The Potential of Generative AI for Analyzing Large Textual Assets

Overview

This internal research webinar will explore how Generative AI can enhance the processing, organization, and accessibility of large textual datasets at the ILO. Using Labour Force Survey (LFS) questionnaires as a case study, we will discuss the broader implications of these tools for improving research workflows and knowledge management.

Building on the findings from the research brief "A New Chapter for the ILO’s Textual Assets: Applying Generative AI to Labour Force Survey Questionnaires," the session will highlight the integration of AI vision capabilities, semantic search through vector-based embeddings, and automation of research summaries—demonstrating how these technologies can support ILO’s data-driven work.

Key Topics

🔹 Automating the structuring and retrieval of large textual datasets using Generative AI
🔹 Extracting and digitizing survey content with AI vision and human verification
🔹 Enhancing searchability through AI-driven vector-based embeddings
🔹 Automating research summaries to improve accessibility for diverse users
🔹 Demonstrating the interactive AI search tool and open-source repository
🔹 Exploring the broader potential of AI for ILO’s research and policy work

Speakers & Panelists

• Janine Berg, Senior Economist, RESEARCH (Moderator)
• Pawel Gmyrek, Senior Researcher, RESEARCH (Presenter)

Who Should Attend?

This session is open to ILO colleagues interested in AI-driven approaches for managing and analyzing large textual datasets, with a focus on research applications and policy development.