Speaker: Hila Lifshitz (Warwick)
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Time: Wednesday, 17 December at 9.30 am EST / 2.30 pm GMT. This webinar is scheduled for 90 minutes, including Q&A.
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Registration: Please register using the Zoom link here to receive a personalized link and a reminder prior to the event.
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As generative AI becomes increasingly used by management researchers, it raises questions about how we develop and maintain our scholarly expertise. In this webinar, we will discuss how management researchers can engage with AI in ways that enhance their expertise rather than diminishing it. We will explore the central tensions facing our field: enhancing productivity vs building expertise that enables us to conduct meaningful research in the age of AI. We will also discuss how different approaches to AI use shape the research expertise and the knowledge we produce, along with the assumptions underlying the framing of AI as a productivity enhancement tool, and what researchers might be overlooking. We will touch on the considerations, trade-offs, and boundary questions that researchers must navigate as we collectively shape how AI tools become part of management scholarship.
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Suggested readings:
- Randazzo, S., Joshi, A., Kellogg, K. C., Lifshitz, H., Dell'Acqua, F., & Lakhani, K. R. (2025) GenAI as a power persuader: How professionals get persuasion bombed when they attempt to validate LLMs (Harvard Business School Working Paper No. 26-021).
- Dell'Acqua, F., Rajendran, S., McFowland, E. III, Krayer, L., Mollick, E., Candelon, F., Lifshitz, H., Lakhani, K. R., & Kellogg, K. C. (2023) Navigating the jagged technological frontier: Field experimental evidence of the effects of AI on knowledge worker productivity and quality (Harvard Business School Working Paper No. 24-013).
- Lebovitz, S., Lifshitz, H., Levina, N. (2022) To Engage or Not to Engage with AI for Critical Judgments: How Professionals Deal with Opacity When Using AI for Medical Diagnosis. Organization Science 33(1):126-148.
About the speaker
Hila Lifshitz is a Professor of Management at Warwick Business School and a faculty affiliate at Harvard University, at the Lab for Innovation Science. Her research focuses on developing an in-depth empirical and theoretical understanding of the micro-foundations of scientific and technological innovation and knowledge creation processes in the digital age.
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Ibrat Djabbarov
Imperial College London
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