Personal Control and Responsibility Measure: A Psychometric Evaluation

Meca, Alan

doi:10.25148/etd.fi12072703

DOI: 10.25148/etd.fi12072703

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Personal Control and Responsibility Measure: A Psychometric Evaluation

Alan Meca¹

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References 44 publications

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Building Human Values into Recommender Systems: An Interdisciplinary Synthesis

Stray,

Halevy,

Assar

et al. 2024

ACM Trans. Recomm. Syst.

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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.

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Building Human Values into Recommender Systems: An Interdisciplinary Synthesis

Stray,

Halevy,

Assar

et al. 2024

ACM Trans. Recomm. Syst.

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Personal Control and Responsibility Measure: A Psychometric Evaluation

Cited by 1 publication

References 44 publications

Building Human Values into Recommender Systems: An Interdisciplinary Synthesis

Building Human Values into Recommender Systems: An Interdisciplinary Synthesis

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