Negotiating Expertise with(in) AI: Dynamics of Identity and Authority at Work

Within the evolving tapestry of contemporary work, algorithmic technologies are becoming fundamental to the structuring and execution of work. Scholarship in this domain has begun to examine the potential impacts of work when AI technologies complement, augment, or even replace aspects of an individual’s workflow (Faraj, Pachidi, and Sayegh, 2018). As a result, employees enact new forms of organizing (e.g., Anthony, 2021; Waardenburg, Huysman, & Sergeeva, 2022) and are called to redefine their professional knowledge boundaries and relationships toward AI (Pakarinen & Huising, 2023). The degree and nature of these changes differ widely across various organizational contexts and individual roles, signaling a shift in the foundational paradigms of work.

For example, generative AI technologies are integrated into workflows as assistants or companions, potentially reshaping conceptualizations and practices of professional identities. In case in point: starting in Fall 2024, Harvard Business School will pair every student with a “virtual AI companion” trained on proprietary course material, illustrating this multi-level integration at a knowledge and relational level. This example extends beyond a tasks, but explores how these technologies shift the identity of what constitutes a team member, peer, or colleague.
Using the ‘trading zones’ framework from anthropology of science (Collins, Evans, & Gorman, 2007), I explore the collaborative interactions between human experts and AI systems using two empirical case studies in (1) talent acquisition/recruiting and (2) advertising. This concept, originally describing how scientists with differing expertise communicate and cooperate, is adapted to analyze how humans and AI navigate their distinct and common understandings. These interactions, marked by mutual yet asymmetrical adaptation, reveal a new ‘algorithmic expertise’ developed through daily AI use in decision-making. This paper investigates how these dynamics alter traditional roles and perceptions of authority, reshaping our identities and our partnerships with technology in these evolving ecosystems.

Anthony, C. (2021). When knowledge work and analytical technologies collide: The practices and consequences of black boxing algorithmic technologies. Administrative Science Quarterly, 66(4), 1173-1212.
Collins, H., Evans, R., & Gorman, M. (2007). Trading zones and interactional expertise. Studies in History and Philosophy of Science Part A, 38(4), 657–666.
Faraj, S., Pachidi, S., & Sayegh, K. (2018). Working and organizing in the age of the learning algorithm. Information and Organization, 28(1), 62–70.
Pakarinen, P. and Huising, R. (2023). Relational expertise: What machines can’t know. Journal of Management Studies.
Waardenburg, L., Huysman, M., & Sergeeva, A. V. (2022). In the land of the blind, the one-eyed man is king: Knowledge brokerage in the age of learning algorithms. Organization Science, 33(1), 59-82.

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