1 - 4 of 4
ItemThe Influence of AI-Based Chatbots and Their Design on Users’ Trust and Information Sharing in Online Loan Applications( 2021-01-05)Based on recent advances in Artificial Intelligence (AI), chatbots are now increasingly offered as an alternative source of customer service. For their uptake user trust in critical. However, little is known about how these interfaces fundamentally influence trust perceptions. In particular, it’s unclear what exactly causes perceptual differences - the change towards a conversational interface or the usage of anthropomorphic design elements. In this study, an online experiment with 160 participants was conducted to examine the differential effects of conversational interaction and anthropomorphism on trust in the interface or the provider within the context of online loan applications. The results show that both treatment conditions affect trust in the interface and the provider by increasing perceptions of social presence. Meanwhile, trust in the interface significantly effects the intention to share information, while trust in the provider has no effect on behavioral intention.
ItemThe Bermuda Triangle of Leadership in the AI Era? Emerging Trust Implications From “Two-Leader-Situations” in the Eyes of Employees( 2021-01-05)Artificial Intelligence (AI) and machine learning (ML) algorithms are changing the work in many ways. One hitherto little-studied area is how these technologies are impacting leader-employee relationships, particularly employees’ trust relationships in their “flesh-and-blood” leaders. In this paper, we discuss how algorithms change the nature of leadership when some leadership functions become automated. As a consequence, employees will often find themselves in a “two-leader-situation” with resulting frictions, that create novel leadership focus areas. Three situations, in particular, can be trust-problematic in the eyes of followers: the triad relationship might (1) make responsibilities blur, (2) create conflicting decisions of human leaders and algorithms, and (3) make employees’ voice unheard. We argue that these situations can undermine employee perceptions of leaders' trustworthiness as followers might start to question a leaders’ ability, benevolence, and integrity if leaders do not understand these novel situations.
ItemA Review of Trust in Artificial Intelligence: Challenges, Vulnerabilities and Future Directions( 2021-01-05)Artificial Intelligence (AI) can benefit society, but it is also fraught with risks. Societal adoption of AI is recognized to depend on stakeholder trust in AI, yet the literature on trust in AI is fragmented, and little is known about the vulnerabilities faced by different stakeholders, making it is difficult to draw on this evidence-base to inform practice and policy. We undertake a literature review to take stock of what is known about the antecedents of trust in AI, and organize our findings around five trust challenges unique to or exacerbated by AI. Further, we develop a concept matrix identifying the key vulnerabilities to stakeholders raised by each of the challenges, and propose a multi-stakeholder approach to future research.