Inspired by recent breakthroughs in predictive modeling, practitioners in both industry and government have turned to machine learning with hopes of operationalizing predictions to drive automated decisions. Unfortunately, many social desiderata concerning consequential decisions, such as justice or fairness, have no natural formulation within a purely predictive framework. In efforts to mitigate these problems, researchers have proposed a variety of metrics for quantifying deviations from various statistical parities that we might expect to observe in a fair world and offered a (...) variety of algorithms in attempts to satisfy subsets of these parities or to trade o the degree to which they are satised against utility. In this paper, we connect this approach to fair machine learning to the literature on ideal and non-ideal methodological approaches in political philosophy. The ideal approach requires positing the principles according to which a just world would operate. In the most straightforward application of ideal theory, one supports a proposed policy by arguing that it closes a discrepancy between the real and the perfectly just world. However, by failing to account for the mechanisms by which our non-ideal world arose, the responsibilities of various decision-makers, and the impacts of proposed policies, naive applications of ideal thinking can lead to misguided interventions. In this paper, we demonstrate a connection between the fair machine learning literature and the ideal approach in political philosophy, and argue that the increasingly apparent shortcomings of proposed fair machine learning algorithms reflect broader troubles faced by the ideal approach. We conclude with a critical discussion of the harms of misguided solutions, a reinterpretation of impossibility results, and directions for future research. (shrink)

In this critique, Martha Nussbaum argues that our dominant theories of development have given us policies that ignore our most basic human needs for dignity and self-respect.

Technological advances are bringing new light to privacy issues and changing the reasons for why privacy is important. These advances have changed not only the kind of personal data that is available to be collected, but also how that personal data can be used by those who have access to it. We are particularly concerned with how information about personal attributes inferred from collected data (such as online behaviour), can be used to tailor messages and services to specific individuals or (...) groups. This kind of ‘personalised targeting’ has the potential to influence individuals’ perceptions, attitudes, and choices in unprecedented ways. In this paper, we argue that because it is becoming easier for companies to use collected data for influence, threats to privacy are increasingly also threats to personal autonomy—an individual’s ability to reflect on and decide freely about their values, actions, and behaviour, and to act on those choices.4 While increasing attention is directed to the ethics of how personal data is collected, we make the case that a new ethics of privacy needs to also think more rigorously about how personal data may be used, and its potential impact on personal autonomy. (shrink)

Professional Ethics: A Trust-Based Approach explores the unique nature of professional duty and virtue in light of the trust that professionals must invite, develop, and honor from those they intend to serve.

With automation of routine decisions coupled with more intricate and complex information architecture operating this automation, concerns are increasing about the trustworthiness of these systems. These concerns are exacerbated by a class of artificial intelligence that uses deep learning, an algorithmic system of deep neural networks, which on the whole remain opaque or hidden from human comprehension. This situation is commonly referred to as the black box problem in AI. Without understanding how AI reaches its conclusions, it is an open (...) question to what extent we can trust these systems. The question of trust becomes more urgent as we delegate more and more decision-making to and increasingly rely on AI to safeguard significant human goods, such as security, healthcare, and safety. Models that “open the black box” by making the non-linear and complex decision process understandable by human observers are promising solutions to the black box problem in AI but are limited, at least in their current state, in their ability to make these processes less opaque to most observers. A philosophical analysis of trust will show why transparency is a necessary condition for trust and eventually for judging AI to be trustworthy. A more fruitful route for establishing trust in AI is to acknowledge that AI is situated within a socio-technical system that mediates trust, and by increasing the trustworthiness of these systems, we thereby increase trust in AI. (shrink)

Many industry leaders and academics from the field of machine ethics would have us believe that the inevitability of robots coming to have a larger role in our lives demands that robots be endowed with moral reasoning capabilities. Robots endowed in this way may be referred to as artificial moral agents. Reasons often given for developing AMAs are: the prevention of harm, the necessity for public trust, the prevention of immoral use, such machines are better moral reasoners than humans, and (...) building these machines would lead to a better understanding of human morality. Although some scholars have challenged the very initiative to develop AMAs, what is currently missing from the debate is a closer examination of the reasons offered by machine ethicists to justify the development of AMAs. This closer examination is especially needed because of the amount of funding currently being allocated to the development of AMAs coupled with the amount of attention researchers and industry leaders receive in the media for their efforts in this direction. The stakes in this debate are high because moral robots would make demands on society; answers to a host of pending questions about what counts as an AMA and whether they are morally responsible for their behavior or not. This paper shifts the burden of proof back to the machine ethicists demanding that they give good reasons to build AMAs. The paper argues that until this is done, the development of commercially available AMAs should not proceed further. (shrink)

Many industry leaders and academics from the field of machine ethics would have us believe that the inevitability of robots coming to have a larger role in our lives demands that robots be endowed with moral reasoning capabilities. Robots endowed in this way may be referred to as artificial moral agents. Reasons often given for developing AMAs are: the prevention of harm, the necessity for public trust, the prevention of immoral use, such machines are better moral reasoners than humans, and (...) building these machines would lead to a better understanding of human morality. Although some scholars have challenged the very initiative to develop AMAs, what is currently missing from the debate is a closer examination of the reasons offered by machine ethicists to justify the development of AMAs. This closer examination is especially needed because of the amount of funding currently being allocated to the development of AMAs coupled with the amount of attention researchers and industry leaders receive in the media for their efforts in this direction. The stakes in this debate are high because moral robots would make demands on society; answers to a host of pending questions about what counts as an AMA and whether they are morally responsible for their behavior or not. This paper shifts the burden of proof back to the machine ethicists demanding that they give good reasons to build AMAs. The paper argues that until this is done, the development of commercially available AMAs should not proceed further. (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)

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

In this paper, we use the case of the COVID-19 pandemic in Europe to address the question of what kind of knowledge we should incorporate into public health policy. We show that policy-making during the COVID-19 pandemic has been biomedicine-centric in that its evidential basis marginalised input from non-biomedical disciplines. We then argue that in particular the social sciences could contribute essential expertise and evidence to public health policy in times of biomedical emergencies and that we should thus strive for (...) a tighter integration of the social sciences in future evidence-based policy-making. This demand faces challenges on different levels, which we identify and discuss as potential inhibitors for a more pluralistic evidential basis. (shrink)

This article presents the framework Capability Sensitive Design (CSD), which consists of merging the design methodology Value Sensitive Design (VSD) with Martha Nussbaum's capability theory. CSD aims to normatively assess technology design in general, and technology design for health and wellbeing in particular. Unique to CSD is its ability to account for human diversity and to counter (structural) injustices that manifest in technology design. The basic framework of CSD is demonstrated by applying it to the hypothetical design case of a (...) therapy chatbot for mental health. By applying CSD to a design case, the merits of this new framework over the standard VSD approach become apparent. Also, the application demonstrates what a technology design would look like when attention is paid to capabilities right from the start of the design process. (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)

Software systems play an ever more important role in our lives and software engineers and their companies find themselves in a position where they are held responsible for ethical issues that may arise. In this paper, we try to disentangle ethical considerations that can be performed at the level of the software engineer from those that belong in the wider domain of business ethics. The handling of ethical problems that fall into the responsibility of the engineer has traditionally been addressed (...) by the publication of Codes of Ethics and Conduct. We argue that these Codes are barely able to provide normative orientation in software development. The main contribution of this paper is, thus, to analyze the normative features of Codes of Ethics in software engineering and to explicate how their value-based approach might prevent their usefulness from a normative perspective. Codes of Conduct cannot replace ethical deliberation because they do not and cannot offer guidance because of their underdetermined nature. This lack of orientation, we argue, triggers reactive behavior such as “cherry-picking,” “risk of indifference,” “ex-post orientation,” and the “desire to rely on gut feeling.” In the light of this, we propose to implement ethical deliberation within software development teams as a way out. (shrink)

What is the relation between the ethics, the law, and the governance of the digital? In this article I articulate and defend what I consider the most reasonable answer.

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)

Theories of social justice are necessarily abstract, reaching beyond the particular and the immediate to the general and the timeless. Yet such theories, addressing the world and its problems, must respond to the real and changing dilemmas of the day. A brilliant work of practical philosophy, Frontiers of Justice is dedicated to this proposition. Taking up three urgent problems of social justice neglected by current theories and thus harder to tackle in practical terms and everyday life, Martha Nussbaum seeks a (...) theory of social justice that can guide us to a richer, more responsive approach to social cooperation. The idea of the social contract--especially as developed in the work of John Rawls--is one of the most powerful approaches to social justice in the Western tradition. But as Nussbaum demonstrates, even Rawls's theory, suggesting a contract for mutual advantage among approximate equals, cannot address questions of social justice posed by unequal parties. How, for instance, can we extend the equal rights of citizenship--education, health care, political rights and liberties--to those with physical and mental disabilities? How can we extend justice and dignified life conditions to all citizens of the world? And how, finally, can we bring our treatment of nonhuman animals into our notions of social justice? Exploring the limitations of the social contract in these three areas, Nussbaum devises an alternative theory based on the idea of capabilities. She helps us to think more clearly about the purposes of political cooperation and the nature of political principles--and to look to a future of greater justice for all. (shrink)

New technologies from artificial intelligence to drones, and biomedical enhancement make the future of the human family increasingly hard to predict and protect. This book explores how the philosophical tradition of virtue ethics can help us to cultivate the moral wisdom we need to live wisely and well with emerging technologies.

Scenarios involving the introduction of artificially intelligent (AI) assistive technologies in health care practices raise several ethical issues. In this paper, I discuss four objections to introducing AI assistive technologies in health care practices as replacements of human care. I analyse them as demands for felt care, good care, private care, and real care. I argue that although these objections cannot stand as good reasons for a general and a priori rejection of AI assistive technologies as such or as replacements (...) of human care, they demand us to clarify what is at stake, to develop more comprehensive criteria for good care, and to rethink existing practices of care. In response to these challenges, I propose a (modified) capabilities approach to care and emphasize the inherent social dimension of care. I also discuss the demand for real care by introducing the ‘Care Experience Machine’ thought experiment. I conclude that if we set the standards of care too high when evaluating the introduction of AI assistive technologies in health care, we have to reject many of our existing, low-tech health care practices. (shrink)

Nussbaum’s version of the capability approach is not only a helpful approach to development problems but can also be employed as a general ethical-anthropological framework in ‘advanced’ societies. This paper explores its normative force for evaluating information technologies, with a particular focus on the issue of human enhancement. It suggests that the capability approach can be a useful way of to specify a workable and adequate level of analysis in human enhancement discussions, but argues that any interpretation of what these (...) capabilities mean is itself dependent on (interpretations of) the techno-human practices under discussion. This challenges the capability approach’s means-end dualism concerning the relation between on the one hand technology and on the other hand humans and capabilities. It is argued that instead of facing a choice between development and enhancement, we better reflect on how we want to shape human-technological practices, for instance by using the language of capabilities. For this purpose, we have to engage in a cumbersome hermeneutics that interprets dynamic relations between unstable capabilities, technologies, practices, and values. This requires us to modify the capability approach by highlighting and interpreting its interpretative dimension. (shrink)

A capability approach prescribes paternalist government actions to the extent that it requires the promotion of specific functionings, instead of the corresponding capabilities. Capability theorists have argued that their theories do not have much of these paternalist implications, since promoting capabilities will be the rule, promoting functionings the exception. This paper critically surveys that claim. From a close investigation of Nussbaum's statements about these exceptions, it derives a framework of five categories of functionings promotion that are more or less unavoidable (...) in a capability theory. It argues that some of these categories may have an expansionary dynamic; they may give rise to widespread functionings promotion, which would defeat the capabilitarian promise that paternalist interventions will be exceptions to the rule of a focus on capabilities. Finally, the paper discusses three further theoretical issues that will be decisive in holding this paternalist tendency in check: how high one sets threshold levels of capability protection, how lengthy one's list of basic capabilities is, and how one deals with individual responsibility for choices resulting in a loss of one's capabilities. (shrink)

Fundamental questions in value sensitive design include whether and how high-tech products/artefacts could embody values and ethical ideals, and how plural and incommensurable values of ethical and social importance could be chosen rationally and objectively at a collective level. By using a humanitarian cargo drone study as a starting point, this paper tackles the challenges that VSD’s lack of commitment to a specific ethical theory generates in practical applications. Besides, it highlights how mainstream ethical approaches usually related to VSD are (...) incapable of solving main ethical dilemmas raised by technological design for well-being in democratic settings. Accordingly, it is argued that VSD’s ethical-democratic import would substantially be enhanced by the espousal of a procedural ethics stance and the deliberative approach to value and welfare entailed by Amartya Sen’s capability approach. Differently from rival ethical–political theories, its normative and meta-ethical foundations better handle human diversity, value-goal pluralism, conflicting vested interests as well as the epistemic-moral disagreements typical of contemporary complex democracies. Particularly, Sen’s capability approach procedural-deliberative tenets result in an “objective-impartial” choice procedure selecting a “hierarchy” of plural incommensurable values and rational goals thus, suitable to validate an applied science such as welfare-oriented technological design in concrete social environments. Conclusions suggest that refining VSD with a capability-based procedural approach to ethics fosters the concern for democracy and social justice while preserving vital scientific-technical standards. Major advantages are at an applied level to delivering ethically and socially justified, but yet highly functional technologies and high-tech products/artefacts. (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)

Commodities and Capabilities presents a set of inter-related theses concerning the foundations of welfare economics, and in particular about the assessment of personal well-being and advantage. The argument presented focuses on the capability to function, i.e. what a person can do or can be, questioning in the process the more standard emphasis on opulence or on utility. In fact, a person's motivation behind choice is treated here as a parametric variable which may or may not coincide with the pursuit of (...) self-interest. Given the large number of practical problems arising from the roles and limitations of different concepts of interest and the judgement of advantage and well-being, this scholarly investigation is both of theoretical interest and practical import. (shrink)

Julia Annas offers a new account of virtue and happiness as central ethical ideas. She argues that exercising a virtue involves practical reasoning of the kind we find in someone exercising an everyday practical skill, such as farming, building, or playing the piano. This helps us to see virtue as part of an agent's happiness or flourishing.

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)

Since 2016, when the Facebook/Cambridge Analytica scandal began to emerge, public concern has grown around the threat of “online manipulation”. While these worries are familiar to privacy researchers, this paper aims to make them more salient to policymakers — first, by defining “online manipulation”, thus enabling identification of manipulative practices; and second, by drawing attention to the specific harms online manipulation threatens. We argue that online manipulation is the use of information technology to covertly influence another person’s decision-making, by targeting (...) and exploiting their decision-making vulnerabilities. Engaging in such practices can harm individuals by diminishing their economic interests, but its deeper, more insidious harm is its challenge to individual autonomy. We explore this autonomy harm, emphasising its implications for both individuals and society, and we briefly outline some strategies for combating online manipulation and strengthening autonomy in an increasingly digital world. (shrink)

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)

This paper offers a critique of Martha Nussbaum’s description of the capability approach, and offers an alternative. I will argue that Nussbaum’s characterization of the capability approach is flawed, in two ways. First, she unduly limits the capability to two strands of work, thereby ignoring important other capabilitarian scholarship. Second, she argues that there are five essential elements that all capability theories meet; yet upon closer analysis three of them are not really essential to the capability approach. I also offer (...) an alternative description of the capability approach, which is called the cartwheel view of the capability approach. This view is at the same time radically multidisciplinary yet also contains a foundationally robust core among its various usages, and is therefore much better able to make the case that the capability approach can be developed in a very wide range of more specific normative theories. Finally, the cartwheel view is used to argue against Nussbaum's claim that all capabilitarian political theory needs to be politically liberal. (shrink)