Fairness in streaming submodular maximization: Algorithms and hardness
Submodular maximization has become established as the method of choice for the task of
selecting representative and diverse summaries of data. However, if datapoints have …
selecting representative and diverse summaries of data. However, if datapoints have …
Bias in evaluation processes: an optimization-based model
Biases with respect to socially-salient attributes of individuals have been well documented in
evaluation processes used in settings such as admissions and hiring. We view such an …
evaluation processes used in settings such as admissions and hiring. We view such an …
Group-level fairness maximization in online bipartite matching
We consider the allocation of limited resources to heterogeneous customers who arrive in
an online fashion. We would like to allocate the resources" fairly", so that no group of …
an online fashion. We would like to allocate the resources" fairly", so that no group of …
Disentangling and operationalizing AI fairness at linkedin
Operationalizing AI fairness at LinkedIn's scale is challenging not only because there are
multiple mutually incompatible definitions of fairness but also because determining what is …
multiple mutually incompatible definitions of fairness but also because determining what is …
Fairness maximization among offline agents in online-matching markets
Online matching markets (OMMs) are commonly used in today's world to pair agents from
two parties (whom we will call offline and online agents) for mutual benefit. However, studies …
two parties (whom we will call offline and online agents) for mutual benefit. However, studies …
Wise Fusion: Group Fairness Enhanced Rank Fusion
Rank fusion is a technique for combining multiple rankings into a single aggregated ranking,
commonly used in high-stakes applications. For hiring decisions, a fused ranking might …
commonly used in high-stakes applications. For hiring decisions, a fused ranking might …
Don't let Ricci v. DeStefano hold you back: A bias-aware legal solution to the hiring paradox
Companies that try to address inequality in employment face a hiring paradox. Failing to
address workforce imbalance can result in legal sanctions and scrutiny, but proactive …
address workforce imbalance can result in legal sanctions and scrutiny, but proactive …
Online fair allocation of perishable resources
We consider a practically motivated variant of the canonical online fair allocation problem: a
decision-maker has a budget of resources to allocate over a fixed number of rounds. Each …
decision-maker has a budget of resources to allocate over a fixed number of rounds. Each …
Robust online selection with uncertain offer acceptance
Online advertising has motivated interest in online selection problems. Displaying ads to the
right users benefits both the platform (eg, via pay-per-click) and the advertisers (by …
right users benefits both the platform (eg, via pay-per-click) and the advertisers (by …
Fairness as a Robust Utilitarianism
M Liu, Q Meng, G Yu, ZH Zhang - Production and …, 2024 - journals.sagepub.com
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focuses on the social choice problem in which decisions are based on the utility of multiple …
focuses on the social choice problem in which decisions are based on the utility of multiple …