The Organization, Markets and Governance (OMG) group at IOA invites to a seminar on

Generative machine learning and professional knowledge work

with Professor James Faulconbridge

Generative Artificial Intelligence, the technology behind innovations like ChatGPT and Midjourney, is revolutionizing human behavior and the organization of professional work. In the Danish financial sector alone, 59% of firms report to use this technology which has only been available for about two years.

Join us for an engaging seminar, where James Faulconbridge will present his timely research on how generative machine learning is reshaping professional work.

Hosted by: Leonard Seabrooke

Seminar Agenda:

• 10:00–10:25 Presentation by James Faulconbridge
• 10:25–10:45 Discussion and Q&A

We look forward to your participation.

Information about his paper:

Generative machine learning and professional knowledge work: a literature review and research agenda

Our purpose in this paper is to address the need for a conceptual framework for understanding the impacts of generative machine learning on professional work and PSFs through what Elsbach and Van Knippenberg (2020) describe as an integrative literature review. Specifically, in line with the recognised need for “broad reviews of emerging topics in need of initial synthesis” which “set the stage for future research” (Elsbach and Van Knippenberg, 2020: 1284), we build a framework for examining the implications of generative machine learning for professional work and PSFs. Through our integrative review, we consider how pre-existing questions raised by earlier generations of algorithmic technologies and extractive machine learning are now becoming even more pertinent as change becomes even quicker and extensive as a result of generative machine learning. In particular, we argue that change will continue to be mediated by professionals and their responses to generative machine learning and the decisions taken within PSFs (often by professionals) about how to adopt the technology. We thus argue that a framework for understanding the mediated adoption of generative machine learning is needed. We outline the different dimensions of this framework, how it produces a recursive process of change in professional work and PSFs, and the research questions posed by the framework.