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The oft-cited privacy paradox is the perceived disconnect between individuals’ stated privacy expectations as captured in surveys and consumer market behavior in going online: i.e. individuals purport to value privacy yet still disclose information to firms. The privacy paradox is important for business ethics because the narrative of the privacy paradox defines the scope of corporate responsibility as quite narrow: firms have little to no responsibility to identify or respect privacy expectations if consumers are framed as relinquishing privacy online. The goal of this paper is to test the privacy paradox and empirically examine the conceptualization of privacy post disclosure assumed in the privacy paradox. Contrary to the privacy paradox, the results suggest consumers retain strong privacy expectations even after disclosing information. Privacy violations are valued akin to security violations in creating distrust in firms and in consumer (un)willingness to engage with firms in an experiment. Where firms currently are framed as having, at most, a duty to not interfere with consumers choosing to relinquish privacy, this paper broadens the scope of corporate responsibility to suggest firms have a positive obligation to identify reasonable expectations of privacy of consumers. In addition, the results impact how privacy is conceptualized and empirically examined in business ethics; research perpetuating the privacy paradox through the mistaken framing of disclosure as proof of anti-privacy behavior is harmful by giving license to firms to act contrary to the interests of consumers.

While the ethics of technology is analyzed across disciplines from science and technology studies (STS), 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.

While Big Data has garnered attention for its impact on firms and consumers, the algorithms that make sense of the large data sets are recently in the news – and not only for creating value but for being biased and unfair. Algorithms – including artificial intelligence, machine learning, and neural networks – drive critical decisions such as which patient is seen, who is offered insurance, or what street is patrolled by the police. Such algorithmic decisions, like all decisions, are biased and make mistakes. However the question remains, who is responsible for managing those mistakes? What is the appropriate role of algorithms in critical decisions such as being promoted, receiving medical care, or being offered a loan? I turn to focus on the design of ethical algorithms and the responsibility of developers and users of algorithms to ensure algorithms support good decisions. I make two ethical arguments. First, while mistakes may be unintentional, ignoring or even fostering mistakes is unethical –mistakes can diminish rights, cause harms, or be unfair. Ethical algorithms should be designed to be governed by identifying, judging, and correcting mistakes. Second, by creating inscrutable, autonomous algorithms, developers may voluntarily take on accountability for the role of the algorithm in the decision including the ability to correct mistakes.

With information misuse as a particularly salient form of risk online, respecting privacy is often closely tied to trust in consumer surveys. This study uses factorial vignette survey methodology to measure the relative importance of violating privacy expectations to consumers' trust in a website. The findings suggest consumers find violations of privacy expectations, specifically the secondary uses of information, to diminish trust in a website. Firms that violate privacy expectations are penalized twice: violations of privacy (1) impact trust directly and (2) diminish the importance of trust factors such as integrity and ability on trust. In addition, consumers with greater technology savvy place greater importance on privacy factors than respondents with less knowledge. Violations of privacy may place firms in a downward trust spiral by decreasing not only trust in the website but also the impact of possible mechanisms to rebuild trust such as a firm's integrity and ability.

While privacy online is governed through formal privacy notices, little is known about the impact of privacy notices on trust online. I use a factorial vignette study to examine how the introduction of formal privacy governance (privacy notices) impacts consumer trust and compare the importance of respecting informal privacy norms versus formal privacy notices on consumer trust. The results show that invoking formal privacy notices decreases trust in a website. Further, violating informal privacy norms negatively impacts trust in the website even when the information exchange conforms to or is not mentioned in the privacy notice. The results suggest that respecting privacy norms is key to trust online and challenge the reliance on privacy notices to maintain consumer trust. The consumer, who is the exchange partner most vulnerable to information asymmetries and uncertainty, is not a party to the development of the formal privacy contract and instead relies on informal privacy norms.

Public trust in business, defined as the degree to which the public—meaning society at large—trusts business in general, is largely understudied. This article suggests four domains of existing trust research from which scholars of public trust in business can draw. The authors then propose four main hypotheses, which aim to predict the determinants of public trust, and test these hypotheses using a factorial vignette methodology. These results will provide scholars with more direction as this article is, to the authors’ knowledge, one of the first empirical studies of public trust. Furthermore, the study will enable those companies interested in increasing public trust to understand better respective determinants of public trust.

Users increasingly use mobile devices to engage in social activity and commerce, enabling new forms of data collection by firms and marketers. User privacy expectations for these new forms of data collection remain unclear. A particularly difficult challenge is meeting expectations for contextual integrity, as user privacy expectations vary depending upon data type collected and context of use. This article illustrates how fine-grained, contextual privacy expectations can be measured. It presents findings from a factorial vignette survey that measured the impact of diverse real-world contexts e.g., medical, navigation, music, data types, and data uses on user privacy expectations. Results demonstrate that individuals’ general privacy preferences are of limited significance for predicting their privacy judgments in specific scenarios. Instead, the results present a nuanced portrait of the relative importance of particular contextual factors and information uses, and demonstrate how those contextual factors can be found and measured. The results also suggest that current common activities of mobile application companies, such as harvesting and reusing location data, images, and contact lists, do not meet users’ privacy expectations. Understanding how user privacy expectations vary according to context, data types, and data uses highlights areas requiring stricter privacy protections by governments and industry.

The goal of this article is to examine the strategic choices of firms collecting consumer data online and to identify the roles and obligations of the actors within the current network of online tracking. In doing so, the focus shifts from placing the onus on individuals to make an informed choice, to justifying the roles and responsibilities of firms when gathering, aggregating, and using consumers' interests or behavior online. Firms online are uniquely positioned to undercut or to respect privacy expectations within three possible roles: as a member of a supply chain of information traders, within a network of surveillance online, and as an arm of law enforcement. These firms benefit from aggregating and analyzing consumer data and have an associated responsibility to not only minimize the harm to consumers but also to enact change where the firm is in the most knowledgeable and powerful position.

Two dominant theoretical models for privacy-individual privacy preferences and context-dependent definitions of privacy-are often studied separately in information systems research. This paper unites these theories by examining how individual privacy preferences impact context-dependent privacy expectations. The paper theorizes that experience provides a bridge between individuals' general privacy attitudes and nuanced contextual factors. This leads to the hypothesis that, when making judgments about privacy expectations, individuals with less experience in a context rely more on individual preferences such as their generalized privacy beliefs, whereas individuals with more experience in a context are influenced by contextual factors and norms. To test this hypothesis, 1,925 American users of mobile applications made judgments about whether varied real-world scenarios involving data collection and use met their privacy expectations. Analysis of the data suggests that experience using mobile applications did moderate the effect of individual preferences and contextual factors on privacy judgments. Experience changed the equation respondents used to assess whether data collection and use scenarios met their privacy expectations. Discovering the bridge between 2 dominant theoretical models enables future privacy research to consider both personal and contextual variables by taking differences in experience into account.

Declining levels of stakeholder trust in business are of concern to business executives and scholars for legitimacy- and performance-related effects. Research in the area of stakeholder trust in business is nascent; therefore, the trust formation process has been rarely examined at the stakeholder level. Furthermore, the role of personal values as one significant influence in trust formation has been under-researched. In this paper, we develop a contingency model for stakeholder trust formation based on the effects of stakeholder-specific vulnerability and personal values of the trustor. Using a factorial vignette methodology, we find that Schwartz’s (J Soc Issues 50:19–45, 1994) value set interacts with stakeholder roles so that trustworthiness signals of competence and character play differing roles during trust formation. These results inform stakeholder trust research, organizational trust research, and research in personal values. The research also informs managers tasked with rebuilding stakeholder trust in business.

Recent scholarship in philosophy, law, and information systems suggests that respecting privacy entails understanding the implicit privacy norms about what, why, and to whom information is shared within specific relationships. These social contracts are important to understand if firms are to adequately manage the privacy expectations of stakeholders. This paper explores a social contract approach to developing, acknowledging, and protecting privacy norms within specific contexts. While privacy as a social contract—a mutually beneficial agreement within a community about sharing and using information—has been introduced theoretically and empirically, the full impact on firms of an alternative framework to respecting the privacy expectations of stakeholders has not been examined. The goal of this paper is to examine how privacy norms develop through social contract’s narrative, to redescribe privacy violations given the social contract approach, and to critically examine the role of business as a contractor in developing privacy norms. A social contract narrative dealing specifically with issues of privacy is an important next step in exploring a social contract approach to privacy. Here, the narrative is used to explain to analyze the dynamic process of privacy norm generation within particular communities. Based on this narrative, individuals within a given community discriminately share information with a particular set of obligations in mind as to who has access to the information and how it will be used. Rather than giving away privacy, individuals discriminately share information within a particular community and with norms governing the use of their information. Similar to contractual business ethics’ impact on global commerce in explaining how and why norms vary across global contexts, the social contract approach to privacy explains how and why norms vary across communities of actors. Focusing on agreements around privacy expectations shifts the responsibility of firms from adequate notification to the responsibility of firms as contractors to maintain a mutually beneficial and sustainable solution.