Building Human Values into Recommender Systems: An Interdisciplinary Synthesis
Recommender systems are the algorithms which select, filter, and personalize content across many of the world?s largest platforms and apps. As such, their positive and negative effects on individuals and on societies have been extensively theorized and studied. Our overarching question is how to ens...
| Main Authors: | , , , , , , , , , , , , , , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
ACM
2023
|
| Online Access: | https://hdl.handle.net/1721.1/153135 |
| _version_ | 1826196291204415488 |
|---|---|
| author | Stray, Jonathan Halevy, Alon Assar, Parisa Hadfield-Menell, Dylan Boutilier, Craig Ashar, Amar Bakalar, Chloe Beattie, Lex Ekstrand, Michael Leibowicz, Claire Moon Sehat, Connie Johansen, Sara Kerlin, Lianne Vickrey, David Singh, Spandana Vrijenhoek, Sanne Zhang, Amy Andrus, McKane Helberger, Natali Proutskova, Polina |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Stray, Jonathan Halevy, Alon Assar, Parisa Hadfield-Menell, Dylan Boutilier, Craig Ashar, Amar Bakalar, Chloe Beattie, Lex Ekstrand, Michael Leibowicz, Claire Moon Sehat, Connie Johansen, Sara Kerlin, Lianne Vickrey, David Singh, Spandana Vrijenhoek, Sanne Zhang, Amy Andrus, McKane Helberger, Natali Proutskova, Polina |
| author_sort | Stray, Jonathan |
| collection | MIT |
| description | Recommender systems are the algorithms which select, filter, and personalize content across many of the world?s largest platforms and apps. As such, their positive and negative effects on individuals and on societies have been extensively theorized and studied. Our overarching question is how to ensure that recommender systems enact the values of the individuals and societies that they serve. Addressing this question in a principled fashion requires technical knowledge of recommender design and operation, and also critically depends on insights from diverse fields including social science, ethics, economics, psychology, policy and law. This paper is a multidisciplinary effort to synthesize theory and practice from different perspectives, with the goal of providing a shared language, articulating current design approaches, and identifying open problems. We collect a set of values that seem most relevant to recommender systems operating across different domains, then examine them from the perspectives of current industry practice, measurement, product design, and policy approaches. Important open problems include multi-stakeholder processes for defining values and resolving trade-offs, better values-driven measurements, recommender controls that people use, non-behavioral algorithmic feedback, optimization for long-term outcomes, causal inference of recommender effects, academic-industry research collaborations, and interdisciplinary policy-making. |
| first_indexed | 2024-09-23T10:24:34Z |
| format | Article |
| id | mit-1721.1/153135 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T10:24:34Z |
| publishDate | 2023 |
| publisher | ACM |
| record_format | dspace |
| spelling | mit-1721.1/1531352024-02-05T19:53:17Z Building Human Values into Recommender Systems: An Interdisciplinary Synthesis Stray, Jonathan Halevy, Alon Assar, Parisa Hadfield-Menell, Dylan Boutilier, Craig Ashar, Amar Bakalar, Chloe Beattie, Lex Ekstrand, Michael Leibowicz, Claire Moon Sehat, Connie Johansen, Sara Kerlin, Lianne Vickrey, David Singh, Spandana Vrijenhoek, Sanne Zhang, Amy Andrus, McKane Helberger, Natali Proutskova, Polina Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Recommender systems are the algorithms which select, filter, and personalize content across many of the world?s largest platforms and apps. As such, their positive and negative effects on individuals and on societies have been extensively theorized and studied. Our overarching question is how to ensure that recommender systems enact the values of the individuals and societies that they serve. Addressing this question in a principled fashion requires technical knowledge of recommender design and operation, and also critically depends on insights from diverse fields including social science, ethics, economics, psychology, policy and law. This paper is a multidisciplinary effort to synthesize theory and practice from different perspectives, with the goal of providing a shared language, articulating current design approaches, and identifying open problems. We collect a set of values that seem most relevant to recommender systems operating across different domains, then examine them from the perspectives of current industry practice, measurement, product design, and policy approaches. Important open problems include multi-stakeholder processes for defining values and resolving trade-offs, better values-driven measurements, recommender controls that people use, non-behavioral algorithmic feedback, optimization for long-term outcomes, causal inference of recommender effects, academic-industry research collaborations, and interdisciplinary policy-making. 2023-12-12T13:44:15Z 2023-12-12T13:44:15Z 2023-12-01T08:45:10Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/153135 Stray, Jonathan, Halevy, Alon, Assar, Parisa, Hadfield-Menell, Dylan, Boutilier, Craig et al. "Building Human Values into Recommender Systems: An Interdisciplinary Synthesis." ACM Transactions on Recommender Systems. PUBLISHER_POLICY en http://dx.doi.org/10.1145/3632297 ACM Transactions on Recommender Systems Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The author(s) application/pdf ACM Association for Computing Machinery |
| spellingShingle | Stray, Jonathan Halevy, Alon Assar, Parisa Hadfield-Menell, Dylan Boutilier, Craig Ashar, Amar Bakalar, Chloe Beattie, Lex Ekstrand, Michael Leibowicz, Claire Moon Sehat, Connie Johansen, Sara Kerlin, Lianne Vickrey, David Singh, Spandana Vrijenhoek, Sanne Zhang, Amy Andrus, McKane Helberger, Natali Proutskova, Polina Building Human Values into Recommender Systems: An Interdisciplinary Synthesis |
| title | Building Human Values into Recommender Systems: An Interdisciplinary Synthesis |
| title_full | Building Human Values into Recommender Systems: An Interdisciplinary Synthesis |
| title_fullStr | Building Human Values into Recommender Systems: An Interdisciplinary Synthesis |
| title_full_unstemmed | Building Human Values into Recommender Systems: An Interdisciplinary Synthesis |
| title_short | Building Human Values into Recommender Systems: An Interdisciplinary Synthesis |
| title_sort | building human values into recommender systems an interdisciplinary synthesis |
| url | https://hdl.handle.net/1721.1/153135 |
| work_keys_str_mv | AT strayjonathan buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT halevyalon buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT assarparisa buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT hadfieldmenelldylan buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT boutiliercraig buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT asharamar buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT bakalarchloe buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT beattielex buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT ekstrandmichael buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT leibowiczclaire buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT moonsehatconnie buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT johansensara buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT kerlinlianne buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT vickreydavid buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT singhspandana buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT vrijenhoeksanne buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT zhangamy buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT andrusmckane buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT helbergernatali buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis AT proutskovapolina buildinghumanvaluesintorecommendersystemsaninterdisciplinarysynthesis |