between ‘academic’ and ‘commercial’ Big Data practices in terms of potential harm to data subjects; future problems with ownership of intellectual property generated from analysis of aggregated datasets; and the difficulty of providing meaningful access rights to individual data subjects that lack necessary resources. Considered together, these eleven themes provide a thorough critical framework to guide ethical assessment and governance of emerging Big Data practices. (shrink)

This theme issue has the founding ambition of landscaping Data Ethics as a new branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing, and use), algorithms (including AI, artificial agents, machine learning, and robots), and corresponding practices (including responsible innovation, programming, hacking, and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). Data Ethics builds on the foundation provided by Computer and Information (...) Ethics but, at the same time, it refines the approach endorsed so far in this research field, by shifting the Level of Abstraction of ethical enquiries, from being information-centric to being data-centric. This shift brings into focus the different moral dimensions of all kinds of data, even the data that never translate directly into information but can be used to support actions or generate behaviours, for example. It highlights the need for ethical analyses to concentrate on the content and nature of computational operations — the interactions among hardware, software, and data — rather than on the variety of digital technologies that enables them. And it emphasises the complexity of the ethical challenges posed by Data Science. Because of such complexity, Data Ethics should be developed from the start as a macroethics, that is, as an overall framework that avoids narrow, ad hoc approaches and addresses the ethical impact and implications of Data Science and its applications within a consistent, holistic, and inclusive framework. Only as a macroethics Data Ethics will provide the solutions that can maximise the value of Data Science for our societies, for all of us, and for our environments. (shrink)

The phenomenon of distributed knowledge is well-known in epistemic logic. In this paper, a similar phenomenon in ethics, somewhat neglected so far, is investigated, namely distributed morality. The article explains the nature of distributed morality, as a feature of moral agency, and explores the implications of its occurrence in advanced information societies. In the course of the analysis, the concept of infraethics is introduced, in order to refer to the ensemble of moral enablers, which, although morally neutral per se, can (...) significantly facilitate or hinder both positive and negative moral behaviours. (shrink)

Are wealthy countries' duties towards developing countries grounded in justice or in weaker concerns of charity? Justice in a Globalized World offers both an in-depth critique of the most prominent philosophical answers to this question, and a distinctive approach for addressing it.

The current challenges of implementing responsible innovation can in part be traced back to the assumptions behind the ways of thinking that ground the different pre-existing theories and approaches that are shared under the RI-umbrella. Achieving the ideals of RI, therefore not only requires a shift on an operational and systemic level but also at the paradigm-level. In order to develop a deeper understanding of this paradigm shift, this paper analyses the paradigm-level assumptions that are being brought forward by the (...) different conceptualizations of RI. To this purpose it deploys a pragmatic stance on paradigms that allows discerning ontological and axiological elements shared by the RI community and an accompanying critical hermeneutic research approach that enables the profiling of paradigmatic beliefs and assumptions of accounts of RI. The research surfaces the distance of four salient RI accounts from the currently dominant techno-economic innovation paradigm RI seeks to shift. With this, our contribution helps to raise the self-awareness of the RI community about their presuppositions and the paradigm level barriers and enablers to reaching the RI ideal. This insight is needed for a successful transition to responsible research and innovation practices. (shrink)

Very large databases are a major opportunity for science and data analytics is a remarkable new field of investigation in computer science. The effectiveness of these tools is used to support a “philosophy” against the scientific method as developed throughout history. According to this view, computer-discovered correlations should replace understanding and guide prediction and action. Consequently, there will be no need to give scientific meaning to phenomena, by proposing, say, causal relations, since regularities in very large databases are enough: “with (...) enough data, the numbers speak for themselves”. The “end of science” is proclaimed. Using classical results from ergodic theory, Ramsey theory and algorithmic information theory, we show that this “philosophy” is wrong. For example, we prove that very large databases have to contain arbitrary correlations. These correlations appear only due to the size, not the nature, of data. They can be found in “randomly” generated, large enough databases, which—as we will prove—implies that most correlations are spurious. Too much information tends to behave like very little information. The scientific method can be enriched by computer mining in immense databases, but not replaced by it. (shrink)

A. John Simmons is widely regarded as one of the most innovative and creative of today's political philosophers. His work on political obligation is regarded as definitive and he is also internationally respected as an interpreter of John Locke. The characteristic features of clear argumentation and careful scholarship that have been hallmarks of his philosophy are everywhere evident in this collection. The essays focus on the problems of political obligation and state legitimacy as well as on historical theories of property (...) and justice. Cumulatively the collection presents a distinctive social and political philosophy, exploring the nature of our most fundamental rights and obligations, and displaying the power and plausibility of Lockean ideal theory. (shrink)

Assuming that states will remain a permanent feature of our world, what is the ideal that we should hold out for the international order? An attractive proposal is that those peoples that are already organized under non-dominating, representative states should pursue a twin goal: first, arrange things so that they each enjoy the republican ideal of freedom as non-domination in relation to one another and to other multi-national and international agencies; and second, do everything possible and productive to facilitate the (...) representation of less fortunate peoples in non-dominating states and to incorporate them in a non-dominating international order. This republican ideal stands midway between a utopian ideal of cosmopolitan justice and a sceptical ideal of non-intervention. The article explores its attractions and the broad institutional measures that it would support. (shrink)

The notion of responsible innovation suggests that innovators carry additional responsibilities beyond those commonly suggested. In this paper, we will discuss the meaning of these novel responsibilities focusing on two philosophical problems of attributing such responsibilities to innovators. The first is the allocation of responsibilities to innovators. Innovation is a process that involves a multiplicity of agents and unpredictable, far-reaching causal chains from innovation to social impacts, which creates great uncertainty. A second problem is constituted by possible trade-offs between different (...) kinds of responsibility. It is evident that attributing backward-looking responsibility for product failures diminishes the willingness to learn about such defects and to take forward-looking responsibility. We will argue that these problems can be overcome by elaborating what it is exactly that innovators are responsible for. In this manner, we will distinguish more clearly between holding responsible and taking responsibility. This opens a space for ‘supererogatory’ responsibilities. Second, we will argue that both innovation processes and outcomes can be objects of innovators’ responsibility. Third, we will analyze different kinds of responsibility and show that the functions of their attribution are not necessarily contradictory. Based on this conceptual refinement, we will argue that accountability, responsibility-as-virtue and the willingness to take responsibility are crucial for responsible innovation. (shrink)

Data science, and the related field of big data, is an emerging discipline involving the analysis of data to solve problems and develop insights. This rapidly growing domain promises many benefits to both consumers and businesses. However, the use of big data analytics can also introduce many ethical concerns, stemming from, for example, the possible loss of privacy or the harming of a sub-category of the population via a classification algorithm. To help address these potential ethical challenges, this paper maps (...) and describes the main ethical themes that were identified via systematic literature review. It then identifies a possible structure to integrate these themes within a data science project, thus helping to provide some structure in the on-going debate with respect to the possible ethical situations that can arise when using data science analytics. (shrink)

Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining and fairness, accountability and transparency machine learning, their practical implementation faces real-world challenges. For legal, institutional or commercial reasons, organisations might not hold the data on sensitive attributes such as gender, ethnicity, sexuality or disability needed to diagnose and mitigate emergent indirect discrimination-by-proxy, such (...) as redlining. Such organisations might also lack the knowledge and capacity to identify and manage fairness issues that are emergent properties of complex sociotechnical systems. This paper presents and discusses three potential approaches to deal with such knowledge and information deficits in the context of fairer machine learning. Trusted third parties could selectively store data necessary for performing discrimination discovery and incorporating fairness constraints into model-building in a privacy-preserving manner. Collaborative online platforms would allow diverse organisations to record, share and access contextual and experiential knowledge to promote fairness in machine learning systems. Finally, unsupervised learning and pedagogically interpretable algorithms might allow fairness hypotheses to be built for further selective testing and exploration. Real-world fairness challenges in machine learning are not abstract, constrained optimisation problems, but are institutionally and contextually grounded. Computational fairness tools are useful, but must be researched and developed in and with the messy contexts that will shape their deployment, rather than just for imagined situations. Not doing so risks real, near-term algorithmic harm. (shrink)

This article provides an account of the value of privacy in securing the republican aims of self-government and conditions of non-domination. It describes how loss of privacy might lead to subjugation to dominating power. The republican concept of domination provides the foundation of a broad and coherent account of the value of privacy. One that encompasses circumstances in which the subject suffers interference as a result of the loss, is aware that he has suffered a loss of privacy, but suffers (...) no subsequent interference and is unaware that he has suffered any loss of privacy, and suffers no subsequent interference. Liberal accounts explain the value of privacy in the first two circumstances by pointing to the possible effect of the loss on the autonomy of the subject, but because they focus on autonomy are unable to explain why privacy is valuable where an agent is unaware of the loss. The republican account provided here explains why loss is harmful in all three circumstances. The final part of the article argues that because privacy is a pre-requisite for effective participation in political life, and republicans consider such participation to be the essence of self-government and the means through which a polity can secure conditions of freedom, in a republican democracy individual privacy will be seen as a collective good. (shrink)

Arbitrary state and corporate powers are helping to turn the Internet into a global surveillance dragnet. Responses to this novel form of power have been tepid and ineffective. Liberal critiques of surveillance are constrained by their focus on privacy, security and the underlying presupposition that freedom consists only of freedom from interference. By contrast, (post)Foucauldian critiques rejecting liberalism have been well rewarded analytically, but have proven incapable of addressing normative questions regarding the relationship between surveillance and freedom. Quite apart from (...) these debates, neorepublicans have excavated a third concept of freedom, understood as non-domination. Could neorepublicanism overcome the limitations of liberal and (post)Foucauldian critiques of surveillance? We argue, positively, that neorepublicanism can accommodate much of the (post)Foucauldian analyses while also incorporating a normative critique of surveillance vis-à-vis freedom. We further argue, negatively, that surveillance power has outstripped the capacities of traditional republican institutional responses to domination. We conclude by considering ways in which neorepublicanism can be recalibrated to address the novelty of surveillance power while adhering to the ideal of non-domination. Two ways of addressing the problem are proposed: an offensive, dedicated surveillance antipower and a defensive republican amplification of privacy. (shrink)

Interest in republicanism as a political theory has burgeoned in recent years, but its implications for the understanding of law have remained largely unexplored. Legal Republicanism is the first book to offer a comprehensive, critical survey of the potential for creating republican accounts of fundamental issues in law and legal theory.

In the expansion of health ecosystems, issues of responsibility and sustainability of the data science involved are central. The idea that these values should be central to the practice of data science is increasingly gaining traction, yet there is no agreement on what exactly makes data science responsible or sustainable because these concepts prove slippery when applied to a global field involving commercial, academic and governmental actors. This lack of clarity is causing problems in setting goals and boundaries for data (...) scientific practice, and risks fundamental disagreement on governance principles for this emerging field. We will argue in this commentary for a commons analytical framework as one approach to this problem, since it offers useful signposts for how to establish governance principles for shared resources. (shrink)

In the late eighteenth century, Adam Smith significantly shaped the modern world by claiming that when people individually pursue their own interests, they are together led towards achieving the common good. But can a population of selfish people achieve the economic common good in the absence of moral constraints on their behavior? If not, then what are the moral conditions of market interaction which lead to economically efficient outcomes of trade? Answers to these questions profoundly affect basic concepts and principles (...) of economic theory, legal theory, moral philosophy, political theory, and even judicial decisions at the appellate level. Walter Schultz illustrates the deficiencies of theories which purport to show that markets alone can provide the basis for efficiency. He demonstrates that efficient outcomes of market interaction cannot be achieved without moral normative constraints and then goes on to specify a set of normative conditions which make these positive outcomes possible. (shrink)

Republicanism gives non-domination a central role. However, the modes of domination change over time. Expertise and anticipation have gained growing relevance in this respect. An emergent form of anticipation is pre-emption. This represents a peculiar ‘politics of time’, whereby an eschatological event is set and continuously postponed, past, present and future are no longer sequentially connected, and change reproduces the ruling order. Mainly addressed in relation to the military and security, pre-emption plays a growing role in the environmental field. The (...) paper discusses three examples: human enhancement, responsible innovation and the ‘ecomodernist’ take on the Anthropocene thesis. In all cases, what is promised on one side – respectively, empowerment, participation and care for nature – is denied on the other, hampering a transformative green politics. To circumvent this deadlock the paper explores the connection between non-domination and inoperosity. The latter does not mean passivity, resignation, but action free from the compulsion to achieve and expand. Non-domination requires recognition of limits as constitutive of the relationship with oneself and the world. On this view, a promising terrain of inquiry for civic republicanism is offered by ‘prefigurative’ mobilizations. (shrink)

« On this account, political participation is valued more for its instrumental than its intrinsic virtues ».