Abstract

Crowdsourcing and human computation have become indispensable methods for leveraging collective intelligence in the collaboration between humans and AI. This presentation provides an overview of key challenges and recent advances in this field, focusing on three main topics.

First, it discusses quality control in crowdsourcing, including the aggregation of crowd responses, truth inference, and learning from noisy crowd labels. Second, it introduces case studies of crowdsourcing applications beyond data collection tasks.

Finally, it explores emerging challenges in the era of large language models (LLMs). 

A/Prof Jiyi Li (fourth from left), guest speaker at the AAII seminar on 13 October 2025, with AAII researchers and students.
A/Prof Jiyi Li (fourth from left), guest speaker at the AAII seminar on 13 October 2025, with AAII researchers and students

Speaker

Jiyi Li received the Ph.D. degree from the Graduate School of Informatics, Kyoto University, Japan. He is currently an Associate Professor with the Graduate School of Information Science and Technology, Hokkaido University, Japan.

His research interests include crowdsourcing and human computation, data mining and machine learning, natural language processing, and multimedia. He has published more than 90 papers in international conferences and journals, including AAAI, IJCAI, WWW, SIGIR, ACL, EMNLP, MM, CIKM and ICASSP. He received the 19th DBSJ Kambayashi Young Researcher Award from the Database Society of Japan.