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Digital trace data can be used to capture organizational practices in granular detail and enable the automation of a wide range of managerial tasks. One example is Digital Productivity Assistants (DPA) that harness digital trace data about knowledge workers’ performance and make targeted suggestions for how to improve and optimize their work patterns. Previous research shows that despite benevolent intentions to increase workers’ wellbeing, DPA tend to introduce novel forms of exploitation and control. Inspired by Michel Foucault’s philosophical strategy of ‘problematization,’ which emphasizes how practices are constructed in the form of problems that subsequently shape certain solutions, this paper takes a critical yet constructive view of DPA. Specifically, we conduct a genealogical reading of the DPA tool, Microsoft MyAnalytics, to investigate the problematics that have structured its emergence, as well as how its uses imply certain discursive commitments to philosophical and ethical questions. In the prevailing discourse, DPA cast digital trace data as a learning opportunity and thereby commit to individualizing the responsibility for handling the paradoxical nature of increasingly fluid work arrangements. Conversely, in our account of the history of MyAnalytics, we uncover a ‘lost discourse’ committed to trace data as a resource that can help knowledge workers negotiate excessive workloads. We propose the problematization lens as a way critically to articulate alternatives and speculate about instantiations of digital technology that today seem ‘unthinkable’.

Crowdsourced disinformation represents a two-sided-market model wherein a platform organizer orchestrates the interaction between disinformation requesters and crowdworkers for a fee. Academic research and industry reports demonstrate that the disinformation business is thriving and that its consequences can be severe; however, research on this topic has focused mainly on developing technical methods to detect disinformation, while leaving the social aspects of the phenomenon unaddressed. In particular, very little is known about the discursive tactics that platforms apply to justify disinformation-service offerings such that these appear acceptable to potential customers. Taking a critical approach to the topic, the paper examines how platform organizers justify their disinformation services and to what extent the justifications given are valid. These questions are addressed via a unique dataset from 10 crowdsourcing platforms specializing in social-media–based reputation management. Drawing on the lens of accounts, the analysis suggests that these platforms employ six means of justification for persuasion purposes: the “claim of entitlement,” “defense of the necessity,” the “claim of ubiquity,” “language sanitization,” “appeal to professionalism,” and “appeal to codified rules.” Critical discourse analysis scrutinizing these accounts against the validity claims of comprehensibility, truth, sincerity, and legitimacy indicates that they cannot be considered valid. The paper discusses the implications of the findings and offers several recommendations designed for improving the status quo.

While digital platforms have become an increasingly important research area in the information systems discipline, the existing literature does not conceptualize a theoretical link between platforms and morality. This paper theorizes such a link by drawing on Jensen’s (2010) conceptualization of processes of demoralization to operationalize two notions from critical social theorist Zygmunt Bauman: workers’ moral impulse and moral ambivalence. We conducted a case study of a large luxury resort hotel to examine how digital platforms (specifically TripAdvisor and WhatsApp) facilitate surveillance. Our findings show how digital platform-facilitated synoptic and panoptic forms of surveillance can suppress workers’ moral impulse and foster moral ambivalence towards such issues as invading others’ privacy, pressuring others outside working hours, and increasing surveillance in the workplace. This paper offers a novel perspective on theorizing the links between digital platforms, surveillance, and workers’ morality and highlights some unintended consequences.

Autonomous driving systems (ADS) operate in an environment that is inherently complex. As these systems may execute a task without the permission of a human agent, they raise major safety and responsibility issues. To identify the relevant issues for information systems, we conducted a critical and scoping review of the literature from many disciplines. The innovative methodology we used combines bibliometrics techniques, grounded theory and a critical conceptual framework to analyse the structure and research themes of the field. Our findings show that there are certain ironies in the way in which responsibility for apparently safe autonomous systems is apportioned. These ironies are interconnected and reveal that there remains significant uncertainty and ambiguity regarding the distribution of responsibility between stakeholders. The ironies draw attention to the challenges of safety and responsibility with ADS and possibly other cyber-physical systems in our increasingly digital world. We make seven recommendations related to (1) value sensitive design and system theory approaches; (2) stakeholders’ interests and interactions; (3) task allocation; (4) deskilling; (5) controllability; (6) responsibility (moral and legal); (7) trust. We suggest five areas for future IS research on ADS. These areas are related to socio-technical systems, critical research, safety, responsibility and trust.

In their pursuit of public health goals, policymakers increasingly turn to innovative apps to complement existing health measures. However, findings from previous research in non-IT health contexts indicate that individuals may compensate for new interventions (e.g., start exercising) by reducing existing preventive health behaviors (e.g., eating fewer healthy foods). However, the findings are inconclusive, and it is unknown whenpeople tend to engage in behavioral compensation. Building on this observation, we draw on rational choice theory to substantiate the subjective rationality of compensation behavior and develop a utility maximization model that suggests circumstances under which adoption of technological innovation may lead to users reducing existing preventive health behaviors. This research provides evidence from a multi-wave study on COVID-19 contact-tracing apps that confirms the existence of what we term the technology-behavioral compensation effect: Individuals who perceive the app to be highly useful or actively use it reduce other preventive health behaviors (e.g., social distancing) after app adoption. Ironically, this technology-behavioral compensation effect indicates a hitherto-overlooked tension between two established IS design goals (i.e., perceived usefulness and active use) and the successful exploitation of technology to support users’ health. We expand research on dark side effects of IS use by revealing a previously neglected type of unintended consequence and elaborate on its implications for research well beyond the health context. Our findings also will help policymakers make decisions on the design of societal technologies.

Because of COVID-19 lockdowns, managers and administrators have begun to look for new ways to monitor and control their stranded-at-home workforce. Yet long before the pandemic already, advancements in datification, sensorization, and artificial intelligence have given rise to what we call connected workplace surveillance. At the heart of this new mode of employee monitoring and control is the extension of the scope of data collection beyond what is necessary and reasonable for performance appraisals or managerial oversight. This includes treating an employee’s body as a data source, disrespecting the boundaries between business and private life, or using gathered surveillance information for subtle persuasion, manipulation, and coercion. This article provides a new perspective on control theory, examining the characteristics of connected surveillance and comparing it to visual or computerized surveillance. Taking an employee-centric position, it also proposes a research agenda for critical, behavioral, and design-oriented scholars who wish to explore the identified issues.

Data analytics provides versatile decision support to help employees tackle the rising complexity of today’s business decisions. Notwithstanding the benefits of these systems, research has shown their potential for provoking discriminatory decisions. While technical causes have been studied, the human side has been mostly neglected, albeit employees mostly still need to decide to turn analytics recommendations into actions. Drawing upon theories of technology dominance and of moral disengagement, we investigate how task complexity and employees’ expertise affect the approval of discriminatory data analytics recommendations. Through two online experiments, we confirm the important role of advantageous comparison, displacement of responsibility, and dehumanization, as the cognitive moral disengagement mechanisms that facilitate such approvals. While task complexity generally enhances these mechanisms, expertise retains a critical role in analytics-supported decision-making processes. Importantly, we find that task complexity’s effects on users’ dehumanization vary: more data subjects increase dehumanization, whereas richer information on subjects has the opposite effect. By identifying the cognitive mechanisms that facilitate approvals of discriminatory data analytics recommendations, this study contributes toward designing tools, methods, and practices that combat unethical consequences of using these systems.

Social media technology not only affords opportunities for digital activism and global liberation, but it also poses threats to the freewheeling of democracy. The emergence and prevalence of conspiracy theories on social media stem from communal processes of online political debate or social movements that degenerate into conspiracy beliefs. This study views the online formation of conspiracy theories as a socially emergent process. Subscribing to a social constructionist lens and synthesizing extant literature on social movements and social media affordances, we conducted discourse analysis on discursive data collected from Twitter for the 2020 U.S. Presidential Election Fraud Conspiracy Theory. Through the analysis, we delineate the formation of conspiracy theory into four stages and characterize each stage according to its mobilizing structure, participants, mode of interaction, content created, and discernible collective action. We also identify social media affordances facilitating the formation of conspiracy theories within and across stages. Findings of this study advance contemporary knowledge on conspiracy theories by not only extending our understanding of the role of social media in conspiracy theory formation, but they also aid practitioners in comprehending the formation process of conspiracy theory formation, the latter of which constitutes the foundation for devising appropriate prevention and mitigation strategies.

Increasingly, people are turning to social media to express grief. By and large, however, the social media community can do little more than improvise reactions, not quite sure how to use the old familiar social scripts as guides to lending effective support. To examine the role of social media in the grieving process, we used a mixed-methods approach: 12 interviews with “social media grievers” reveal the expectations of the bereaved regarding other users’ behavior. By way of two online experiments with 1058 participants, we tested how these expectations are met by the messaging of social media providers in accordance with social norm theory. We found that injunctive social norm messages are particularly effective, whereas descriptive social norm messages vary in their effectiveness, depending on which information is presented and how prominently so. What our study shows, then, is that both are potent socio-technical tools that can guide users towards more empathetic behavior when dealing with the bereaved, so while social media may not be a substitute for therapy, they can offer profound comfort for those of us dealing with bereavement and grief.

The growth and popularity of Web 2.0 applications help people to build and maintain their social networks online and further encourage social network-facilitated team collaboration. In this study, we conceptualized the use of instant messaging in social network-facilitated team collaboration as an intentional social action and further investigated the effect of gender differences in the development of we-intention (i.e. collective intention) to engage in such collaboration. A research model was developed and empirically tested with 482 university students in Mainland China. The results demonstrated that the effects of attitude, positive anticipated emotions, and group norms on we-intention were more important for men, whereas the effects of social identity and negative anticipated emotions were more significant for women to collectively participate in social network-facilitated team collaboration. We believe the implications of this study would shed considerable light on both research and practice.