Trusting automation: Designing for responsivity and resilience
Objective This paper reviews recent articles related to human trust in automation to guide
research and design for increasingly capable automation in complex work environments …
research and design for increasingly capable automation in complex work environments …
A systematic review of human–computer interaction and explainable artificial intelligence in healthcare with artificial intelligence techniques
Artificial intelligence (AI) is one of the emerging technologies. In recent decades, artificial
intelligence (AI) has gained widespread acceptance in a variety of fields, including virtual …
intelligence (AI) has gained widespread acceptance in a variety of fields, including virtual …
Expectation vs. experience: Evaluating the usability of code generation tools powered by large language models
Recent advances in Large Language Models (LLM) have made automatic code generation
possible for real-world programming tasks in general-purpose programming languages …
possible for real-world programming tasks in general-purpose programming languages …
Explanations can reduce overreliance on ai systems during decision-making
H Vasconcelos, M Jörke… - Proceedings of the …, 2023 - dl.acm.org
Prior work has identified a resilient phenomenon that threatens the performance of human-
AI decision-making teams: overreliance, when people agree with an AI, even when it is …
AI decision-making teams: overreliance, when people agree with an AI, even when it is …
To trust or to think: cognitive forcing functions can reduce overreliance on AI in AI-assisted decision-making
People supported by AI-powered decision support tools frequently overrely on the AI: they
accept an AI's suggestion even when that suggestion is wrong. Adding explanations to the …
accept an AI's suggestion even when that suggestion is wrong. Adding explanations to the …
Expanding explainability: Towards social transparency in ai systems
As AI-powered systems increasingly mediate consequential decision-making, their
explainability is critical for end-users to take informed and accountable actions. Explanations …
explainability is critical for end-users to take informed and accountable actions. Explanations …
Does the whole exceed its parts? the effect of ai explanations on complementary team performance
Many researchers motivate explainable AI with studies showing that human-AI team
performance on decision-making tasks improves when the AI explains its recommendations …
performance on decision-making tasks improves when the AI explains its recommendations …
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 …
[PDF][PDF] Ai transparency in the age of llms: A human-centered research roadmap
QV Liao, JW Vaughan - arXiv preprint arXiv:2306.01941, 2023 - assets.pubpub.org
The rise of powerful large language models (LLMs) brings about tremendous opportunities
for innovation but also looming risks for individuals and society at large. We have reached a …
for innovation but also looming risks for individuals and society at large. We have reached a …
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 …