ABSTRACT:This paper presents a holistic, contextualised case study of reintegration and trust repair at a UK utilities firm in the wake of its fraud and data manipulation scandal. Drawing upon conceptual frameworks of reintegration and organizational trust repair, we analyze the decisions and actions taken by the company in its efforts to restore trust with its stakeholders. The analysis reveals seven themes on the merits of proposed approaches for reintegration after an integrity violation (including open investigations, accurate explanations, apologies, penance, and systemic reforms), and novel insights on the role of organizational identity, “changing of the guard” and cultural reforms alongside procedural modifications. The case further supports the dynamic nature of stakeholder salience across the reintegration process. The study both supports propositions from existing frameworks and suggests novel theoretical extensions for future research.
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.
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