Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities

JK Paulus, DM Kent - NPJ digital medicine, 2020 - nature.com
The machine learning community has become alert to the ways that predictive algorithms
can inadvertently introduce unfairness in decision-making. Herein, we discuss how concepts …

Fairness in recommender systems: research landscape and future directions

Y Deldjoo, D Jannach, A Bellogin, A Difonzo… - User Modeling and User …, 2024 - Springer
Recommender systems can strongly influence which information we see online, eg, on
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …

Fairness and explanation in AI-informed decision making

A Angerschmid, J Zhou, K Theuermann… - Machine Learning and …, 2022 - mdpi.com
AI-assisted decision-making that impacts individuals raises critical questions about
transparency and fairness in artificial intelligence (AI). Much research has highlighted the …

The emergence of economic rationality of GPT

Y Chen, TX Liu, Y Shan… - Proceedings of the …, 2023 - National Acad Sciences
As large language models (LLMs) like GPT become increasingly prevalent, it is essential
that we assess their capabilities beyond language processing. This paper examines the …

How computers see gender: An evaluation of gender classification in commercial facial analysis services

MK Scheuerman, JM Paul, JR Brubaker - Proceedings of the ACM on …, 2019 - dl.acm.org
Investigations of facial analysis (FA) technologies-such as facial detection and facial
recognition-have been central to discussions about Artificial Intelligence's (AI) impact on …

The contribution of data-driven technologies in achieving the sustainable development goals

N Bachmann, S Tripathi, M Brunner, H Jodlbauer - Sustainability, 2022 - mdpi.com
The United Nations' Sustainable Development Goals (SDGs) set out to improve the quality of
life of people in developed, emerging, and developing countries by covering social and …

How we've taught algorithms to see identity: Constructing race and gender in image databases for facial analysis

MK Scheuerman, K Wade, C Lustig… - Proceedings of the ACM …, 2020 - dl.acm.org
Race and gender have long sociopolitical histories of classification in technical
infrastructures-from the passport to social media. Facial analysis technologies are …

It's compaslicated: The messy relationship between rai datasets and algorithmic fairness benchmarks

M Bao, A Zhou, S Zottola, B Brubach… - arXiv preprint arXiv …, 2021 - arxiv.org
Risk assessment instrument (RAI) datasets, particularly ProPublica's COMPAS dataset, are
commonly used in algorithmic fairness papers due to benchmarking practices of comparing …

A review of predictive policing from the perspective of fairness

K Alikhademi, E Drobina, D Prioleau… - Artificial Intelligence and …, 2022 - Springer
Abstract Machine Learning has become a popular tool in a variety of applications in criminal
justice, including sentencing and policing. Media has brought attention to the possibility of …

Prediction-based decisions and fairness: A catalogue of choices, assumptions, and definitions

S Mitchell, E Potash, S Barocas, A D'Amour… - arXiv preprint arXiv …, 2018 - arxiv.org
A recent flurry of research activity has attempted to quantitatively define" fairness" for
decisions based on statistical and machine learning (ML) predictions. The rapid growth of …