Towards An Integrated Framework for Artificial Intelligence Governance

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationAMCIS 2022 Proceedings
Publication statusPublished - Aug 2022

Conference

TitleTwenty-eighth Americas Conference on Information Systems 2022
LocationIn-Person and Virtual Conference
PlaceUnited States
CityMinneapolis
Period10 - 14 August 2022

Abstract

Artificial intelligence (AI) is being developed and adopted by many organizations throughout the world. As the potential of AI is being leveraged, many opportunities are being realized and continue to emerge. However, potential issues need to be addressed (Wang and Siau, 2019), such as ethical and legal concerns (Siau and Wang, 2020), making an AI governance framework paramount (Wang and Siau, 2018; Chen et al., 2022). To address this need, we propose an integrated AI governance framework based on an analysis of existing AI frameworks from different regions of the world (i.e., United States, European Commission, Singapore, and Hong Kong). More specifically, we systematically analyzed these frameworks, juxtaposed the frameworks to identify similarities and differences, which allowed us to identify the core components of AI governance, and proposed an integrated framework for AI governance that adheres to the characteristics of analytic theory (Gregor, 2006). The proposed AI governance framework encompasses both Strategic as well as Tactical and Operational components. There is an overarching theme that crosses the Strategic, Tactical, and Operational components that we termed Stakeholder Communication, Interaction, and Engagement. The integrated framework can be utilized by practitioners as guidelines for their AI endeavors and it can also serve as a foundation to guide future AI governance research. Moving forward, we plan to conduct case studies on AI governance frameworks in organizations and study their impacts on AI success. Future research also includes extending our proposed AI governance framework and fine-tuning it to fit unique organizational characteristics or specific sectors of industry.

Research Area(s)

  • Artificial Intelligence (AI), Governance Framework

Bibliographic Note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Citation Format(s)

Towards An Integrated Framework for Artificial Intelligence Governance. / Eschenbrenner, Brenda; Nah, Fiona Fui-Hoon; Siau, Keng ; Chen, Langtao; Qian, Yuzhou.

AMCIS 2022 Proceedings. 2022. 1605.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review