Zobrazeno 1 - 10
of 118
pro vyhledávání: '"Wilson, Christo"'
Many existing fairness metrics measure group-wise demographic disparities in system behavior or model performance. Calculating these metrics requires access to demographic information, which, in industrial settings, is often unavailable. By contrast,
Externí odkaz:
http://arxiv.org/abs/2409.08135
Autor:
Hu, Desheng, Aziz, Muhammad Abu Bakar, Gleason, Jeffrey, Koeninger, Alice, Guggenberger, Nikolas, Robertson, Ronald E., Wilson, Christo
Is Google Search a monopoly with gatekeeping power? Regulators from the US, UK, and Europe have argued that it is based on the assumption that Google Search dominates the market for horizontal (a.k.a. "general") web search. Google disputes this, clai
Externí odkaz:
http://arxiv.org/abs/2407.11918
The operationalization of algorithmic fairness comes with several practical challenges, not the least of which is the availability or reliability of protected attributes in datasets. In real-world contexts, practical and legal impediments may prevent
Externí odkaz:
http://arxiv.org/abs/2307.03306
Autor:
Kopec, Matthew, Magnani, Meica, Ricks, Vance, Torosyan, Roben, Basl, John, Miklaucic, Nicholas, Muzny, Felix, Sandler, Ronald, Wilson, Christo, Wisniewski-Jensen, Adam, Lundgren, Cora, Mills, Kevin, Wells, Mark
Embedding ethics modules within computer science courses has become a popular response to the growing recognition that CS programs need to better equip their students to navigate the ethical dimensions of computing technologies like AI, machine learn
Externí odkaz:
http://arxiv.org/abs/2208.05453
In this work we explore the intersection fairness and robustness in the context of ranking: when a ranking model has been calibrated to achieve some definition of fairness, is it possible for an external adversary to make the ranking model behave unf
Externí odkaz:
http://arxiv.org/abs/2205.02414
Do online platforms facilitate the consumption of potentially harmful content? Using paired behavioral and survey data provided by participants recruited from a representative sample in 2020 (n=1,181), we show that exposure to alternative and extremi
Externí odkaz:
http://arxiv.org/abs/2204.10921
Autor:
Robertson, Ronald E., Green, Jon, Ruck, Damian J., Ognyanova, Katherine, Wilson, Christo, Lazer, David
If popular online platforms systematically expose their users to partisan and unreliable news, they could potentially contribute to societal issues like rising political polarization. This concern is central to the echo chamber and filter bubble deba
Externí odkaz:
http://arxiv.org/abs/2201.00074
Systems that offer continuous model monitoring have emerged in response to (1) well-documented failures of deployed Machine Learning (ML) and Artificial Intelligence (AI) models and (2) new regulatory requirements impacting these models. Existing mon
Externí odkaz:
http://arxiv.org/abs/2106.07057
Existing fair ranking systems, especially those designed to be demographically fair, assume that accurate demographic information about individuals is available to the ranking algorithm. In practice, however, this assumption may not hold -- in real-w
Externí odkaz:
http://arxiv.org/abs/2105.02091
In this work, we introduce a novel metric for auditing group fairness in ranked lists. Our approach offers two benefits compared to the state of the art. First, we offer a blueprint for modeling of user attention. Rather than assuming a logarithmic l
Externí odkaz:
http://arxiv.org/abs/1901.10437