Publics’ views on ethical challenges of artificial intelligence: a scoping review

Helena Machado · Susana Silva · Laura Neiva

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Ethics and Social Impacts of AI Digitalization, Law, and Regulation Artificial Intelligence in Healthcare and Education

Abstract

Abstract This scoping review examines the research landscape about publics’ views on the ethical challenges of AI. To elucidate how the concerns voiced by the publics are translated within the research domain, this study scrutinizes 64 publications sourced from PubMed ® and Web of Science™. The central inquiry revolves around discerning the motivations, stakeholders, and ethical quandaries that emerge in research on this topic. The analysis reveals that innovation and legitimation stand out as the primary impetuses for engaging the public in deliberations concerning the ethical dilemmas associated with AI technologies. Supplementary motives are rooted in educational endeavors, democratization initiatives, and inspirational pursuits, whereas politicization emerges as a comparatively infrequent incentive. The study participants predominantly comprise the general public and professional groups, followed by AI system developers, industry and business managers, students, scholars, consumers, and policymakers. The ethical dimensions most commonly explored in the literature encompass human agency and oversight, followed by issues centered on privacy and data governance. Conversely, topics related to diversity, nondiscrimination, fairness, societal and environmental well-being, technical robustness, safety, transparency, and accountability receive comparatively less attention. This paper delineates the concrete operationalization of calls for public involvement in AI governance within the research sphere. It underscores the intricate interplay between ethical concerns, public involvement, and societal structures, including political and economic agendas, which serve to bolster technical proficiency and affirm the legitimacy of AI development in accordance with the institutional norms that underlie responsible research practices.

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References

2005Scoping studies: towards a methodological framework 2010Scoping studies: advancing the methodology 2019The global landscape of AI ethics guidelines 2020An overview of content analysis 2020The Ethics of AI Ethics: An Evaluation of Guidelines 2019Principles alone cannot guarantee ethical AI 2016Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability 2018Governing artificial intelligence: ethical, legal and technical opportunities and challenges

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