More than a decade of exacting scientific research involving paleontological fragments and ancient DNA has lately produced a series of pronouncements about a purportedly novel population of archaic hominins dubbed “the Denisova.” The science involved in these matters is both technically stunning and, socially, at times a bit reckless. Here I discuss the responsibilities which scientists incur when they make inductively risky pronouncements about the different relative contributions by Denisovans to genomes of members of apparent subpopulations of current humans. This (...) science is sensational: it is science which empirically speculates, to the public delight’s and entertainment, about scintillating topics such as when humans evolved, where we came from, and who else we were having sex with during our early hominin history. An initial characterization of sensational science emerges from my discussion of the case, as well as a diagnosis of an interactive phenomenon termed amplified inductive risk. (shrink)

Algorithms have developed into somewhat of a modern myth. On the one hand, they have been depicted as powerful entities that rule, sort, govern, shape, or otherwise control our lives. On the other hand, their alleged obscurity and inscrutability make it difficult to understand what exactly is at stake. What sustains their image as powerful yet inscrutable entities? And how to think about the politics and governance of something that is so difficult to grasp? This editorial essay provides a critical (...) backdrop for the special issue, treating algorithms not only as computational artifacts but also as sensitizing devices that can help us rethink some entrenched assumptions about agency, transparency, and normativity. (shrink)

Using the Aristotelian virtue of friendship and concept of practical wisdom, this paper argues that engaging in political discourse with friends on social media is conducive to the pursuit of the good life because it facilitates the acquisition of the socio-political information and understanding necessary to live well. Previous work on social media, the virtues, and friendship focuses on the initiation and maintenance of the highest form of friendship (Aristotle’s ‘ideal friendship’) online. I argue that the information necessary to live (...) well can come from non-ideal, civic friends in addition to ideal friends. In order to acquire this information successfully via social media, users should practice inclusive engagement, self-control, discretion, and audience-sensitivity in their cyber interactions. This argument is salient given the current concerns about ‘echo chambers’ or ‘filter bubbles’, in which users ignore or block out friends and news sources that support political perspectives different from one’s own. (shrink)

ABSTRACTThe 2016 US presidential election witnessed the development of ethically dubious methods of political persuasion built and executed on social networking sites. The following analyzes the ethics of behavioral microtargeting practices such as those of Cambridge Analytica, a company that claims to have played a central role in Donald Trump’s successful candidacy through its use of social networking sites such as Facebook. After describing Cambridge Analytica’s method of data manipulation and identifying several threats to individual autonomy posed by such practices, (...) this research explores whether Immanuel Kant’s categorical imperative could be used by individuals to effectively guard democratic processes. (shrink)

Fairness is one of the most prominent values in the Ethics and Artificial Intelligence (AI) debate and, specifically, in the discussion on algorithmic decision-making (ADM). However, while the need for fairness in ADM is widely acknowledged, the very concept of fairness has not been sufficiently explored so far. Our paper aims to fill this gap and claims that an ethically informed re-definition of fairness is needed to adequately investigate fairness in ADM. To achieve our goal, after an introductory section aimed (...) at clarifying the aim and structure of the paper, in section “Fairness in algorithmic decision-making” we provide an overview of the state of the art of the discussion on fairness in ADM and show its shortcomings; in section “Fairness as an ethical value”, we pursue an ethical inquiry into the concept of fairness, drawing insights from accounts of fairness developed in moral philosophy, and define fairness as an ethical value. In particular, we argue that fairness is articulated in a distributive and socio-relational dimension; it comprises three main components: fair equality of opportunity, equal right to justification, and fair equality of relationship; these components are grounded in the need to respect persons both as persons and as particular individuals. In section “Fairness in algorithmic decision-making revised”, we analyze the implications of our redefinition of fairness as an ethical value on the discussion of fairness in ADM and show that each component of fairness has profound effects on the criteria that ADM ought to meet. Finally, in section “Concluding remarks”, we sketch some broader implications and conclude. (shrink)

Research into the ethics of artificial intelligence is often categorized into two subareas—robot ethics and machine ethics. Many of the definitions and classifications of the subject matter of these subfields, as found in the literature, are conflated, which I seek to rectify. In this essay, I infer that using the term ‘machine ethics’ is too broad and glosses over issues that the term computational ethics best describes. I show that the subject of inquiry of computational ethics is of great value (...) and indeed is an important frontier in developing ethical artificial intelligence systems. I also show that computational is a distinct, often neglected field in the ethics of AI. In contrast to much of the literature, I argue that the appellation ‘machine ethics’ does not sufficiently capture the entire project of embedding ethics into AI/S, and hence the need for computational ethics. This essay is unique for two reasons; first, it offers a philosophical analysis of the subject of computational ethics that is not found in the literature. Second, it offers a finely grained analysis that shows the thematic distinction among robot ethics, machine ethics and computational ethics. (shrink)

Recent rapid advances in Artificial Intelligence and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by machines. To achieve (...) this, we can adapt the concept of human-in-the-loop from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop, which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, ‘SITL = HITL + Social Contract.’. (shrink)

This paper intends to contribute to the emerging literature on the ethical problems posed by quantum computing and quantum technologies in general. The key ethical questions are as follows: Does quantum computing pose new ethical problems, or are those raised by quantum computing just a different version of the same ethical problems raised by other technologies, such as nanotechnologies, nuclear plants, or cloud computing? In other words, what is new in quantum computing from an ethical point of view? The paper (...) aims to answer these two questions by (a) developing an analysis of the existing literature on the ethical and social aspects of quantum computing and (b) identifying and analyzing the main ethical problems posed by quantum computing. The conclusion is that quantum computing poses completely new ethical issues that require new conceptual tools and methods. (shrink)

In an analysis of artificially intelligent systems for medical diagnostics and treatment planning we argue that patients should be able to exercise a right to withdraw from AI diagnostics and treatment planning for reasons related to (1) the physician’s role in the patients’ formation of and acting on personal preferences and values, (2) the bias and opacity problem of AI systems, and (3) rational concerns about the future societal effects of introducing AI systems in the health care sector.

In the age of ubiquitous computing and artificially intelligent applications, social machines serves as a powerful framework for understanding and interpreting interactions in socio-algorithmic ecosystems. Although researchers have largely used it to analyze the interactions of individuals and algorithms, limited attempts have been made to investigate the politics in social machines. In this study, I claim that social machines are per se political machines, and introduce a five-point framework for classifying influence processes in socio-algorithmic ecosystems. By drawing from scholars from (...) political theory, I use a notion of influence that functions as a meta-concept for connecting and comparing different conceptions of politics. In this way, I can associate multiple political aspects of social machines from a cybernetic perspective. I show that the framework efficiently categorizes dimensions of influence that shape interactions between individuals and algorithms. These categories are symbolic influence, political conduct, algorithmic influence, design, and regulatory influence. Using case studies, I describe how they interact with each other on online social networks and in algorithmic decision-making systems and illustrate how the framework is able to guide scientists in further research. (shrink)

This paper delves into the nuances of ‘fashion’ in recommender systems and social media analytics, which shape and define an individual’s perception and self-relationality. Its aim is twofold: first, it supports a different perspective on privacy that focuses on the individual’s process of identity construction considering the social and personal aspects of ‘fashion’. Second, it underlines the limitations of computational models in capturing the diverse meaning of ‘fashion’, whereby the algorithmic prediction of user preferences is based on individual conscious and (...) unconscious associations with fashion identity. I test both of these claims in the context of current concerns over the impact of algorithmic personalisation systems on individual autonomy and privacy: creating ‘filter bubbles’, nudging the user beyond their conscious awareness, as well as the inherent bias in algorithmic decision-making. We need an understanding of privacy that sustains the inherent reduction of fashion identity to literal attributes and protects individual autonomy in shaping algorithmic approximations of the self. (shrink)

Implications of algorithmic mediation can be studied through the artefact itself, peoples’ practices, and the social/political/economical arrangements that affect and are affected by such interactions. Most studies in Academic social media (ASM) focus on one of these elements at a time, either examining design elements or the users’ behaviour on and perceptions of such platforms. We take a multi-faceted approach using affordances as a lens to analyze practices and arrangements traversed by algorithmic mediation. Following our earlier studies that examined the (...) artefact, this study’s aim is to understand how algorithmic mediation in ASM may shape researchers’ perceptions. We conducted online in-depth interviews with show and tell (n = 11) with ASM users from four countries, about their use of ASM. Data were analyzed using thematic analysis, and the codes were clustered in themes and validated via peer debriefing process. Four themes—related to exposure to content, visibility, ethical or legal infringements, and engagement—are discussed considering implications of datafication and findability. We conclude that algorithmic mediation constructs a narration of the relevant other in ASM, configuring the other as participatory and productive. (shrink)

This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of concern, and maps them onto a proposed taxonomy of different kinds of ethical impact. The analysis uncovers a gap in the literature: currently user-centred approaches do not consider the interests of a variety of other stakeholders—as opposed to just the receivers of a recommendation—in assessing the ethical impacts of a recommender system.

Algorithms silently structure our lives. Algorithms can determine whether someone is hired, promoted, offered a loan, or provided housing as well as determine which political ads and news articles consumers see. Yet, the responsibility for algorithms in these important decisions is not clear. This article identifies whether developers have a responsibility for their algorithms later in use, what those firms are responsible for, and the normative grounding for that responsibility. I conceptualize algorithms as value-laden, rather than neutral, in that algorithms (...) create moral consequences, reinforce or undercut ethical principles, and enable or diminish stakeholder rights and dignity. In addition, algorithms are an important actor in ethical decisions and influence the delegation of roles and responsibilities within these decisions. As such, firms should be responsible not only for the value-laden-ness of an algorithm but also for designing who-does-what within the algorithmic decision. As such, firms developing algorithms are accountable for designing how large a role individual will be permitted to take in the subsequent algorithmic decision. Counter to current arguments, I find that if an algorithm is designed to preclude individuals from taking responsibility within a decision, then the designer of the algorithm should be held accountable for the ethical implications of the algorithm in use. (shrink)

This article discusses the topic of algorithmic personalization and the creation of the so-called “filter bubble” effect, which is often understood as one of the most problematic influences of artificial intelligence on democratic social order. The author suggests that focusing on the issue of information diversity, which had far-reaching effect on the empirical research that tried to quantitatively measure and systematically prove the existence of the filter bubbles, was the wrong starting point for the discussion on the application of algorithmic (...) personalization. It has drawn our attention away from the deeper issue: habit. Habitual adaptation of algorithmic personalization, namely, stands in essential contradiction to the ideal image of a non-adaptive public sphere, upon which democratic societies should be based. Focusing on habitual adaptation could also explain why users addictively stick to certain kinds of information, even if they are not caught in an isolated chamber. (shrink)

In this paper, we build upon Bruno Latour’s political writings to address the current impasse regarding algorithms in public life. We assert that the increasing difficulties at governing algorithms—be they qualified as “machine learning,” “big data,” or “artificial intelligence”—can be related to their current ontological thinness: deriving from constricted views on theoretical practices, algorithms’ standard definition as problem-solving computerized methods provides poor grips for affective dissensions. We then emphasize on the role historical and ethnographic studies of algorithms can potentially play (...) in the politicization of algorithms. By both digging into the genealogy of algorithms’ constricted definition and by making their contemporary constitutive relationships more visible, both historical and ethnographic studies can contribute to vascularizing algorithms and making them objects of enlarged disputes. We conclude by giving a flavor of the political potential of the vascularization efforts we call for, using materials from an ethnographic study conducted in a computer science laboratory. (shrink)

The revelation that menstruation tracking apps share sensitive data with third parties, like Facebook, provoked a sense of violation among users. This case highlights the need to address ethics and governance of health data created outside of traditional healthcare contexts. Commodifying health data breaches trust and entails health and moral risks. Through the metaphor of The Wizard of Oz, we argue that these apps approximate healthcare without the professional competency, fiduciary duties, legal protections and liabilities such care requires and thus (...) represent an innovation in the annals of snake-oil salesmanship and the systematic devaluing of women’s bodies, lives, and work. (shrink)

The increasing implementation of and reliance on machine-learning (ML) algorithms to perform tasks, deliver services and make decisions in health and healthcare have made the need for fairness in ML, and more specifically in healthcare ML algorithms (HMLA), a very important and urgent task. However, while the debate on fairness in the ethics of artificial intelligence (AI) and in HMLA has grown significantly over the last decade, the very concept of fairness as an ethical value has not yet been sufficiently (...) explored. Our paper aims to fill this gap and address the AI ethics principle of fairness from a conceptual standpoint, drawing insights from accounts of fairness elaborated in moral philosophy and using them to conceptualise fairness as an ethical value and to redefine fairness in HMLA accordingly. To achieve our goal, following a first section aimed at clarifying the background, methodology and structure of the paper, in the second section, we provide an overview of the discussion of the AI ethics principle of fairness in HMLA and show that the concept of fairness underlying this debate is framed in purely distributive terms and overlaps with non-discrimination, which is defined in turn as the absence of biases. After showing that this framing is inadequate, in the third section, we pursue an ethical inquiry into the concept of fairness and argue that fairness ought to be conceived of as an ethical value. Following a clarification of the relationship between fairness and non-discrimination, we show that the two do not overlap and that fairness requires much more than just non-discrimination. Moreover, we highlight that fairness not only has a distributive but also a socio-relational dimension. Finally, we pinpoint the constitutive components of fairness. In doing so, we base our arguments on a renewed reflection on the concept of respect, which goes beyond the idea of equal respect to include respect for individual persons. In the fourth section, we analyse the implications of our conceptual redefinition of fairness as an ethical value in the discussion of fairness in HMLA. Here, we claim that fairness requires more than non-discrimination and the absence of biases as well as more than just distribution; it needs to ensure that HMLA respects persons both as persons and as particular individuals. Finally, in the fifth section, we sketch some broader implications and show how our inquiry can contribute to making HMLA and, more generally, AI promote the social good and a fairer society. (shrink)

In this article, we develop the concept of Transparency by Design that serves as practical guidance in helping promote the beneficial functions of transparency while mitigating its challenges in automated-decision making environments. With the rise of artificial intelligence and the ability of AI systems to make automated and self-learned decisions, a call for transparency of how such systems reach decisions has echoed within academic and policy circles. The term transparency, however, relates to multiple concepts, fulfills many functions, and holds different (...) promises that struggle to be realized in concrete applications. Indeed, the complexity of transparency for ADM shows tension between transparency as a normative ideal and its translation to practical application. To address this tension, we first conduct a review of transparency, analyzing its challenges and limitations concerning automated decision-making practices. We then look at the lessons learned from the development of Privacy by Design, as a basis for developing the Transparency by Design principles. Finally, we propose a set of nine principles to cover relevant contextual, technical, informational, and stakeholder-sensitive considerations. Transparency by Design is a model that helps organizations design transparent AI systems, by integrating these principles in a step-by-step manner and as an ex-ante value, not as an afterthought. (shrink)

This paper focuses on extant approaches to counteract the consumption of fake news online. Proponents of structural approaches suggest that our proneness to consuming fake news could only be reduced by reshaping the architecture of online environments. Proponents of educational approaches suggest that fake news consumers should be empowered to improve their epistemic agency. In this paper, we address a question that is relevant to this debate: namely, whether fake news consumers commit mistakes for which they can be criticized and (...) that they could easily avoid by reforming their doxastic conduct. Proponents of structural approaches, like R. Rini and B. Millar, have defended in different ways a negative answer to this question. In this paper, we criticize their views and suggest that individual users could improve on their epistemic practice by widening their information diet. (shrink)

It has been argued that the Internet and social media increase the number of available viewpoints, perspectives, ideas and opinions available, leading to a very diverse pool of information. However, critics have argued that algorithms used by search engines, social networking platforms and other large online intermediaries actually decrease information diversity by forming so-called “filter bubbles”. This may form a serious threat to our democracies. In response to this threat others have developed algorithms and digital tools to combat filter bubbles. (...) This paper first provides examples of different software designs that try to break filter bubbles. Secondly, we show how norms required by two democracy models dominate the tools that are developed to fight the filter bubbles, while norms of other models are completely missing in the tools. The paper in conclusion argues that democracy itself is a contested concept and points to a variety of norms. Designers of diversity enhancing tools must thus be exposed to diverse conceptions of democracy. (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)

In the past few years, scholars have been questioning whether the current approach in data ethics based on the higher level case studies and general principles is effective. In particular, some have been complaining that such an approach to ethics is difficult to be applied and to be taught in the context of data science. In response to these concerns, there have been discussions about how ethics should be “embedded” in the practice of data science, in the sense of showing (...) how ethical issues emerge in small technical choices made by data scientists in their day-to-day activities, and how such an approach can be used to teach data ethics. However, a precise description of how such proposals have to be theoretically conceived and could be operationalized has been lacking. In this article, we propose a full-fledged characterization of ‘embedding’ ethics, and how this can be applied especially to the problem of teaching data science ethics. Using the emerging model of ‘microethics’, we propose a way of teaching daily responsibility in digital activities that is connected to the higher level ethical challenges discussed in digital/data ethics. We ground this microethical approach into a virtue theory framework, by stressing that the goal of a microethics is to foster the cultivation of moral virtues. After delineating this approach of embedding ethics in theoretical detail, this article discusses a concrete example of how such a ‘micro-virtue ethics’ approach could be practically taught to data science students. (shrink)

Critics of persuasive advertising argue that it undermines the autonomy of consumers by manipulating their desires in morally problematic ways. My aim is this paper is to refine that argument by employing a conception of autonomy that is not at odds with certain forms of manipulation. I argue that the charge of manipulation is not sufficient for condemning persuasive advertising. On my view, manipulation of an agent’s desires through advertising is justifiable in cases where the agent accepts the process through (...) which the desires were developed. I show how the standard manipulation objection proves too much as it would also condemn cases of that kind. I argue that this distinction is especially important when we consider the implications of “new media.” In addition to increasing vulnerability to manipulation, new media have considerable impacts on well-being. By siding with the traditional autonomy argument, we would be compelled to take an implausible stand against all forms of manipulation through advertising, but I suggest that only a proper subset of those cases are morally problematic. This conclusion opens up a space for persuasive advertising that is permissible while nevertheless condemning cases that violate consumers’ autonomy. (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)

This paper investigates civility from an Aristotelian perspective and has two objectives. The first is to offer a novel account of this virtue based on Aristotle’s remarks about civic friendship. The proposed account distinguishes two main components of civility—civic benevolence and civil deliberation—and shows how Aristotle’s insights can speak to the needs of our communities today. The notion of civil deliberation is then unpacked into three main dimensions: motivational, inquiry-related, and ethical. The second objective is to illustrate how the post-truth (...) condition—in particular, the spread of misinformation typical of the digital environments we inhabit—obstructs our capacity to cultivate the virtue of civility by impairing every component of civil deliberation. The paper hopes to direct virtue theorists’ attention to the need to foster civic virtues as a means of counteracting the negative aspects of the post-truth age. (shrink)