Behavioral scientists routinely publish broad claims about human psychology and behavior in the world's top journals based on samples drawn entirely from Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies. Researchers – often implicitly – assume that either there is little variation across human populations, or that these “standard subjects” are as representative of the species as any other population. Are these assumptions justified? Here, our review of the comparative database from across the behavioral sciences suggests both that there is (...) substantial variability in experimental results across populations and that WEIRD subjects are particularly unusual compared with the rest of the species – frequent outliers. The domains reviewed include visual perception, fairness, cooperation, spatial reasoning, categorization and inferential induction, moral reasoning, reasoning styles, self-concepts and related motivations, and the heritability of IQ. The findings suggest that members of WEIRD societies, including young children, are among the least representative populations one could find for generalizing about humans. Many of these findings involve domains that are associated with fundamental aspects of psychology, motivation, and behavior – hence, there are no obviousa priorigrounds for claiming that a particular behavioral phenomenon is universal based on sampling from a single subpopulation. Overall, these empirical patterns suggests that we need to be less cavalier in addressing questions ofhumannature on the basis of data drawn from this particularly thin, and rather unusual, slice of humanity. We close by proposing ways to structurally re-organize the behavioral sciences to best tackle these challenges. (shrink)

Introduction -- Part I: The good life -- Hedonism : its powerful appeal -- Is happiness all that matters? -- Getting what you want -- Problems for the desire theory -- Part II: Doing the right thing -- Morality and religion -- Natural law theory -- Psychological egoism -- Ethical egoism -- Consequentialism : its nature and attractions -- Consequentialism : its difficulties -- The kantian perspective : fairness and justice -- The kantian perspective : autonomy and respect -- The (...) social contract tradition : theory and attractions -- The social contract tradition : problems and prospects -- Ethical pluralism and absolute moral rules -- Ethical pluralism : prima facie duties and ethical particularism -- Virtue ethics -- Feminist ethics -- Part III: The status of morality -- Ethical relativism -- Moral nihilism -- Ten arguments against moral objectivity. (shrink)

In a Different Voice is the little book that started a revolution, making women's voices heard, in their own right and with their own integrity, for virtually the first time in social scientific theorizing about women. Its impact was immediate and continues to this day, in the academic world and beyond.

ABSTRACT:While tone at the top is widely regarded as an important predictor of ethical behavior in organizations, we argue that recent research overlooks the various conflicting ethical tones present in many multi-organizational work settings. Further, we propose that the resolution processes promulgated in many firms and professional associations to reconcile this conflict reinforce the tone at the bottom or a tone at the top of the employee’s organization, and that both of these approaches can conflict with the tone at the (...) top of other important organizations such as professional and regulatory organizations. Here we adapt Integrative Social Contract Theory’s priority rules to propose a multi-tone reconciliation process which prioritizes conflicting ethical tones based upon features of the organization and the effects on society. Using three contextualizations, we demonstrate the effectiveness of the multi-tone reconciliation process over current processes. We conclude with recommendations for future research and implications for practice. (shrink)

Firms increasingly deploy algorithmic pricing approaches to determine what to charge for their goods and services. Algorithmic pricing can discriminate prices both dynamically over time and personally depending on individual consumer information. Although legal, the ethicality of such approaches needs to be examined as often they trigger moral concerns and sometimes outrage. In this research paper, we provide an overview and discussion of the ethical challenges germane to algorithmic pricing. As a basis for our discussion, we perform a systematic interpretative (...) review of 315 related articles on dynamic and personalized pricing as well as pricing algorithms in general. We then use this review to define the term algorithmic pricing and map its key elements at the micro-, meso-, and macro levels from a business and marketing ethics perspective. Thus, we can identify morally ambivalent topics that call for deeper exploration by future research. (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)

Accounting firms are reporting the use of Artificial Intelligence in their auditing and advisory functions, citing benefits such as time savings, faster data analysis, increased levels of accuracy, more in-depth insight into business processes, and enhanced client service. AI, an emerging technology that aims to mimic the cognitive skills and judgment of humans, promises competitive advantages to the adopter. As a result, all the Big 4 firms are reporting its use and their plans to continue with this innovation in areas (...) such as audit planning risk assessments, tests of transactions, analytics, and the preparation of audit work-papers, among other uses. As the uses and benefits of AI continue to emerge within the auditing profession, there is a gradual awakening to the fact that unintended consequences may also arise. Thus, we heed to the call of numerous researchers to not only explore the benefits of AI but also investigate the ethical implications of the use of this emerging technology. By combining two futuristic ethical frameworks, we forecast the ethical implications of the use of AI in auditing, given its inherent features, nature, and intended functions. We provide a conceptual analysis of the practical ethical and social issues surrounding AI, using past studies as well as our inferences based on the reported use of the technology by auditing firms. Beyond the exploration of these issues, we also discuss the responsibility for the policy and governance of emerging technology. (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)

Recent advances in machine learning methods have created opportunities to eliminate unfairness from algorithmic decision making. Multiple computational techniques (i.e., algorithmic fairness criteria) have arisen out of this work. Yet, urgent questions remain about the perceived fairness of these criteria and in which situations organizations should use them. In this paper, we seek to gain insight into these questions by exploring fairness perceptions of five algorithmic criteria. We focus on two key dimensions of fairness evaluations: distributive fairness and procedural fairness. (...) We shed light on variation in the potential for different algorithmic criteria to facilitate distributive fairness. Subsequently, we discuss procedural fairness and provide a framework for understanding how algorithmic criteria relate to essential aspects of this construct, which helps to identify when a specific criterion is suitable. From a practical standpoint, we encourage organizations to recognize that managing fairness in machine learning systems is complex, and that adopting a blind or one-size-fits-all mentality toward algorithmic criteria will surely damage people’s attitudes and trust in automated technology. Instead, firms should carefully consider the subtle yet significant differences between these technical solutions. (shrink)

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)

While the ethics of technology is analyzed across disciplines from science and technology studies, engineering, computer science, critical management studies, and law, less attention is paid to the role that firms and managers play in the design, development, and dissemination of technology across communities and within their firm. Although firms play an important role in the development of technology, and make associated value judgments around its use, it remains open how we should understand the contours of what firms owe society (...) as the rate of technological development accelerates. We focus here on digital technologies: devices that rely on rapidly accelerating digital sensing, storage, and transmission capabilities to intervene in human processes. This symposium focuses on how firms should engage ethical choices in developing and deploying these technologies. In this introduction, we, first, identify themes the symposium articles share and discuss how the set of articles illuminate diverse facets of the intersection of technology and business ethics. Second, we use these themes to explore what business ethics offers to the study of technology and, third, what technology studies offers to the field of business ethics. Each field brings expertise that, together, improves our understanding of the ethical implications of technology. Finally we introduce each of the five papers, suggest future research directions, and interpret their implications for business ethics. (shrink)

Organizations increasingly rely on algorithm-based HR decision-making to monitor their employees. This trend is reinforced by the technology industry claiming that its decision-making tools are efficient and objective, downplaying their potential biases. In our manuscript, we identify an important challenge arising from the efficiency-driven logic of algorithm-based HR decision-making, namely that it may shift the delicate balance between employees’ personal integrity and compliance more in the direction of compliance. We suggest that critical data literacy, ethical awareness, the use of participatory (...) design methods, and private regulatory regimes within civil society can help overcome these challenges. Our paper contributes to literature on workplace monitoring, critical data studies, personal integrity, and literature at the intersection between HR management and corporate responsibility. (shrink)

Libertarians are an increasingly prominent ideological group in U.S. politics, yet they have been largely unstudied. Across 16 measures in a large web-based sample that included 11,994 self-identified libertarians, we sought to understand the moral and psychological characteristics of self-described libertarians. Based on an intuitionist view of moral judgment, we focused on the underlying affective and cognitive dispositions that accompany this unique worldview. Compared to self-identified liberals and conservatives, libertarians showed 1) stronger endorsement of individual liberty as their foremost guiding (...) principle, and weaker endorsement of all other moral principles; 2) a relatively cerebral as opposed to emotional cognitive style; and 3) lower interdependence and social relatedness. As predicted by intuitionist theories concerning the origins of moral reasoning, libertarian values showed convergent relationships with libertarian emotional dispositions and social preferences. Our findings add to a growing recognition of the role of personality differences in the organization of political attitudes. (shrink)

Researchers in moral psychology and social justice have agreed that morality is about matters of harm, rights, and justice. On this definition of morality, conservative opposition to social justice programs appears to be immoral, and has been explained as a product of various non-moral processes such as system justification or social dominance orientation. In this article we argue that, from an anthropological perspective, the moral domain is usually much broader, encompassing many more aspects of social life and valuing institutions as (...) much or more than individuals. We present theoretical and empirical reasons for believing that there are five psychological systems that provide the foundations for the world’s many moralities. The five foundations are psychological preparations for detecting and reacting emotionally to issues related to harm/care, fairness/reciprocity, ingroup/loyalty, authority/respect, and purity/sanctity. Political liberals have moral intuitions primarily based upon the first two foundations, and therefore misunderstand the moral motivations of political conservatives, who generally rely upon all five foundations. (shrink)

Research on moral judgment has been dominated by rationalist models, in which moral judgment is thought to be caused by moral reasoning. The author gives 4 reasons for considering the hypothesis that moral reasoning does not cause moral judgment; rather, moral reasoning is usually a post hoc construction, generated after a judgment has been reached. The social intuitionist model is presented as an alternative to rationalist models. The model is a social model in that it deemphasizes the private reasoning done (...) by individuals and emphasizes instead the importance of social and cultural influences. The model is an intuitionist model in that it states that moral judgment is generally the result of quick, automatic evaluations (intuitions). The model is more consistent than rationalist models with recent findings in social, cultural, evolutionary, and biological psychology, as well as in anthropology and primatology. (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)

The moral domain is broader than the empathy and justice concerns assessed by existing measures of moral competence, and it is not just a subset of the values assessed by value inventories. To fill the need for reliable and theoretically grounded measurement of the full range of moral concerns, we developed the Moral Foundations Questionnaire on the basis of a theoretical model of 5 universally available sets of moral intuitions: Harm/Care, Fairness/Reciprocity, Ingroup/Loyalty, Authority/Respect, and Purity/Sanctity. We present evidence for the (...) internal and external validity of the scale and the model, and in doing so we present new findings about morality: Comparative model fitting of confirmatory factor analyses provides empirical justification for a 5-factor structure of moral concerns; convergent/discriminant validity evidence suggests that moral concerns predict personality features and social group attitudes not previously considered morally relevant; and we establish pragmatic validity of the measure in providing new knowledge and research opportunities concerning demographic and cultural differences in moral intuitions. These analyses provide evidence for the usefulness of Moral Foundations Theory in simultaneously increasing the scope and sharpening the resolution of psychological views of morality. (shrink)

How and why do moral judgments vary across the political spectrum? To test moral foundations theory, the authors developed several ways to measure people’s use of 5 sets of moral intuitions: Harm/care, Fairness/reciprocity, Ingroup/loyalty, Authority/respect, and Purity/sanctity. Across 4 studies using multiple methods, liberals consistently showed greater endorsement and use of the Harm/care and Fairness/reciprocity foundations compared to the other 3 foundations, whereas conservatives endorsed and used the 5 foundations more equally. This difference was observed in abstract assessments of the (...) moral relevance of foundation-related concerns such as violence or loyalty, moral judgments of statements and scenarios, “sacredness” reactions to taboo trade-offs, and use of foundation-related words in the moral texts of religious sermons. These findings help to illuminate the nature and intractability of moral disagreements in the American “culture war.”. (shrink)

This article details the personal involvement of the author in the early stages of the infamous Pinto fire case. The paper first presents an insider account of the context and decision environment within which he failed to initiate an early recall of defective vehicles. A cognitive script analysis of the personal experience is then offered as an explanation of factors that led to a decision that now is commonly seen as a definitive study in unethical corporate behavior. The main analytical (...) thesis is that script schemas that were guiding cognition and action at the time precluded consideration of issues in ethical terms because the scripts did not include ethical dimensions. (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)

While much research has focused on the effects of ethical and unethical leadership, little is known about how followers come to perceive their leaders as ethical or unethical. In this article, we investigate the co-creation of ethical and unethical leadership perceptions. Specifically, we draw from emerging research on moral congruence in organizational behaviour and empirically investigate the role of congruence in leaders’ and followers’ moral foundations in followers’ perceptions of ethical and unethical leadership. By analysing objective congruence scores from 67 (...) leader–follower dyads by means of polynomial regression with surface response analysis, we find partial support for our theoretically derived predictions. Significant effects were revealed for the fairness, loyalty, and authority moral foundations but not for the care and sanctity moral foundations. We discuss theoretical and practical implications of these findings. (shrink)

Drawing from moral foundations theory, we show that differences in sensitivity to distinct moral norms help explain differences in the perceived fairness of punishing employees for off-duty deviance. We used an initial study to validate realistic examples of non-criminal behavior that were perceived as violating a specific moral foundation. Participants in the main study evaluated scenarios in which co-workers were fired for those behaviors, which took place outside of work but were revealed via social media. The extent to which participants (...) valued the norm violated by the co-worker positively predicted perceived fairness of the firing, and negatively predicted expressed intent to take retributive action against the responsible manager. This effect was moderated by the presence of a pre-existing organizational policy regarding off-duty conduct, which uniformly decreased negative reactions to the firing. Because social media now makes the revelation of an employee’s off-duty behavior to a broad audience increasingly likely, our results suggest the importance of developing an approach for responding to employee off-duty deviance while highlighting the relevance of moral pluralism to the study of third-party reactions. (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)