Death.--The absurd.--Moral luck.--Sexual perversion.--War and massacre.--Ruthlessness in public life.--The policy of preference.--Equality.--The fragmentation of value.--Ethics without biology.--Brain bisection and the unity of consciousness.--What is it like to be a bat?--Panpsychism.--Subjective and objective.

Thomas Nagel addresses the conflict between the claims of the group and those of the individual. Nagel attempts to clarify the nature of the conflict – one of the most fundamental problems in moral and political theory – and argues that its reconciliation is the essential task of any legitimate political system.

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)

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 paper surveys the current philosophical discussion of the ethics of risk imposition, placing it in the context of relevant work in psychology, economics and social theory. The central philosophical problem starts from the observation that it is not practically possible to assign people individual rights not to be exposed to risk, as virtually all activity imposes some risk on others. This is the ‘problem of paralysis’. However, the obvious alternative theory that exposure to risk is justified when its total (...) benefits exceed its total costs faces the standard distributional challenges of consequentialism. Forms of contractualism have been proposed as a solution, but how exactly such theories can be formulated remains problematic, especially when confronted with the difficult cases of mass, novel, risk such as climate change. (shrink)

The combination of increased availability of large amounts of fine-grained human behavioral data and advances in machine learning is presiding over a growing reliance on algorithms to address complex societal problems. Algorithmic decision-making processes might lead to more objective and thus potentially fairer decisions than those made by humans who may be influenced by greed, prejudice, fatigue, or hunger. However, algorithmic decision-making has been criticized for its potential to enhance discrimination, information and power asymmetry, and opacity. In this paper, we (...) provide an overview of available technical solutions to enhance fairness, accountability, and transparency in algorithmic decision-making. We also highlight the criticality and urgency to engage multi-disciplinary teams of researchers, practitioners, policy-makers, and citizens to co-develop, deploy, and evaluate in the real-world algorithmic decision-making processes designed to maximize fairness and transparency. In doing so, we describe the Open Algortihms project as a step towards realizing the vision of a world where data and algorithms are used as lenses and levers in support of democracy and development. (shrink)

PhD, Institute of Public Health, Unit of Medical Philosophy and Clinical Theory, University of Copenhagen, Øster Farimagsgade 5, P.O. Box 2099 1014 Copenhagen. Tel: +45 30 32 33 63; Email: s.lauridsen{at}pubhealth.ku.dk ' + u + '@ ' + d + ' '/ /- ->Citizens’ consent to political decisions is often regarded as a necessary condition of political legitimacy. Consequently, legitimate allocation of healthcare has seemed almost unattainable in contemporary pluralistic societies. The problem is that citizens do not agree on any (...) single principle governing priorities among groups of patients. The Accountability for Reasonableness framework suggests an ingenious solution to this problem of moral disagreement. Rather than advocating any substantive distributive principle, its advocates propose a feasible set of conditions, which, if met by decision makers at the institutional level, provide, so it is promised, legitimate decisions. While we agree that A4R represents an important contribution to the priority-setting debate, we challenge the framework in two respects. First, we argue that A4R, and more specifically the relevance condition of A4R, does not enable healthcare institutions to generally distinguish between relevant and irrelevant reasons for priority-setting. Second, we criticize Daniels’ and Sabin's argument that A4R and deliberative democracy constitute necessary and sufficient conditions of a feasible procedure for setting legitimate limits within healthcare. CiteULike Connotea Del.icio.us What's this? (shrink)

Health-care goods are goods with peculiar properties, and where they are scarce, societies face potentially explosive distributional conflicts. Animated public and academic debates on the necessity and possible justice of limit-setting in health care have taken place in the last decades and have recently taken a turn toward procedural rather than substantial criteria for justice. This article argues that the most influential account of procedural justice in health-care rationing, presented by Daniels and Sabin, is indeterminate where concrete properties of rationing (...) institutions are concerned. Such properties inscribe substantial norms into institutions. These norms can derive validity only from democratic majority decisions, which must be seen as an instance of pure procedural justice. We therefore have to move the discussion to a meta-level and ask how concrete properties of institutions are being chosen. I suggest four criteria for sufficiently democratic institutional design choice and conclude that as institutional properties are likely to have effects on the resulting distribution of health care, design choices should be empirically informed and taken both democratically and deliberately. (shrink)

This paper surveys the current philosophical discussion of the ethics of risk imposition, placing it in the context of relevant work in psychology, economics and social theory. The central philosophical problem starts from the observation that it is not practically possible to assign people individual rights not to be exposed to risk, as virtually all activity imposes some risk on others. This is the ‘problem of paralysis’. However, the obvious alternative theory that exposure to risk is justified when its total (...) benefits exceed its total costs faces the standard distributional challenges of consequentialism. Forms of contractualism have been proposed as a solution, but how exactly such theories can be formulated remains problematic, especially when confronted with the difficult cases of mass, novel, risk such as climate change. (shrink)

Several attempts have been made to transfer the concept of informed consent from medical and research ethics to dealing with affected groups in other areas such as engineering, land use planning, and business management. It is argued that these attempts are unsuccessful since the concept of informed consent is inadequate for situations in which groups of affected persons are dealt with collectively (rather than individually, as in clinical medicine). There are several reasons for this. The affected groups from which informed (...) consent is sought cannot be identified with sufficient precision. Informed consent is associated with individual veto power, but it does not appear realistic to give veto power to all individuals who are affected for instance by an engineering project. Most importantly, the concept of informed consent puts focus on the public’s acceptance of ready-made proposals rather than on its participation in the decision-making process as a whole, which includes the development of alternatives for the decision. Therefore, the concept of informed consent is not applicable to a company’s relations with groups and collectives. It may, however, be applicable to a company’s relations with individual persons such as customers and employees. (shrink)

Whilst public engagement in decisions concerning science and technology is widely extolled, research shows that the application of deliberative democratic theory remains – at least in Europe – highly constrained. Science and technology policy requires closer attention to the wider context of governance and the compatibility of public deliberation with established modes of policy-making.

The most widely debated conception of democracy in recent years is deliberative democracy--the idea that citizens or their representatives owe each other mutually acceptable reasons for the laws they enact. Two prominent voices in the ongoing discussion are Amy Gutmann and Dennis Thompson. In Why Deliberative Democracy?, they move the debate forward beyond their influential book, Democracy and Disagreement.What exactly is deliberative democracy? Why is it more defensible than its rivals? By offering clear answers to these timely questions, Gutmann and (...) Thompson illuminate the theory and practice of justifying public policies in contemporary democracies. They not only develop their theory of deliberative democracy in new directions but also apply it to new practical problems. They discuss bioethics, health care, truth commissions, educational policy, and decisions to declare war. In "What Deliberative Democracy Means," which opens this collection of essays, they provide the most accessible exposition of deliberative democracy to date. They show how deliberative democracy should play an important role even in the debates about military intervention abroad.Why Deliberative Democracy? contributes to our understanding of how democratic citizens and their representatives can make justifiable decisions for their society in the face of the fundamental disagreements that are inevitable in diverse societies. Gutmann and Thompson provide a balanced and fair-minded approach that will benefit anyone intent on giving reason and reciprocity a more prominent place in politics than power and special interests. (shrink)

This paper is a critique of Norman Daniels' and James Sabin's ‘Accountability for Reasonableness’ framework for making priority-setting decisions in health care in the face of widespread disagreement about values. Accountability for Reasonableness has been rapidly gaining worldwide acceptance, arguably to the point of becoming the dominant paradigm in the field of health policy. The framework attempts to set ground rules for a procedure that ensures that whatever decisions result will be fair, reasonable, and legitimate to the extent that even (...) those who would be adversely affected will have reason to abide by them. I argue that the framework's four conditions are inadequate to this task. While we certainly require a fair and legitimate procedure for making priority setting decisions in health care despite a lack of consensus on relevant ethical and political issues, we must significantly revise the four conditions, and we cannot avoid facing our substantive disagreements head on if we hope to arrive at decisions that would (and should) be acceptable to everyone. I offer two suggestions. First, there is need for greater public involvement in all stages of deliberation. Second, we should give up on the idea that we can simplify the task of democratic deliberation by disallowing particular kinds or reasons and types of reasoning. Reasons of all kinds should be on the table, but then should be judged on their merits, such as consistency, plausibility and explanatory power, without any regard for their alleged sources of authority. (shrink)

Accountability for Reasonableness has gained international acceptance as a framework to assist with resource allocation within healthcare. Despite this, one of the four conditions, the relevance condition, has not been widely adopted. In this paper I will start by examining the relevance condition, and the constraints placed on it by Daniels and Sabin. Following this, I review the theoretical limitations of the condition identified to date, by prominent critics such as Rid, Friedman, Lauridsen and Lippert—Rasmussen. Finally, I respond to Daniels (...) and Sabin’s enthusiasm for testing the accountability for reasonableness framework in different contexts, by evaluating the challenges of implementing the relevance condition within the NHS. I use the funding of treatments for patients on the basis of their exceptional circumstances as a case study to examine whether the relevance condition could be applied in practice. (shrink)

This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud detection, search engines, news trends, market segmentation and advertising, insurance or loan qualification, and credit scoring. These mechanisms of classification all frequently rely on computational algorithms, and in many cases on machine learning algorithms to do this work. In this article, I draw a distinction between three forms of opacity: opacity as intentional corporate or state (...) secrecy, opacity as technical illiteracy, and an opacity that arises from the characteristics of machine learning algorithms and the scale required to apply them usefully. The analysis in this article gets inside the algorithms themselves. I cite existing literatures in computer science, known industry practices, and do some testing and manipulation of code as a form of lightweight code audit. I argue that recognizing the distinct forms of opacity that may be coming into play in a given application is a key to determining which of a variety of technical and non-technical solutions could help to prevent harm. (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)

The ever-increasing application of algorithms to decision-making in a range of social contexts has prompted demands for algorithmic accountability. Accountable decision-makers must provide their decision-subjects with justifications for their automated system’s outputs, but what kinds of broader principles should we expect such justifications to appeal to? Drawing from political philosophy, I present an account of algorithmic accountability in terms of the democratic ideal of ‘public reason’. I argue that situating demands for algorithmic accountability within this justificatory framework enables us to (...) better articulate their purpose and assess the adequacy of efforts toward them. (shrink)

Norman Daniels’s theory of ‘accountability for reasonableness’ is an influential conception of fairness in healthcare resource allocation. Although it is widely thought that this theory provides a consistent extension of John Rawls’s general conception of justice, this paper shows that accountability for reasonableness has important points of contact with both utilitarianism and intuitionism, the main targets of Rawls’s argument. My aim is to demonstrate that its overlap with utilitarianism and intuitionism leaves accountability for reasonableness open to damaging critiques. The important (...) role that utilitarian-like cost-effectiveness calculations are allowed to play in resource allocation processes disregards the separateness of persons and is seriously unfair towards individuals whose interests are sacrificed for the sake of groups. Furthermore, the function played by intuitions in settling frequent value conflicts opens the door for sheer custom and vested interests to steer decision-making. (shrink)

In Between Facts and Norms, Jürgen Habermas works out the legal and political implications of his Theory of Communicative Action (1981), bringing to fruition the project announced with his publication of The Structural Transformation of the Public Sphere in 1962. This new work is a major contribution to recent debates on the rule of law and the possibilities of democracy in postindustrial societies, but it is much more. The introduction by William Rehg succinctly captures the special nature of the work, (...) noting that it offers a sweeping, sociologically informed conceptualization of law and basic rights, a normative account of the rule of law and the constitutional state, an attempt to bridge normative and empirical approaches to democracy, and an account of the social context required for democracy. Finally, the work frames and caps these arguments with a bold proposal for a new paradigm of law that goes beyond the dichotomies that have afflicted modern political theory from its inception and that still underlie current controversies between so-called liberals and civic republicans. The book includes a postscript written in 1994, which restates the argument in light of its initial reception, and two appendixes, which cover key developments that preceded the book. Habermas himself was actively involved in the translation, adapting the text as necessary to make it more accessible to English-speaking readers. (shrink)

This latest work from one of the world's leading political philosophers will appeal to audiences from a variety of fields, including philosophy, political science, women's studies, ethnic studies, sociology, and communications studies.

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)

The paper puts forward a pluralistic account of fairness within which concepts of equality of sacrifice and outcome, desert, and randomized outcomes within a fair framework all have their place. The distinction between efficiency and fairness is set out early on, and it is later argued that only efficient social arrangements can withstand the questioning about the fairness of the way they distribute their benefits to their beneficiaries and impose demands on those whose taxes pay for them that the modern (...) welfare state increasingly has to face. (shrink)

The paper puts forward a pluralistic account of fairness within which concepts of equality of sacrifice and outcome, desert, and randomized outcomes within a fair framework all have their place. The distinction between efficiency and fairness is set out early on, and it is later argued that only efficient social arrangements can withstand the questioning about the fairness of the way they distribute their benefits to their beneficiaries and impose demands on those whose taxes pay for them that the modern (...) welfare state increasingly has to face. (shrink)