Report on the Search Futures Workshop at ECIR 2024
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Published:2024-06
Issue:1
Volume:58
Page:1-41
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ISSN:0163-5840
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Container-title:ACM SIGIR Forum
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language:en
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Short-container-title:SIGIR Forum
Author:
Azzopardi Leif1, Clarke Charles L. A.2, Kantor Paul3, Mitra Bhaskar4, Trippas Johanne R.5, Ren Zhaochun6, Aliannejadi Mohammad7, Arabzadeh Negar2, Chandrasekar Raman8, de Rijke Maarten7, Eustratiadis Panagiotis7, Hersh William9, Huang Jin10, Kanoulas Evangelos7, Kareem Jasmin11, Li Yongkang7, Lupart Simon7, Mekonnen Kidist Amde7, Roegiest Adam12, Soboroff Ian13, Silvestri Fabrizio14, Verberne Suzan6, Vos David10, Yang Eugene15, Zhao Yuyue10
Affiliation:
1. University of Strathclyde, UK 2. University of Waterloo, Canada 3. University of Wisconsin Madison, USA 4. Microsoft, Canada 5. RMIT University, Australia 6. Leiden University, The Netherlands 7. University of Amsterdam, Netherlands 8. Institute for Experiential AI, Northeastern University, USA 9. Oregon Health & Science University, USA 10. University of Amsterdam, The Netherlands 11. Eindhoven University of Technology, Netherlands 12. Zuva, Canada 13. NIST, USA 14. Sapienza University of Rome, Italy 15. Johns Hopkins University, USA
Abstract
The First Search Futures Workshop, in conjunction with the
Fourty-sixth European Conference on Information Retrieval (ECIR)
2024, looked into the future of search to ask questions such as:
• How can we harness the power of generative AI to enhance, improve and re-imagine Information Retrieval (IR)?
• What are the principles and fundamental rights that the field of Information Retrieval should strive to uphold?
• How can we build trustworthy IR systems in light of Large Language Models and their ability to generate content at super human speeds?
• What new applications and affordances does generative AI offer and enable, and can we go back to the future, and do what we only dreamed of previously?
The workshop started with seventeen lightning talks from a diverse set speakers. Instead of conventional paper presentations, the lightning talks provided a rapid and concise overview of ideas, allowing speakers to share critical points or novel concepts quickly. This format was designed to encourage discussion and introduce a wide range of topics within a short period, thereby maximising the exchange of ideas and ensuring that participants could gain insights into various future search areas without the deep dive typically required in longer presentations. This report, co-authored by the workshop's organisers and its participants, summarises the talks and discussions. This report aims to provide the broader IR community with the insights and ideas discussed and debated during the workshop - and to provide a platform for future discussion.
Date
: 24 March 2024.
Website
: https://searchfutures.github.io/.
Publisher
Association for Computing Machinery (ACM)
Reference206 articles.
1. Syed Wajid Aalam, Abdul Basit Ahanger, Muzafar Rasool Bhat, and Assif Assad. Evaluation of fairness in recommender systems: A review. In International Conference on Emerging Technologies in Computer Engineering, pages 456--465. Springer, 2022. 2. Amin Abolghasemi, Suzan Verberne, Arian Askari, and Leif Azzopardi. Retrievability Bias Estimation Using Synthetically Generated Queries. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, pages 3712--3716, 2023. 3. Amin Abolghasemi, Leif Azzopardi, Arian Askari, Maarten de Rijke, and Suzan Verberne. Measuring Bias in a Ranked List Using Term-Based Representations. In European Conference on Information Retrieval, pages 3--19. Springer, 2024. 4. Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. GPT-4 technical report. arXiv preprint arXiv:2303.08774, 2023. 5. Marwah Alaofi, Negar Arabzadeh, Charles LA Clarke, and Mark Sanderson. Generative information retrieval evaluation. arXiv preprint arXiv:2404.08137, 2024.
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