1868. Soft OR and generative AI
Invited abstract in session WA-41: Impact of AI on Soft OR, stream Soft OR and Problem Structuring Methods.
Wednesday, 8:30-10:00Room: Newlyn GR.01
Authors (first author is the speaker)
| 1. | Leroy White
|
| University of Exeter Business School |
Abstract
Studies on OR and AI have a long and intertwined history, with no doubt about OR’s contribution to predictive AI—particularly in the field of machine learning. However, when applying OR to complex interventions or to solve previously unexplored problems, it is important to distinguish between predictive AI (where machines often outperform humans in specific tasks) and the emerging generation of AI built on large language models (LLMs), which promotes close collaboration between humans and machines to generate novel insights. At the same time, concerns are growing about the efficacy of generative AI in augmenting human tasks, especially in highly complex or high-risk contexts that demand Soft OR approaches. This presentation argues that by adopting a broader perspective of AI and embracing a responsible approach to integrating generative AI into interventions, OR can resolve these tensions and achieve synergies that benefit both organisations and society. Given the rapid advances and capabilities of novel LLMs, there is a pressing need to deepen our understanding of ‘AI-in-the making’, moving beyond the polarised debates of hope and fear that currently dominate the headlines.
Keywords
- Soft OR
- Artificial Intelligence
Status: accepted
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