Towards a science of human-AI decision making: An overview of design space in empirical human-subject studies
AI systems are adopted in numerous domains due to their increasingly strong predictive
performance. However, in high-stakes domains such as criminal justice and healthcare, full …
performance. However, in high-stakes domains such as criminal justice and healthcare, full …
Towards a science of human-ai decision making: a survey of empirical studies
As AI systems demonstrate increasingly strong predictive performance, their adoption has
grown in numerous domains. However, in high-stakes domains such as criminal justice and …
grown in numerous domains. However, in high-stakes domains such as criminal justice and …
Who is included in human perceptions of AI?: Trust and perceived fairness around healthcare AI and cultural mistrust
MK Lee, K Rich - Proceedings of the 2021 CHI conference on human …, 2021 - dl.acm.org
Emerging research suggests that people trust algorithmic decisions less than human
decisions. However, different populations, particularly in marginalized communities, may …
decisions. However, different populations, particularly in marginalized communities, may …
Toward involving end-users in interactive human-in-the-loop AI fairness
Ensuring fairness in artificial intelligence (AI) is important to counteract bias and
discrimination in far-reaching applications. Recent work has started to investigate how …
discrimination in far-reaching applications. Recent work has started to investigate how …
[HTML][HTML] The methodology of studying fairness perceptions in Artificial Intelligence: Contrasting CHI and FAccT
The topic of algorithmic fairness is of increasing importance to the Human–Computer
Interaction research community following accumulating concerns regarding the use and …
Interaction research community following accumulating concerns regarding the use and …
Fairness evaluation in text classification: Machine learning practitioner perspectives of individual and group fairness
Mitigating algorithmic bias is a critical task in the development and deployment of machine
learning models. While several toolkits exist to aid machine learning practitioners in …
learning models. While several toolkits exist to aid machine learning practitioners in …
Diversity in sociotechnical machine learning systems
S Fazelpour, M De-Arteaga - Big Data & Society, 2022 - journals.sagepub.com
There has been a surge of recent interest in sociocultural diversity in machine learning
research. Currently, however, there is a gap between discussions of measures and benefits …
research. Currently, however, there is a gap between discussions of measures and benefits …
Towards responsible AI: A design space exploration of human-centered artificial intelligence user interfaces to investigate fairness
With Artificial intelligence (AI) to aid or automate decision-making advancing rapidly, a
particular concern is its fairness. In order to create reliable, safe and trustworthy systems …
particular concern is its fairness. In order to create reliable, safe and trustworthy systems …
The impact of algorithmic risk assessments on human predictions and its analysis via crowdsourcing studies
As algorithmic risk assessment instruments (RAIs) are increasingly adopted to assist
decision makers, their predictive performance and potential to promote inequity have come …
decision makers, their predictive performance and potential to promote inequity have come …
Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making
In this work, we study the effects of feature-based explanations on distributive fairness of AI-
assisted decisions, specifically focusing on the task of predicting occupations from short …
assisted decisions, specifically focusing on the task of predicting occupations from short …