Report on CHIIR 2026 Workshop on Generative AI and Academic Search (GAI&AS)

2026-06-07

AI Summary

Generative artificial intelligence is transforming academic search from traditional document retrieval toward intelligent, interactive paradigms, yet it faces significant challenges concerning transparency, trustworthiness, and support for higher-order cognitive tasks. This work addresses these issues by organizing the CHIIR 2026 workshop—the first initiative to systematically integrate perspectives from information retrieval and human-computer interaction. Centered on three core themes—foundational principles, application scenarios, and “search as learning”—the project explores the design and evaluation of generative academic search systems leveraging conversational interaction, literature summarization, recommendation, and knowledge synthesis. By fostering cross-disciplinary consensus and identifying critical research directions, this effort advances a human-centered paradigm for next-generation academic search and catalyzes sustained community collaboration and innovation.

Abstract

This report summarizes the CHIIR 2026 Workshop on Generative AI and Academic Search (GAI\&AS), which examined how GenAI is reshaping academic search systems and research practices. The workshop brought together researchers in human information interaction and information retrieval to explore key challenges and opportunities in designing and evaluating future academic search systems that integrate GenAI, moving beyond traditional document retrieval to support summarization, recommendation, synthesis, and conversational interaction. Participants' interests and discussions focused on three thematic clusters: foundations and principles, applications and opportunities, and search-as-learning. Across these themes, the workshop highlighted the importance of academic search systems in supporting transparency, credibility, research integrity, and long-term scholarly needs, as well as in fostering higher-order cognitive processes. Participants discussed guiding theories, design principles, methodological approaches, partnerships, and community-building efforts aimed at advancing human-centered GenAI-enhanced academic search systems. Overall, the workshop demonstrated strong community interest and a diverse range of ongoing and emerging research initiatives at the intersection of GenAI and academic search.

Problem

• Generative AI
• Academic Search
• Research Integrity
• Information Retrieval
• Human Information Interaction

Innovation

• Generative AI
• Academic Search
• Conversational Interaction
• Search-as-Learning
• Human-Centered Design