Since its inception in the 2000s, AI for Software Engineering (AI4SE) has grown rapidly, with the MSR community playing a pivotal role. By analyzing data in various repositories, AI in its different forms, e.g., data mining, information retrieval, machine learning, natural language processing, etc., has been demonstrated to be able to produce good results for automating many tasks, including specification mining, bug and vulnerability discovery, bug localization, duplicate bug report identification, failure detection, program repair, technical question answering, code search, and many more. AI4SE has much potential to improve software engineers’ productivity and software quality. Due to its potential, it is currently one of the most popular research areas in the software engineering field.

To advance AI4SE, this talk highlights the need for Human-Centered AI4SE. Without considering humans, it is easy for AI-powered tools to hinder rather than help humans in their job or introduce unwanted and unacceptable side effects. Human-centered AI4SE puts humans (i.e., software practitioners) at the forefront of the design of AI4SE tools, aiming to amplify and augment software practitioners’ capabilities. This talk will describe some requirements of human-centered AI4SE. Specifically, among others, the need to (i) listen to humans, (ii) learn from (and like) humans, and (iii) synergize with humans. For the first two requirements, I will present a reflection on relevant work we have done in the last decade and a vision of what we can do to push forward Human-Centered AI4SE.

David Lo is a Professor of Computer Science and Director of the Information Systems and Technology Cluster at the School of Computing and Information Systems, Singapore Management University. For nearly two decades, he has championed AI4SE, specifically demonstrating how AI – including data mining, machine learning, information retrieval, natural language processing, and search-based algorithms – can transform passive software engineering data stored in various software repositories into automation and insights. He has published 400+ AI4SE papers that have gathered 25k+ citations. He has won 20+ international awards, including the IEEE TCSE Distinguished Service award, two Test-of-Time (or Most Influential Paper) awards, and six ACM Distinguished Paper awards. He is an IEEE Fellow (for contributions to synergizing software engineering and data mining), Fellow of Automated Software Engineering (for significant and sustained contributions to the automated software engineering community), ACM Distinguished Member, and NRF Investigator (2023-28). He served as the GC of MSR’22 and PC Co-Chair of ASE’20 and is serving as a PC Co-Chair of ESEC/FSE’24 and ICSE’25. More information about him and his work can be found at: http://www.mysmu.edu/faculty/davidlo/.