Collaborative governance (CG) is becoming the common currency of decision-making, able to surmount existing institutional constraints to effectively address challenges related to sustainability and social and environmental corporate behavior. CG approaches may however result in institutional complexity. As an illustration of CG in the domain of corporate social responsibility (CSR), the ISO 26000 standard is a legitimate point of reference for organizations worldwide. The standard represents a pluralistic institutional logic that resonates several tensions arising from the domain it tries to standardize, the nature of its development process, its interpretation of CSR and the type of standard it represents. This article aims to identify and examine strategic responses to ISO 26000 by various standards-related organizations (including national standardization institutes, certification organizations, and service providers) and to contribute to the understanding of strategic responses of organizations to pluralistic institutional logics that result from CG.
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31-08-2016Artificial Intelligence (AI) offers organizations unprecedented opportunities. However, one of the risks of using AI is that its outcomes and inner workings are not intelligible. In industries where trust is critical, such as healthcare and finance, explainable AI (XAI) is a necessity. However, the implementation of XAI is not straightforward, as it requires addressing both technical and social aspects. Previous studies on XAI primarily focused on either technical or social aspects and lacked a practical perspective. This study aims to empirically examine the XAI related aspects faced by developers, users, and managers of AI systems during the development process of the AI system. To this end, a multiple case study was conducted in two Dutch financial services companies using four use cases. Our findings reveal a wide range of aspects that must be considered during XAI implementation, which we grouped and integrated into a conceptual model. This model helps practitioners to make informed decisions when developing XAI. We argue that the diversity of aspects to consider necessitates an XAI “by design” approach, especially in high-risk use cases in industries where the stakes are high such as finance, public services, and healthcare. As such, the conceptual model offers a taxonomy for method engineering of XAI related methods, techniques, and tools.
MULTIFILE
21-06-2023
Risk matrices have been widely used in the industry under the notion that risk is a product of likelihood by severity of the hazard or safety case under consideration. When reliable raw data are not available to feed mathematical models, experts are asked to state their estimations. This paper presents two studies conducted in a large European airline and partially regarded the weighting of 14 experienced pilots’ judgment though software, and the calculation of agreement amongst 10 accident investigators when asked to assess the worst outcome, most credible outcome and risk level for 12 real events. According to the results, only 4 out of the 14 pilots could be reliably used as experts, and low to moderate agreement amongst the accident investigators was observed.
