Research seminar by Natalia Levina

Abstract: Organizations increasingly seek to govern artificial intelligence (AI) in ways that align with organizational objectives. Governing AI development, however, is particularly challenging because the technology is rapidly evolving, difficult to control, and often requires deep contextual and technical knowledge to assess. We conducted a longitudinal qualitative field study in a large European telecommunications company to understand how governance is enacted in AI development practices. Taking a material-discursive practice perspective, we identify several distinct modes through which organizations seek to govern AI, varying in their emphasis on formal organizational processes, technologicalarrangements, and ongoing interaction among organizational actors. We show how these modes become decoupled, aligned, and reconfigured in practice as organizational actors navigate competing priorities and confront the limitations of different forms of governance. Over time, the relative importance of and relationships among these modes also shift as organizations respond to emerging challenges and uncertainties surrounding AI development. Our study develops a process theory explaining how organizations govern emerging and evolving technologies by combining and reconfiguring multiple governance modes as they negotiate competing value aspirations.

 

(Co-Author: Tamara Thius, KIN Center for Digital Innovation, VU Amsterdam)

 

 

About Natalia Levina

 

Natalia Levina has received her Ph.D. in Information Technology from MIT’s Sloan School of Management and is a Full Chair Professor at New York University Stern School of Business. She focuses on how people span organizational, professional, cultural, and other boundaries while producing and using technological innovations. Currently, she studies the evaluation and adoption of Artificial Intelligence (AI) in medicine and HR, open innovation, theories of smart contracts, and firm-community relationships in crowdsourcing. Prof. Levina is an innovative teacher who has developed a unique course on “Digital Innovation & Crowdsourcing,” which has been receiving stellar evaluations in undergraduate, MBA, and Executive MBA programs. She has been nominated for the Best Professor Award by NYU Stern’s EMBA students. She is a frequent speaker on these topics in academic and industry conferences. Her research has been published in top journals such as Information Systems Research, MIS Quarterly, Organization Science, Academy of Management Journal, Decision Sciences Journal, and Harvard Business Review, among others. For more about Professor Natalia Levina, see her full bio on the NYU Stern website.