[HTML][HTML] The role of explainability in creating trustworthy artificial intelligence for health care: a comprehensive survey of the terminology, design choices, and …
Artificial intelligence (AI) has huge potential to improve the health and well-being of people,
but adoption in clinical practice is still limited. Lack of transparency is identified as one of the …
but adoption in clinical practice is still limited. Lack of transparency is identified as one of the …
The state of the art in enhancing trust in machine learning models with the use of visualizations
Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …
[图书][B] Human-centered AI
B Shneiderman - 2022 - books.google.com
The remarkable progress in algorithms for machine and deep learning have opened the
doors to new opportunities, and some dark possibilities. However, a bright future awaits …
doors to new opportunities, and some dark possibilities. However, a bright future awaits …
What do we want from Explainable Artificial Intelligence (XAI)?–A stakeholder perspective on XAI and a conceptual model guiding interdisciplinary XAI research
Abstract Previous research in Explainable Artificial Intelligence (XAI) suggests that a main
aim of explainability approaches is to satisfy specific interests, goals, expectations, needs …
aim of explainability approaches is to satisfy specific interests, goals, expectations, needs …
Bridging the gap between ethics and practice: guidelines for reliable, safe, and trustworthy human-centered AI systems
B Shneiderman - ACM Transactions on Interactive Intelligent Systems …, 2020 - dl.acm.org
This article attempts to bridge the gap between widely discussed ethical principles of Human-
centered AI (HCAI) and practical steps for effective governance. Since HCAI systems are …
centered AI (HCAI) and practical steps for effective governance. Since HCAI systems are …
Questioning the AI: informing design practices for explainable AI user experiences
A surge of interest in explainable AI (XAI) has led to a vast collection of algorithmic work on
the topic. While many recognize the necessity to incorporate explainability features in AI …
the topic. While many recognize the necessity to incorporate explainability features in AI …
Human-centered explainable ai (xai): From algorithms to user experiences
QV Liao, KR Varshney - arXiv preprint arXiv:2110.10790, 2021 - arxiv.org
In recent years, the field of explainable AI (XAI) has produced a vast collection of algorithms,
providing a useful toolbox for researchers and practitioners to build XAI applications. With …
providing a useful toolbox for researchers and practitioners to build XAI applications. With …
Interpreting interpretability: understanding data scientists' use of interpretability tools for machine learning
Machine learning (ML) models are now routinely deployed in domains ranging from criminal
justice to healthcare. With this newfound ubiquity, ML has moved beyond academia and …
justice to healthcare. With this newfound ubiquity, ML has moved beyond academia and …
Are explanations helpful? a comparative study of the effects of explanations in ai-assisted decision-making
This paper contributes to the growing literature in empirical evaluation of explainable AI
(XAI) methods by presenting a comparison on the effects of a set of established XAI methods …
(XAI) methods by presenting a comparison on the effects of a set of established XAI methods …
Toward trustworthy AI development: mechanisms for supporting verifiable claims
With the recent wave of progress in artificial intelligence (AI) has come a growing awareness
of the large-scale impacts of AI systems, and recognition that existing regulations and norms …
of the large-scale impacts of AI systems, and recognition that existing regulations and norms …