A systematic review of artificial intelligence impact assessments.

Artificial intelligence (AI) is producing highly beneficial impacts in many domains, from transport to healthcare, from energy distribution to marketing, but it also raises concerns about undesirable ethical and social consequences. AI impact assessments (AI-IAs) are a way of identifying positive and negative impacts early on to safeguard AI's benefits and avoid its downsides. This article describes the first systematic review of these AI-IAs.

Research and Practice of AI Ethics: A Case Study Approach Juxtaposing Academic Discourse with Organisational Reality.

This study investigates the ethical use of Big Data and Artificial Intelligence (AI) technologies (BD + AI)-using an empirical approach. The paper categorises the current literature and presents a multi-case study of 'on-the-ground' ethical issues that uses qualitative tools to analyse findings from ten targeted case-studies from a range of domains. The analysis coalesces identified singular ethical issues, (from the literature), into clusters to offer a comparison with the proposed classification in the literature.

Understanding innovators' experiences of barriers and facilitators in implementation and diffusion of healthcare service innovations: a qualitative study.

Background: Healthcare service innovations are considered to play a pivotal role in improving organisational efficiency and responding effectively to healthcare needs. Nevertheless, healthcare organisations encounter major difficulties in sustaining and diffusing innovations, especially those which concern the organisation and delivery of healthcare services. The purpose of the present study was to explore how healthcare innovators of process-based initiatives perceived and made sense of factors that either facilitated or obstructed the innovation implementation and diffusion.