26 papers · ranked by Valyu relevance
Indrė Žliobaitė
Nowadays, many decisions are made using predictive models built on historical data. Predictive models may systematically discriminate groups of people even if the computing process is fair and well-intentioned. Discrimination-aware data mining studies how to make predictive models free from discrimination, when…
Annamaria Öblom, Jan Antfolk, Asim Zia
Ethnic and gender discrimination in a variety of markets has been documented in several populations. We conducted an online field experiment to examine ethnic and gender discrimination in the private rental housing market in Finland. We sent 1459 inquiries regarding 800 apartments. We compared responses to standardized…
Elias Baumann, Josef Lorenz Rumberger
Machine learning is becoming an ever present part in our lives as many decisions, e.g. to lend a credit, are no longer made by humans but by machine learning algorithms. However those decisions are often unfair and discriminating individuals belonging to protected groups based on race or gender. With the recent General…
Xavier Ferrer, Tom van Nuenen, José M. Such, Mark Coté + 1 more
'Natalia Criado'] Abstract—With the widespread and pervasive use of Artificial Intelligence (AI) for automated decision-making systems, AI bias is becoming more apparent and problematic. One of its negative consequences is discrimination: the unfair, or unequal treatment of individuals based on certain characteristics.…
Donna Cormack, James Stanley, Ricci Harris
Background The complex ways in which experiences of discrimination are patterned in society, including the exposure of communities to multiple overlapping forms of discrimination within social systems of oppression, is increasingly recognised in the health sciences. However, research examining the impacts on health and…
Pieter-Paul Verhaeghe, Mariña Fernández-Reino, Valentina Di Stasio
Research on the causes and consequences of ethnic and racial discrimination is central to social, economic, and psychological sciences. Discrimination is defined as the unequal and unfair treatment of people because of their (perceived) ethnic or racial origin. While US scholars have focused on race-based…
Ruth A. Hackett, Amy Ronaldson, Kamaldeep Bhui, Andrew Steptoe + 1 more
'Sarah E. Jackson'] Background Racism has been linked with poor health in studies in the United States. Little is known about prospective associations between racial discrimination and health outcomes in the United Kingdom (UK). Methods Data were from 4883 ethnic minority (i.e. non-white) participants in the UK…
Olaf von dem Knesebeck, Jens Klein
Background It has consistently been shown that perceived discrimination is associated with adverse health outcomes. Despite this uncontested relevance, there is a lack of research on the experiences of discrimination in health care. Therefore, the following research questions were addressed: (1) How often do people in…
Shreya Atrey
The central case methodology captures the features that something must have in order for it to be that thing. As applied to the field of discrimination law, the methodology helps identify both the central cases of discrimination as well as the key features of discrimination law which address such discrimination.…
Hilde Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen + 1 more
'Mykola Pechenizkiy'] Concerns regarding unfairness and discrimination in the context of artificial intelligence (AI) systems have recently received increased attention from both legal and computer science scholars. Yet, the degree of overlap between notions of algorithmic bias and fairness on the one hand, and legal…
Nicholas J. Goode, Eric Potter, Meerab Rasheed, Mariela Camacho + 8 more
Discrimination is a chronic stressor linked to adverse health outcomes, particularly in racial and ethnic minorities. Understanding associations between early discrimination and the brain in childhood may help identify mechanisms through which discrimination impacts future health. Data from 4512 children (ages 9-11)…
Colin Wayne Leach, Chloe Bracegirdle, Nils Karl Reimer, Danny Osborne + 3 more
'Danny Osborne' 'Chris G. Sibley' 'Ralf Wölfer' 'Nikhil Kumar Sengupta'] Contact with members of one’s own group (ingroup) and other groups (outgroups) shapes individuals’ beliefs about the world, including perceptions of discrimination against one’s ingroup. Research to date indicates that, among members of…
Lisa Koutsoviti Koumeri, Magali Legast, Yasaman Yousefi, Koen Vanhoof + 2 more
'Koen Vanhoof' 'Axel Legay' 'Christoph Schommer'] Empirical evidence suggests that algorithmic decisions driven by Machine Learning (ML) techniques threaten to discriminate against legally protected groups or create new sources of unfairness. This work supports the contextual approach to fairness in EU…
Lu Zhang, Yongkai Wu, Xintao Wu
Discrimination discovery and prevention/removal are increasingly important tasks in data mining. Discrimination discovery aims to unveil discriminatory practices on the protected attribute (e.g., gender) by analyzing the dataset of historical decision records, and discrimination prevention aims to remove discrimination…
Michele Loi, Francesco Nappo, Eleonora Viganò
The widespread use of algorithms for prediction-based decisions urges us to consider the question of what it means for a given act or practice to be discriminatory. Building upon work by Kusner and colleagues in the field of machine learning, we propose a counterfactual condition as a necessary requirement on…
Giorgos Giannopoulos, Maria Psalla, Loukas Kavouras, Dimitris Sacharidis + 3 more
law Authors: ['Giorgos Giannopoulos' 'Maria Psalla' 'Loukas Kavouras' 'Dimitris Sacharidis' 'Jakub Mareček' 'German Martinez Matilla' 'Ioannis Z. Emiris'] Abstract—In this paper we examine algorithmic fairness from the perspective of law aiming to identify best practices and strategies for the specification and…
Marie E. Portuallo, David Y. Lu, Gretchen M. Alicea, Joel Bolling + 7 more
Last October, within the 2021 SMR congress, we held the inaugural Diversity in Science Session. The goal of the session was to discuss diversity, equity, and inclusion in the melanoma research community and strategies to promote the advancement of underrepresented melanoma researchers. An international survey was…
Hudson P Santos, Benjamin C Nephew, Arjun Bhattacharya, Xianming Tan + 6 more
Latina mothers, who have the highest fertility rate among all ethnic groups in the US, are often exposed to discrimination. The biological impacts of this discrimination are unknown. This study is the first to explore the relationship between discrimination and DNA methylation of stress regulatory genes in Latinas. Our…
Arjun Roy, Jan Horstmann, Eirini Ntoutsi
AI-driven decision-making can lead to discrimination against certain individuals or social groups based on protected characteristics/attributes such as race, gender, or age. The domain of fairness-aware machine learning focuses on methods and algorithms for understanding, mitigating, and accounting for bias in AI/ML…
Matthew Gardner, Alexander Power, Rachael Andrews, Gyles Cozier + 15 more
Alexander Power 2 , Matthew Gardner 1 , Rachael Andrews 1 , Gyles Cozier 2 , Ranjeet Kumar 1 , Tom Freeman 1 , Ian Blagbrough 1 , Jennifer Scott 3 , Anca Frinculescu 4 , Trevor Shine 4 , Gillian Taylor 5 , Caitlyn Norman 6 , Herve Menard 6 , Niamh Nic Daeid 6 , Oliver Sutcliffe 7 , Stephen Husbands 1 , Richard Bowman 8…
Maxwell A. Bertolero, Jordan D. Dworkin, Sophia U. David, Claudia López Lloreda + 11 more
Discrimination against racial and ethnic minority groups exists in the academy, and the associated biases impact hiring and promotion, publication rates, grant funding, and awards. Precisely how racial and ethnic bias impacts the manner in which the scientific community engages with the ideas of academics in minority…
Authors not listed
In the United States, people of color are disproportionately and unjustly exposed to air pollution. Historically, environmental policy has emphasized aggregate emission reductions; yet major emission reduction scenarios do not sufficiently mitigate relative exposure disparities. Here, we show that without focusing on…
Authors not listed
People of color in the United States are disproportionately and unfairly exposed to air pollution. Equity-oriented scientific evaluations quantifying these disparities often use population-average exposure metrics to capture the overall inequality within a system. Utilizing these metrics involves choices about the…
Michael Moutoussis, Joe Barnby, Anais Durand, Megan Croal + 3 more
Attributing motives to others is a crucial aspect of mentalizing, can be biased by prejudice, and also is affected by common psychiatric disorders. It is therefore important to understand in depth the mechanisms underpinning it. Toward improving models of mentalizing motives, we hypothesized that people quickly infer…
Biao Chen, Wenhuan Huang, Guoqing Zhang
Chiral recognition with molecular luminescence is a beneficial but challenging method due to an often lack of dramatic difference in intermolecular interactions between the chiral analyte/substrate pair versus their enantiomeric counterpart. Here we show that the difference in room-temperature phosphorescence (RTP) can…
Libby Koolik, Álvaro Alvarado, Amy Budahn, Laurel Plummer + 2 more
As policymakers increasingly focus on environmental justice, a key question is whether emissions reductions aimed at addressing air quality or climate change can also ameliorate persistent air pollution exposure disparities. We examine evidence from California's aggressive vehicle emissions control policy from…