Introduction to the Minitrack on Advances in Trust, Identity, and Trusted Systems in Technology-Mediated Environments

Within the 52nd Hawaiian International Conference on System Sciences (HICSS), we organize for the third time a minitrack on Trust, Identity, and Trusted Systems in Technology-mediated Environments. Trust is a pervasive concern not just with new technologies but also with established technologies as they become more complex and interdependent. Through five papers and an open discussion, the minitrack will discuss and debate when and to what degree trust matters, in what form(s), and with which consequences in the context of existing and emerging hardware and software technologies, e.g., biometric technologies, cryptocurrencies, artificial intelligence, peer-to-peer networked platforms, and autonomous vehicles

Algorithmic Management: Its Implications for Information Systems Research

In recent years, the topic of algorithmic management has received increasing attention in information systems (IS) research and beyond. As both emerging platform businesses and established companies rely on artificial intelligence and sophisticated software to automate tasks previously done by managers, important organizational, social, and ethical questions emerge. However, a cross-disciplinary approach to algorithmic management that brings together IS perspectives with other (sub-)disciplines such as macro- and micro-organizational behavior, business ethics, and digital sociology is missing, despite its usefulness for IS research. This article engages in cross-disciplinary agenda setting through an in-depth report of a professional development workshop (PDW) entitled “Algorithmic Management: Toward a Cross-Disciplinary Research Agenda” delivered at the 2021 Academy of Management Annual Meeting. Three leading experts (Mareike Möhlmann, Lindsey Cameron, and Laura Lamers) on the topic provide their insights on the current status of algorithmic management research, how their work contributes to this area, where the field is heading in the future, and what important questions should be answered going forward. These accounts are followed up by insights from the breakout group discussions at the PDW that provided further input. Overall, the experts and workshop participants highlighted that future research should examine both the desirable and undesirable outcomes of algorithmic management and should not shy away from posing ethical and normative questions

What people hate about being managed by algorithms, according to a study of Uber drivers

Companies are increasingly using algorithms to manage their remote workforces. Called “algorithmic management,” this approach has been most widely adopted in gig economy companies. For example, ride-hailing company Uber substantially increases its efficiency by managing some three million workers with an app that instructs drivers which passengers to pick up and which route to take

Cognitive Challenges on Digital Exchange Platforms: Exploring Misspecifications of Trust

Digital platforms are complex, layered, modular systems comprising many different entities, including intermediary organizations, technological infrastructure, peer entrepreneurs, peer consumers, and advertisers. Relationships on these complex platforms are multi-faceted and at mixed levels. This complexity creates cognitive challenges for peer consumers, which may lead to trust misspecifications. Such misspecifications are important, as they may cause social dilemmas and political challenges. Four different misspecifications of trust are discussed and illustrated in the context of Airbnb. We identify boundary conditions that may either exacerbate or attenuate misspecifications of trust. We conclude by discussing the implications for trust research and directions for future research