Tasks, Copilots, and the Future of Search: A Keynote at SIGIR 2023

Author:

White Ryen W.1

Affiliation:

1. Microsoft Research, Redmond, WA, USA

Abstract

Search is far from being a solved problem. While search engines may cope well with simple tasks, searchers and systems struggle as task complexity increases. Task is central to the search process, motivating the search and driving search behavior. Complex search tasks require more than support for rudimentary fact finding or re-finding. Various support options have been offered by search systems over time (e.g., query suggestions, contextual search) to help search engine users more effectively tackle complex tasks. The recent emergence of generative artificial intelligence (AI) and the arrival of assistive agents, or copilots , based on this technology, has the potential to offer further assistance to searchers, especially those engaged in complex tasks. The implications from these advances for the design of intelligent systems and for the future of search itself are significant. This overview of the keynote that I gave at the 2023 ACM SIGIR Conference introduces AI copilots and briefly presents some of the challenges and opportunities for researching, developing, and deploying search copilots. Date : 26 July 2023.

Publisher

Association for Computing Machinery (ACM)

Reference30 articles.

1. Eugene Agichtein, Ryen W White, Susan T Dumais, and Paul N Bennett. Search, interrupted: Understanding and predicting search task continuation. In Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 315--324, 2012.

2. Where should the person stop and the information search interface start?

3. Anomalous states of knowledge as a basis for information retrieval;Belkin Nicholas J;Canadian Journal of Information Science,1980

4. Modeling the impact of short- and long-term behavior on search personalization

5. Andrei Z Broder and Preston McAfee. Delphic costs and benefits in web search: A utilitarian and historical analysis. arXiv preprint arXiv:2308.07525, 2023.

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