Topic: Joint ISEA-ENBIS Webinar: Generative AI Applications and Opportunities for Business and Industrial Statisticians
Speaker: Fadel M. Megahed
Date: May 10, 10am Eastern Time / 4pm Central European Time / 7 am Pacific Time
Abstract
Fadel M. Megahed, Ying-Ju (Tessa) Chen, L. Allison Jones-Farmer, Joshua Ferris, Sven Knoth, Younghwa (Gabe) Lee, Douglas C. Montgomery, Brooke Wang, Inez Zwetsloot
Generative AI tools such as ChatGPT and Claude have captured global attention. These systems are fast, accessible, and increasingly powerful. Yet, their practical use in business and industrial statistics is still emerging. This talk will introduce key ideas and highlight how our community can shape the responsible use of generative AI.
We will present real examples from our recent research and applications:
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Using generative AI for structured text extraction and annotation, including when and how to assess reliability (with a quick demo using our structured text extraction app ).
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Building chatbots to support business analytics education (e.g., ChatISA) and quality control practice (e.g., ChatSQC).
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Adapting OpenAI’s CLIP model for image inspection in manufacturing settings, including a public tool to try few-shot learning with your own industrial images (with the CLIP for Industrial Quality Control tool).
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Demonstrating how these tools can support forecasting workflows in time series analysis using our StatsForecast app.
This will be an interactive webinar. Attendees can test several web-based tools and leave with simple code snippets and use cases they can explore in their organizations. We will highlight risks, such as model hallucinations and over-reliance on AI-generated content, and suggest practical steps to evaluate whether generative AI suits a given task.
Learning outcomes:
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Understand how LLMs and vision models like CLIP can be used in your work.
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Identify realistic use cases and red flags.
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Access open-source tools and examples for structured text, chatbot development, image inspection, and forecasting.
Whether you are an academic or a practitioner, this session aims to show that our community has an important role in evaluating and applying generative AI tools; not just using them but shaping how they are used in our organizations.
Bio:
Fadel M. Megahed is a Miami University Faculty Scholar and a Professor of Information
Systems & Analytics. He received his Ph.D. and M.S. in Industrial and Systems Engineering from Virginia Tech and a B.S. in Mechanical Engineering from the American University in Cairo. His main research streams include applied artificial intelligence (AI) and statistical surveillance, with applications in manufacturing, public health, and occupational health & safety. His work in these areas has been funded by Aflac, The American Society for Safety Engineers (ASSE) Foundation, GE Research, Gore, The National Institute for Occupational Safety and Health (NIOSH), and The National Science Foundation (NSF). Dr. Megahed has 56 peer-reviewed journal papers, four invited editorials/discussions, and 12 conference proceedings. His research findings and views have been covered in over 50 media articles.
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