Survey of explainable AI techniques in healthcare
Artificial intelligence (AI) with deep learning models has been widely applied in numerous
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …
domains, including medical imaging and healthcare tasks. In the medical field, any judgment …
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 …
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 …
Debugging tests for model explanations
We investigate whether post-hoc model explanations are effective for diagnosing model
errors--model debugging. In response to the challenge of explaining a model's prediction, a …
errors--model debugging. In response to the challenge of explaining a model's prediction, a …
In search of verifiability: Explanations rarely enable complementary performance in AI‐advised decision making
The current literature on AI‐advised decision making—involving explainable AI systems
advising human decision makers—presents a series of inconclusive and confounding …
advising human decision makers—presents a series of inconclusive and confounding …