Understanding Frontline Workers' and Unhoused Individuals' Perspectives on AI Used in Homeless Services
Recent years have seen growing adoption of AI-based decision-support systems (ADS) in
homeless services, yet we know little about stakeholder desires and concerns surrounding …
homeless services, yet we know little about stakeholder desires and concerns surrounding …
Ethical considerations and fairness in the use of artificial intelligence for neuroradiology
In this review, concepts of algorithmic bias and fairness are defined qualitatively and
mathematically. Illustrative examples are given of what can go wrong when unintended bias …
mathematically. Illustrative examples are given of what can go wrong when unintended bias …
Limits and possibilities for “Ethical AI” in open source: A study of deepfakes
Open source software communities are a significant site of AI development, but “Ethical AI”
discourses largely focus on the problems that arise in software produced by private …
discourses largely focus on the problems that arise in software produced by private …
Fairness through robustness: Investigating robustness disparity in deep learning
Deep neural networks (DNNs) are increasingly used in real-world applications (eg facial
recognition). This has resulted in concerns about the fairness of decisions made by these …
recognition). This has resulted in concerns about the fairness of decisions made by these …
The many faces of fairness: Exploring the institutional logics of multistakeholder microlending recommendation
Recommender systems have a variety of stakeholders. Applying concepts of fairness in such
systems requires attention to stakeholders' complex and often-conflicting needs. Since …
systems requires attention to stakeholders' complex and often-conflicting needs. Since …
Equity and artificial intelligence in education: will" aied" amplify or alleviate inequities in education?
K Holstein, S Doroudi - arXiv preprint arXiv:2104.12920, 2021 - arxiv.org
The development of educational AI (AIEd) systems has often been motivated by their
potential to promote educational equity and reduce achievement gaps across different …
potential to promote educational equity and reduce achievement gaps across different …
Equity and artificial intelligence in education
K Holstein, S Doroudi - The ethics of artificial intelligence in …, 2022 - taylorfrancis.com
The development of educational AI (AIED) systems has often been motivated by their
potential to promote educational equity and reduce achievement gaps across different …
potential to promote educational equity and reduce achievement gaps across different …
Assessing methods and tools to improve reporting, increase transparency, and reduce failures in machine learning applications in health care
Artificial intelligence applications for health care have come a long way. Despite the
remarkable progress, there are several examples of unfulfilled promises and outright …
remarkable progress, there are several examples of unfulfilled promises and outright …
Social Choice for Heterogeneous Fairness in Recommendation
Algorithmic fairness in recommender systems requires close attention to the needs of a
diverse set of stakeholders that may have competing interests. Previous work in this area …
diverse set of stakeholders that may have competing interests. Previous work in this area …
[PDF][PDF] A performance-preserving fairness intervention for adaptive microfinance recommendation
Recommender systems are among the most widely-deployed and frequently-encountered
machine learning systems for the general public. The fairness properties of such systems …
machine learning systems for the general public. The fairness properties of such systems …