Matches in SemOpenAlex for { <https://semopenalex.org/work/W3135468018> ?p ?o ?g. }
- W3135468018 abstract "Decision-making systems increasingly orchestrate our world: how to intervene on the algorithmic components to build fair and equitable systems is therefore a question of utmost importance; one that is substantially complicated by the context-dependent nature of fairness and discrimination. Modern decision-making systems that involve allocating resources or information to people (e.g., school choice, advertising) incorporate machine-learned predictions in their pipelines, raising concerns about potential strategic behavior or constrained allocation, concerns usually tackled in the context of mechanism design. Although both machine learning and mechanism design have developed frameworks for addressing issues of fairness and equity, in some complex decision-making systems, neither framework is individually sufficient. In this paper, we develop the position that building fair decision-making systems requires overcoming these limitations which, we argue, are inherent to each field. Our ultimate objective is to build an encompassing framework that cohesively bridges the individual frameworks of mechanism design and machine learning. We begin to lay the ground work towards this goal by comparing the perspective each discipline takes on fair decision-making, teasing out the lessons each field has taught and can teach the other, and highlighting application domains that require a strong collaboration between these disciplines." @default.
- W3135468018 created "2021-03-15" @default.
- W3135468018 creator A5009598002 @default.
- W3135468018 creator A5019843700 @default.
- W3135468018 creator A5035213985 @default.
- W3135468018 creator A5039527953 @default.
- W3135468018 creator A5052541789 @default.
- W3135468018 creator A5062163239 @default.
- W3135468018 creator A5086820426 @default.
- W3135468018 date "2021-03-01" @default.
- W3135468018 modified "2023-10-16" @default.
- W3135468018 title "Bridging Machine Learning and Mechanism Design towards Algorithmic Fairness" @default.
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