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Despite the proliferation of ethical frameworks of artificial intelligence (AI) from different organizations such as government agencies, large corporations, and academic institutions, it is still a challenge to implement and operationalize ethical and legal frameworks for AI in practice due to its complexities. The implementation and operationalization involve different aspects in original theoretical and practical research on designing, developing, presenting, testing, and evaluating approaches, which are supported by advanced AI techniques and interdisciplinary research, in particular, social science, law, and cognitive science. This editorial provides an overview of the field of operationalization of AI ethics and trust, and highlights a few key topics covered in this special issue, i.e., the current landscape of AI ethics implementation, trust and trustworthiness in AI, ethical framework for trust calibration, approaches to build morality in AI, implementation of AI ethics with a pattern-oriented engineering approach, and inclusive user studies.
Chen et al. (2023) studied this question.