Luciano Floridi presents an innovative approach to philosophy, conceived as conceptual design. His starting-point is that reality provides the data which we transform into information. He explores how we make, transform, refine, and improve the objects of our knowledge, and defends the radical idea that knowledge is design.

The paper investigates the ethics of information transparency (henceforth transparency). It argues that transparency is not an ethical principle in itself but a pro-ethical condition for enabling or impairing other ethical practices or principles. A new definition of transparency is offered in order to take into account the dynamics of information production and the differences between data and information. It is then argued that the proposed definition provides a better understanding of what sort of information should be disclosed and what (...) sort of information should be used in order to implement and make effective the ethical practices and principles to which an organisation is committed. The concepts of “heterogeneous organisation” and “autonomous computational artefact” are further defined in order to clarify the ethical implications of the technology used in implementing information transparency. It is argued that explicit ethical designs, which describe how ethical principles are embedded into the practice of software design, would represent valuable information that could be disclosed by organisations in order to support their ethical standing. (shrink)

The paper offers a solution to the problem of specifying computational systems that behave in accordance with a given set of ethical principles. The proposed solution is based on the concepts of ethical requirements and ethical protocols. A new conceptual tool, called the Control Closure of an operation, is defined and used to translate ethical principles into ethical requirements and protocols. The concept of Generalised Informational Privacy (GIP) is used as a paradigmatic example of an ethical principle. GIP is defined (...) in such a way as to (i) discriminate specific cases in which an individual’s GIP can be infringed without accessing the individual’s data; (ii) separate unauthorised accesses to data that do not respect the right to GIP from access that do; and (iii) distinguish different degrees of GIP. Finally a camera phone is used to illustrate the proposed solution. (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)

In this paper we discuss the social and ethical issues that arise as a result of digitization based on six dominant technologies: Internet of Things, robotics, biometrics, persuasive technology, virtual & augmented reality, and digital platforms. We highlight the many developments in the digitizing society that appear to be at odds with six recurring themes revealing from our analysis of the scientific literature on the dominant technologies: privacy, autonomy, security, human dignity, justice, and balance of power. This study shows that (...) the new wave of digitization is putting pressure on these public values. In order to effectively shape the digital society in a socially and ethically responsible way, stakeholders need to have a clear understanding of what such issues might be. Supervision has been developed the most in the areas of privacy and data protection. For other ethical issues concerning digitization such as discrimination, autonomy, human dignity and unequal balance of power, the supervision is not as well organized. (shrink)

Purpose – Ubiquitous computing and “big data” have been widely recognized as requiring new concepts of privacy and new mechanisms to protect it. While improved concepts of privacy have been suggested, the paper aims to argue that people acting in full conformity to those privacy norms still can infringe the privacy of others in the context of ubiquitous computing and “big data”. Design/methodology/approach – New threats to privacy are described. Helen Nissenbaum's concept of “privacy as contextual integrity” is reviewed concerning (...) its capability to grasp these problems. The argument is based on the assumption that the technologies work, persons are fully informed and capable of deciding according to advanced privacy considerations. Findings – Big data and ubiquitous computing enable privacy threats for persons whose data are only indirectly involved and even for persons about whom no data have been collected and processed. Those new problems are intrinsic to the functionality of these new technologies and need to be addressed on a social and political level. Furthermore, a concept of data minimization in terms of the quality of the data is proposed. Originality/value – The use of personal data as a threat to the privacy of others is established. This new perspective is used to reassess and recontextualize Helen Nissenbaum's concept of privacy. Data minimization in terms of quality of data is proposed as a new concept. (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)

Through the exponential growth in digital devices and computational capabilities, big data technologies are putting pressure upon the boundaries of what can or cannot be considered acceptable from an ethical perspective. Much of the literature on ethical issues related to big data and big data technologies focuses on separate values such as privacy, human dignity, justice or autonomy. More holistic approaches, allowing a more comprehensive view and better balancing of values, usually focus on either a design-based approach, in which it (...) is tried to implement values into the design of new technologies, or an application-based approach, in which it is tried to address the ways in which new technologies are used. Some integrated approaches do exist, but typically are more general in nature. This offers a broad scope of application, but may not always be tailored to the specific nature of big data related ethical issues. In this paper we distil a comprehensive set of ethical values from existing design-based and application-based ethical approaches for new technologies and further focus these values to the context of emerging big data technologies. A total of four value lists were selected for this. The integrated list consists of a total of ten values: human welfare, autonomy, non-maleficence, justice, accountability, trustworthiness, privacy, dignity, solidarity and environmental welfare. Together, this set of values provides a comprehensive and in-depth overview of the values that are to be taken into account for emerging big data technologies. (shrink)

Currently, value sensitive design (VSD) does not commit to a particular ethical theory. Critiques contend that without such an explicit commitment, VSD lacks a methodology for distinguishing genuine moral values from mere stakeholders-preferences and runs the risk of attending to a set of values that is unprincipled or unbounded. We argue that VSD practitioners need to complement it with an ethical theory. We argue in favour of a mid-level ethical theory to fulfil this role.

A number of companies including Google and BMW are currently working on the development of autonomous cars. But if fully autonomous cars are going to drive on our roads, it must be decided who is to be held responsible in case of accidents. This involves not only legal questions, but also moral ones. The first question discussed is whether we should try to design the tort liability for car manufacturers in a way that will help along the development and improvement (...) of autonomous vehicles. In particular, Patrick Lin’s concern that any security gain derived from the introduction of autonomous cars would constitute a trade-off in human lives will be addressed. The second question is whether it would be morally permissible to impose liability on the user based on a duty to pay attention to the road and traffic and to intervene when necessary to avoid accidents. Doubts about the moral legitimacy of such a scheme are based on the notion that it is a form of defamation if a person is held to blame for causing the death of another by his inattention if he never had a real chance to intervene. Therefore, the legitimacy of such an approach would depend on the user having an actual chance to do so. The last option discussed in this paper is a system in which a person using an autonomous vehicle has no duty of interfering, but is still held responsible for possible accidents. Two ways of doing so are discussed, but only one is judged morally feasible. (shrink)

In this article I argue that the conception of discourse ethics that Jürgen Habermas advances in his seminar paper, ‘Discourse Ethics: Notes on a Program of Philosophical Justification’, is subject to significant revision in later work. The central difference has to do with the status of the universalization principle and its relationship to the ‘rightness’ validity claim. The earlier view is structured by a desire to provide a weak-transcendental defense of the universalization principle. The later revision, however, essentially undercuts the (...) basis of this argument, because it severs the conception of practical discourse from the analysis of speech acts. As a way of responding to the difficulties this creates, I propose a ‘reboot’ of the discourse ethics program. This involves reverting to the earlier, more Durkheimian and less Kantian, formulation of the theory. The result is a program that is no longer encumbered by sterile debates about the correct formulation of the universalization principle, but can plausibly claim to provide insight into the role that language-dependence plays in the development and entrenchment of increasingly pro-social behavior patterns within our institutions. (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)

In the original publication of this article, the Table 1 has been published in a low resolution. Now a larger version of Table 1 is published in this correction. The publisher apologizes for the error made during production.

Artificial Intelligence technology presents a multitude of ethical concerns, many of which are being actively considered by organizations ranging from small groups in civil society to large corporations and governments. However, it also presents ethical concerns which are not being actively considered. This paper presents a broad overview of twelve topics in ethics in AI, including function, transparency, evil use, good use, bias, unemployment, socio-economic inequality, moral automation and human de-skilling, robot consciousness and rights, dependency, social-psychological effects, and spiritual effects. (...) Each of these topics will be given a brief discussion, though each deserves much deeper consideration. (shrink)

Modern digital technologies—from web-based services to Artificial Intelligence (AI) solutions—increasingly affect the daily lives of billions of people. Such innovation brings huge opportunities, but also concerns about design, development, and deployment of digital technologies. This article identifies and discusses five clusters of risk in the international debate about digital ethics: ethics shopping; ethics bluewashing; ethics lobbying; ethics dumping; and ethics shirking.

Toleration is one of the fundamental principles that inform the design of a democratic and liberal society. Unfortunately, its adoption seems inconsistent with the adoption of paternalistically benevolent policies, which represent a valuable mechanism to improve individuals’ well-being. In this paper, I refer to this tension as the dilemma of toleration. The dilemma is not new. It arises when an agent A would like to be tolerant and respectful towards another agent B’s choices but, at the same time, A is (...) altruistically concerned that a particular course of action would harm, or at least not improve, B’s well-being, so A would also like to be helpful and seeks to ensure that B does not pursue such course of action, for B’s sake and even against B’s consent. In the article, I clarify the specific nature of the dilemma and show that several forms of paternalism, including those based on ethics by design and structural nudging, may not be suitable to resolve it. I then argue that one form of paternalism, based on pro-ethical design, can be compatible with toleration and hence with the respect for B’s choices, by operating only at the informational and not at the structural level of a choice architecture. This provides a successful resolution of the dilemma, showing that tolerant paternalism is not an oxymoron but a viable approach to the design of a democratic and liberal society. (shrink)

In this article, I outline a logic of design of a system as a specific kind of conceptual logic of the design of the model of a system, that is, the blueprint that provides information about the system to be created. In section two, I introduce the method of levels of abstraction as a modelling tool borrowed from computer science. In section three, I use this method to clarify two main conceptual logics of information inherited from modernity: Kant’s transcendental logic (...) of conditions of possibility of a system, and Hegel’s dialectical logic of conditions of in/stability of a system. Both conceptual logics of information analyse structural properties of given systems. Strictly speaking, neither is a conceptual logic of information about the conditions of feasibility of a system, that is, neither is a logic of information as a logic of design. So, in section four, I outline this third conceptual logic of information and then interpret the conceptual logic of design as a logic of requirements, by introducing the relation of “sufficientisation”. In the conclusion, I argue that the logic of requirements is exactly what we need in order to make sense of, and buttress, a constructionist approach to knowledge. (shrink)

In previous works (Floridi 2018) I introduced the distinction between hard ethics (which may broadly be described as what is morally right and wrong independently of whether something is legal or illegal), and soft or post-compliance ethics (which focuses on what ought to be done over and above existing legislation). This paper analyses the applicability of soft ethics to the General Data Protection Regulation and advances the theory that soft ethics has a dual advantage—as both an opportunity strategy and a (...) risk management solution. (shrink)

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a ‘good AI society’. To do so, we examine how each report addresses the following three topics: the development of a ‘good (...) AI society’; the role and responsibility of the government, the private sector, and the research community in pursuing such a development; and where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a ‘good AI society’. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach. (shrink)

This article reports the findings of AI4People, an Atomium—EISMD initiative designed to lay the foundations for a “Good AI Society”. We introduce the core opportunities and risks of AI for society; present a synthesis of five ethical principles that should undergird its development and adoption; and offer 20 concrete recommendations—to assess, to develop, to incentivise, and to support good AI—which in some cases may be undertaken directly by national or supranational policy makers, while in others may be led by other (...) stakeholders. If adopted, these recommendations would serve as a firm foundation for the establishment of a Good AI Society. (shrink)

A socio-cognitive approach to trust can help us envisage a notion of networked trust for multi-agent systems (MAS) based on different interacting agents. In this framework, the issue is to evaluate whether or not a socio-cognitive analysis of trust can apply to the interactions between human and autonomous agents. Two main arguments support two alternative hypothesis; one suggests that only reliance applies to artificial agents, because predictability of agents’ digital interaction is viewed as an absolute value and human relation is (...) judged to be a necessary requirement for trust. The other suggests that trust may apply to autonomous agents because predictability of agents’ interaction is viewed only as a relative value since the digital normativity that grows out of the communication process between interacting agents in MAS has always deal with some unpredictable outcomes (_reduction of uncertainty_). Furthermore, human touch is not judged to be a necessary requirement for trust. In this perspective, a diverse notion of trust is elaborated, as trust is no longer conceived only as a relation between interacting agents but, rather, as a relation between cognitive states of control and lack of control (_double bind_). (shrink)

In our information societies, tasks and decisions are increasingly outsourced to automated systems, machines, and artificial agents that mediate human relationships, by taking decisions and acting on the basis of algorithms. This raises a critical issue: how are algorithmic procedures and applications to be appraised and governed? This question needs to be investigated, if one wishes to avoid the traps of ICTs ending up in isolating humans behind their screens and digital delegates, or harnessing them in a passive role, by (...) curtailing their freedom and autonomy. (shrink)

The standard response to engineering disasters like the Deepwater Horizon case is to ascribe full moral responsibility to individuals and to collectives treated as individuals. However, this approach is inappropriate since concrete action and experience in engineering contexts seldom meets the criteria of our traditional moral theories. Technological action is often distributed rather than individual or collective, we lack full control of the technology and its consequences, and we lack knowledge and are uncertain about these consequences. In this paper, I (...) analyse these problems by employing Kierkegaardian notions of tragedy and moral responsibility in order to account for experiences of the tragic in technological action. I argue that ascription of responsibility in engineering contexts should be sensitive to personal experiences of lack of control, uncertainty, role conflicts, social dependence, and tragic choice. I conclude that this does not justify evading individual and corporate responsibility, but inspires practices of responsibility ascription that are less ‘harsh’ on those directly involved in technological action, that listen to their personal experiences, and that encourage them to gain more knowledge about what they are doing. (shrink)

An accountability-based privacy governance model is one where organizations are charged with societal objectives, such as using personal information in a manner that maintains individual autonomy and which protects individuals from social, financial and physical harms, while leaving the actual mechanisms for achieving those objectives to the organization. This paper discusses the essential elements of accountability identified by the Galway Accountability Project, with scholarship from the Centre for Information Policy Leadership at Hunton & Williams LLP. Conceptual _Privacy by Design_ principles (...) are offered as criteria for building privacy and accountability into organizational information management practices. The authors then provide an example of an organizational control process that uses the principles to implement the essential elements. Initially developed in the ‘90s to advance privacy-enhancing information and communication technologies, Dr. Ann Cavoukian has since expanded the application of _Privacy by Design_ principles to include business processes. (shrink)

This article is based on a roundtable held at the Association of Internet Researchers annual conference in 2017, in Tartu, Estonia. The roundtable was organized by the Oxford Internet Institute’s Digital Ethics Lab. It was entitled “Artificial Intelligence and the Good Society”. It brought together four scholars—Michael Zimmer, Stine Lomborg, Ben Zevenbergen, and Corinne Cath—to discuss the promises and perils of artificial intelligence, in particular what ethical frameworks are needed to guide AI’s rapid development and increased use in societies. The (...) paper covers three case studies. They give a distinct overview of the ethical issues raised by the use of AI at different levels of analysis: top-down application of AI, bottom-up use of AI, and how academics and governments have reacted to these new challenges. From the case studies, four areas emerged. They represent some of the most topical ethical questions related to AI: its uses, its users, its designers, and the data that fuel it. Each of them provided a specific subset of ethical concerns that need further investigation. In conclusion, three recommendations are formulated for researchers and regulators to ensure the AI has a net-positive impact on society. (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)

While organizations today make extensive use of complex algorithms, the notion of algorithmic accountability remains an elusive ideal due to the opacity and fluidity of algorithms. In this article, we develop a framework for managing algorithmic accountability that highlights three interrelated dimensions: reputational concerns, engagement strategies, and discourse principles. The framework clarifies that accountability processes for algorithms are driven by reputational concerns about the epistemic setup, opacity, and outcomes of algorithms; that the way in which organizations practically engage with emergent (...) expectations about algorithms may be manipulative, adaptive, or moral; and that when accountability relationships are heavily burdened by the opacity and fluidity of complex algorithmic systems, the emphasis of engagement should shift to a rational communication process through which a continuous and tentative assessment of the development, workings, and consequences of algorithms can be achieved over time. The degree to which such engagement is, in fact, rational can be assessed based on four discourse-ethical principles of participation, comprehension, multivocality, and responsiveness. We conclude that the framework may help organizations and their environments to jointly work toward greater accountability for complex algorithms. It may further help organizations in reputational positioning surrounding accountability issues. The discourse-ethical principles introduced in this article are meant to elevate these positioning contests to extend beyond mere adaption or compliance and help guide organizations to find moral and forward-looking solutions to accountability issues. (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)

This article argues that existing approaches to programming ethical AI fail to resolve a serious moral-semantic trilemma, generating interpretations of ethical requirements that are either too semantically strict, too semantically flexible, or overly unpredictable. This paper then illustrates the trilemma utilizing a recently proposed ‘general ethical dilemma analyzer,’ GenEth. Finally, it uses empirical evidence to argue that human beings resolve the semantic trilemma using general cognitive and motivational processes involving ‘mental time-travel,’ whereby we simulate different possible pasts and futures. I (...) demonstrate how mental time-travel psychology leads us to resolve the semantic trilemma through a six-step process of interpersonal negotiation and renegotiation, and then conclude by showing how comparative advantages in processing power would plausibly cause AI to use similar processes to solve the semantic trilemma more reliably than we do, leading AI to make better moral-semantic choices than humans do by our very own lights. (shrink)

Human rights theory and practice have long been stuck in a rut. Although disagreement is the norm in philosophy and social-political practice, the sheer depth and breadth of disagreement about human rights is truly unusual. Human rights theorists and practitioners disagree – wildly in many cases – over just about every issue: what human rights are, what they are for, how many of them there are, how they are justified, what human interests or capacities they are supposed to protect, what (...) they require of persons and institutions, etc. Disagreement about human rights is so profound, in fact, that several prominent theorists have remarked that the very concept of a “human right” appears nearly criterionless. In my 2012 article, “Reconceptualizing Human Rights”, I diagnosed the root cause of these problems. Theorists and practitioners have falsely supposed that the concept of “human right” picks out a single, unified class of moral entitlements. However, the concept actually refers to two fundamentally different types of moral entitlements: (A) international human rights, which are universal human moral entitlements to coercive international protections, and (B) domestic human rights, which are universal human moral entitlements to coercive domestic protections. Accordingly, I argue, an adequate “theory of human rights” must be a dual theory. The present paper provides the first such theory. First, I show that almost every justificatory ground given for “human rights” in the literature – such as the notion of a “minimally decent human life”, “urgent human interests”, and “human needs” – faces at least one of two fatal problems. Second, I show that after some revisions, James Griffin’s conception of “personhood” provides a compelling justificatory ground for international human rights. Third, I show that the account entails that there are very few international human rights – far fewer than existing human rights theories and practices suggest. Fourth, I show that there are reasons to find my very short list of international human rights compelling: “human rights justifications” for coercive international and foreign policy actions over the past several decades have consistently overstepped what can be morally justified, and my account reveals precisely how existing human rights theories and practices have failed to adequately grapple with these moral hazards. Finally, I outline an account of domestic human rights which fits well with many existing human rights beliefs and practices, vindicating those beliefs and practices, but only at a domestic level. (shrink)

As a way to address both ominous and ordinary threats of artificial intelligence, researchers have started proposing ways to stop an AI system before it has a chance to escape outside control and cause harm. A so-called “big red button” would enable human operators to interrupt or divert a system while preventing the system from learning that such an intervention is a threat. Though an emergency button for AI seems to make intuitive sense, that approach ultimately concentrates on the point (...) when a system has already “gone rogue” and seeks to obstruct interference. A better approach would be to make ongoing self-evaluation and testing an integral part of a system’s operation, diagnose how the system is in error and to prevent chaos and risk before they start. In this paper, we describe the demands that recent big red button proposals have not addressed, and we offer a preliminary model of an approach that could better meet them. We argue for an ethical core that consists of a scenario-generation mechanism and a simulation environment that are used to test a system’s decisions in simulated worlds, rather than the real world. This EC would be kept opaque to the system itself: through careful design of memory and the character of the scenario, the system’s algorithms would be prevented from learning about its operation and its function, and ultimately its presence. By monitoring and checking for deviant behavior, we conclude, a continual testing approach will be far more effective, responsive, and vigilant toward a system’s learning and action in the world than an emergency button which one might not get to push in time. (shrink)

The purpose of this article is to illuminate the conceptualisations and applications of the Belmont Report’s key ethical principles of respect for persons, beneficence, and justice based on a document analysis of five of the most relevant disciplinary guidelines on internet research in the social sciences. These seminal documents are meant to provide discipline-specific guidance for research design and implementation and are regarded as key references when conducting research online. Our analysis revealed that the principles of respect and beneficence were (...) explicitly conveyed in the documents analysed, offering nuanced interpretations on issues of informed consent, privacy, and benefits and risks as well as providing recommendations for modifying traditional practices to fit the online setting. However, the invocations of the principle of justice were rather implicit and reflect an important shift from the Belmont Report’s protectionist ethical position towards more situational and dialogic approaches. With the rapidly evolving nature of internet technologies, this analysis is projected to contribute to the ongoing developments in research ethics in the social sciences by outlining the tensions and implications of the use of the internet as a methodological tool. We also seek to provide recommendations on how disciplinary associations can proceed to facilitate ethically sensitive internet research. (shrink)

This is Jürgen Habermas's most concrete historical-sociological book and one of the key contributions to political thought in the postwar period. It will be a revelation to those who have known Habermas only through his theoretical writing to find his later interests in problems of legitimation and communication foreshadowed in this lucid study of the origins, nature, and evolution of public opinion in democratic societies.

This major work retraces the emergence and development of the Bourgeois public sphere - that is, a sphere which was distinct from the state and in which citizens could discuss issues of general interest. In analysing the historical transformations of this sphere, Habermas recovers a concept which is of crucial significance for current debates in social and political theory. Habermas focuses on the liberal notion of the bourgeois public sphere as it emerged in Europe in the early modern period. He (...) examines both the writings of political theorists, including Marx, Mill and de Tocqueville, and the specific institutions and social forms in which the public sphere was realized. This brilliant and influential work has been widely recognized for many years as a classic of contemporary social and political thought, of interest to students and scholars throughout the social sciences and humanities. (shrink)

Der kommunikativen Alltagspraxis müssen kognitive Deutungen, moralische Erwartungen, Expressionen und Wertungen einander durchdringen. Die Verständigungsprozesse der Lebenswelt bedürfen deshalb einer kulturellen Überlieferung auf ganzer Breite, nicht nur der Segnungen von Wissenschaft und Technik. So könnte die Philosophie ihren Bezug zur Totalität in einer der Lebenswelt zugewandten Interpretenrolle aktualisieren. Sie könnte mindestens dabei helfen, das stillgestellte Zusammenspiel des Kognitiv-Instrumentellen mit dem Moralisch-Praktischen und dem Ästhetisch-Expressiven wie ein Mobile, das sich hartnäckig verhakt hat, wieder in Bewegung zu setzen.

An account of the emergence and disintegration of.

With globalization, environmental problems and significant failures in corporate governance, business ethics is perceived to be of increasing importance. This is particularly so for IS because of the huge social effects of new technologies. Yet there has been relatively little discussion of ethics in the IS literature and no clear consensus has emerged. This paper argues that Habermas’s discourse ethics can make a major, and practical, contribution. After outlining some major ethical theories and how they have been interpreted in business (...) ethics and IS, the paper details the development of discourse ethics. Discourse ethics is different from other approaches to ethics as it is grounded in actual debates between those affected by decisions and proposals. Recognizing that the theory is rather abstract, the final section discusses how it can be pragmatized, with the help of existing soft and critical methodologies, to become a basis for business and IS ethics. (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)

The paper offers an analysis of the problem of integrating ethical principles into the practice of software design. The approach is grounded on a review of the relevant literature from Computer Ethics and Professional Ethics. The paper is divided into four sections. The first section reviews some key questions that arise when the ethical impact of computational artefacts is analysed. The inner informational nature of such questions is used to argue in favour of the need for a specific branch of (...) ethics called Information Ethics. Such ethics deal with a specific class of ethical problems and Informational Privacy is introduced as a paradigmatic example. The second section analyses the ethical nature of computational artefacts. This section highlights the fact that this nature is impossible to comprehend without first considering designers, users, and patients alongside the artefacts they create, use and are affected by. Some of key ethical concepts are discussed, such as freedom, agency, control, autonomy and accountability. The third section illustrates how autonomous computational artefacts are rapidly changing the way in which computation is used and perceived. The description of the ethical challenges posed to software engineers by this shift in perspective closes the section. The fourth and last section of the paper is dedicated to a discussion of Professional Ethics for software engineers. After establishing the limits of the professional codes of practice, it is argued that ethical considerations are best embedded directly into software design practise. In this context, the Value Sensitive Design approach is considered and insight into how this is being integrated into current research in ethical design methodologies is given. (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)

The concept of distributed moral responsibility (DMR) has a long history. When it is understood as being entirely reducible to the sum of (some) human, individual and already morally loaded actions, then the allocation of DMR, and hence of praise and reward or blame and punishment, may be pragmatically difficult, but not conceptually problematic. However, in distributed environments, it is increasingly possible that a network of agents, some human, some artificial (e.g. a program) and some hybrid (e.g. a group of (...) people working as a team thanks to a software platform), may cause distributed moral actions (DMAs). These are morally good or evil (i.e. morally loaded) actions caused by local interactions that are in themselves neither good nor evil (morally neutral). In this article, I analyse DMRs that are due to DMAs, and argue in favour of the allocation, by default and overridably, of full moral responsibility (faultless responsibility) to all the nodes/agents in the network causally relevant for bringing about the DMA in question, independently of intentionality. The mechanism proposed is inspired by, and adapts, three concepts: back propagation from network theory, strict liability from jurisprudence and common knowledge from epistemic logic. (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)

AI is revolutionizing everyone’s life, and it is crucial that it does so in the right way. AI’s profound and far-reaching potential for transformation concerns the engineering of systems that have some degree of autonomous agency. This is epochal and requires establishing a new, ethical balance between human and artificial autonomy.

Since approval of the EU General Data Protection Regulation (GDPR) in 2016, it has been widely and repeatedly claimed that the GDPR will legally mandate a ‘right to explanation’ of all decisions made by automated or artificially intelligent algorithmic systems. This right to explanation is viewed as an ideal mechanism to enhance the accountability and transparency of automated decision-making. However, there are several reasons to doubt both the legal existence and the feasibility of such a right. In contrast to the (...) right to explanation of specific automated decisions claimed elsewhere, the GDPR only mandates that data subjects receive meaningful, but properly limited, information (Articles 13-15) about the logic involved, as well as the significance and the envisaged consequences of automated decision-making systems, what we term a ‘right to be informed’. Further, the ambiguity and limited scope of the ‘right not to be subject to automated decision-making’ contained in Article 22 (from which the alleged ‘right to explanation’ stems) raises questions over the protection actually afforded to data subjects. These problems show that the GDPR lacks precise language as well as explicit and well-defined rights and safeguards against automated decision-making, and therefore runs the risk of being toothless. We propose a number of legislative and policy steps that, if taken, may improve the transparency and accountability of automated decision-making when the GDPR comes into force in 2018. (shrink)

This article argues that an ethical framework will help to harness the potential of AI while keeping humans in control.

As arti® cial intelligence moves ever closer to the goal of producing fully autonomous agents, the question of how to design and implement an arti® cial moral agent (AMA) becomes increasingly pressing. Robots possessing autonomous capacities to do things that are useful to humans will also have the capacity to do things that are harmful to humans and other sentient beings. Theoretical challenges to developing arti® cial moral agents result both from controversies among ethicists about moral theory itself, and from (...) computational limits to the implementation of such theories. In this paper the ethical disputes are surveyed, the possibility of a `moral Turing Test ’ is considered and the computational di culties accompanying the diŒerent types of approach are assessed. Human-like performance, which is prone to include immoral actions, may not be acceptable in machines, but moral perfection may be computationally unattainable. The risks posed by autonomous machines ignorantly or deliberately harming people and other sentient beings are great. The development of machines with enough intelligence to assess the eŒects of their actions on sentient beings and act accordingly may ultimately be the most important task faced by the designers of arti® cially intelligent automata. (shrink)