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      AI-enabled digital identity – inputs for stakeholders and policymakers

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      Journal of Science and Technology Policy Management
      Emerald

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          Abstract

          Purpose

          This conceptual article’s primary aim is to identify the significant stakeholders of the digital identity system (DIS) and then highlight the impact of artificial intelligence (AI) on each of the identified stakeholders. It also recommends vital points that could be considered by policymakers while developing technology-related policies for effective DIS.

          Design/methodology/approach

          This article uses stakeholder methodology and design theory (DT) as a primary theoretical lens along with the innovation diffusion theory (IDT) as a sub-theory. This article is based on the analysis of existing literature that mainly comprises academic literature, official reports, white papers and publicly available domain experts’ interviews.

          Findings

          The study identified six significant stakeholders, i.e. government, citizens, infrastructure providers, identity providers (IdP), judiciary and relying parties (RPs) of the DIS from the secondary data. Also, the role of IdP becomes insignificant in the context of AI-enabled digital identity systems (AIeDIS). The findings depict that AIeDIS can positively impact the DIS stakeholders by solving a range of problems such as identity theft, unauthorised access and credential misuse, and will also open a possibility of new ways to empower all the stakeholders.

          Research limitations/implications

          The study is based on secondary data and has considered DIS stakeholders from a generic perspective. Incorporating expert opinion and empirical validation of the hypothesis could derive more specific and context-aware insights.

          Practical implications

          The study could facilitate stakeholders to enrich further their understanding and significance of developing sustainable and future-ready DIS by highlighting the impact of AI on the digital identity ecosystem.

          Originality/value

          To the best of the authors’ knowledge, this article is the first of its kind that has used stakeholder theory, DT and IDT to explain the design and developmental phenomenon of AIeDIS. A list of six significant stakeholders of DIS, i.e. government, citizens, infrastructure providers, IdP, judiciary and RP, is identified through comprehensive literature analysis.

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          Most cited references123

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          Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

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            Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy

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              Self and social identity.

              In this chapter, we examine the self and identity by considering the different conditions under which these are affected by the groups to which people belong. From a social identity perspective we argue that group commitment, on the one hand, and features of the social context, on the other hand, are crucial determinants of central identity concerns. We develop a taxonomy of situations to reflect the different concerns and motives that come into play as a result of threats to personal and group identity and degree of commitment to the group. We specify for each cell in this taxonomy how these issues of self and social identity impinge upon a broad variety of responses at the perceptual, affective, and behavioral level.
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                Author and article information

                Journal
                Journal of Science and Technology Policy Management
                JSTPM
                Emerald
                2053-4620
                2053-4620
                August 25 2021
                August 25 2021
                Article
                10.1108/JSTPM-09-2020-0134
                1d5acfe2-27c5-4158-8f12-f5a0b66027fa
                © 2021

                https://www.emerald.com/insight/site-policies

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