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What's Next for Responsible Artificial Intelligence: a Way Forward Through Responsible Innovation

Overview
Journal Heliyon
Specialty Social Sciences
Date 2023 Mar 27
PMID 36967876
Authors
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Abstract

Industry is adopting artificial intelligence (AI) at a rapid pace and a growing number of countries have declared national AI strategies. However, several spectacular AI failures have led to ethical concerns about responsibility in AI development and use, which gave rise to the emerging field of responsible AI (RAI). The field of responsible innovation (RI) has a longer history and evolved toward a framework for the entire research, development, and innovation life cycle. However, this research demonstrates that the uptake of RI by RAI has been slow. RAI has been developing independently, with three times the number of publications than RI. The objective and knowledge contribution of this research was to understand how RAI has been developing independently from RI and contribute to how RI could be leveraged toward the progression of RAI in a causal loop diagram. It is concluded that stakeholder engagement of citizens from diverse cultures across the Global North and South is a policy leverage point for moving the RI adoption by RAI toward global best practice. A role-specific recommendation for policy makers is made to deploy modes of engaging with the Global South with more urgency to avoid the risk of harming vulnerable populations. As an additional methodological contribution, this study employs a novel method, systematic science mapping, which combines systematic literature reviews with science mapping. This new method enabled the discovery of an emerging 'axis of adoption' of RI by RAI around the thematic areas of ethics, governance, stakeholder engagement, and sustainability. 828 Scopus articles were mapped for RI and 2489 articles were mapped for RAI. The research presented here is by any measure the largest systematic literature review of both fields to date and the only cross-disciplinary review from a methodological perspective.

Citing Articles

Applications of artificial intelligence and machine learning in the financial services industry: A bibliometric review.

Pattnaik D, Ray S, Raman R Heliyon. 2024; 10(1):e23492.

PMID: 38187262 PMC: 10770565. DOI: 10.1016/j.heliyon.2023.e23492.

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