To err is human
Bias salience can help overcome resistance to medical AI
Bibliographic Data
| ID | 21561979 |
|---|---|
| Authors | Mathew S Isaac (0000-0002-3182-1341, Seattle University, corresponding author), Rebecca Jen-Hui Wang (0000-0002-7006-8460, Lehigh University), Lucy E Napper (0000-0002-2510-3407, Lehigh University), Jessecae K Marsh (0000-0001-7064-1151, Lehigh University) |
| Year | 2024 |
| Volume | 161 |
| Pages | 108402 |
| Publication date | 2024-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Computers in Human Behavior (JOURNAL) |
| Journal identifiers | ISSN: 0747-5632 • E-ISSN: 1873-7692 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.chb.2024.108402 |
| OpenAlex | W4401569217 |
| Language | EN |
| Citations received | 3 |
| References cited | 55 |
Biology · Cognitive psychology · Artificial Intelligence in Healthcare and Education · Computer Science · Ethics and Social Impacts of AI · Explainable Artificial Intelligence (XAI · Psychology · Social Psychology
Revolutionizing healthcare
Task-Dependent Algorithm Aversion
Consumers and Artificial Intelligence
Role of fairness, accountability, and transparency in algorithmic affordance
Bias in data‐driven artificial intelligence systems—An introductory survey
Physicians and Implicit Bias
High-performance medicine
AI in health and medicine
The effects of explainability and causability on perception, trust, and acceptance
User Perceptions of Algorithmic Decisions in the Personalized AI System
The future of artificial intelligence at work
Where is the human in human-centered AI? Insights from developer priorities and user experiences
Artificial intelligence, transparency, and public decision-making
In AI we trust? Perceptions about automated decision-making by artificial intelligence
Understanding user sensemaking in fairness and transparency in algorithms
Fairness perceptions of algorithmic decision-making
Improving Global Healthcare and Reducing Costs Using Second-Generation Artificial Intelligence-Based Digital Pills
Bias and error in human judgment
Understanding perception of algorithmic decisions
Understanding, explaining, and utilizing medical artificial intelligence
Resistance to Medical Artificial Intelligence
Single-Paper Meta-Analysis
Taking the Full Measure
Understanding and Improving Consumer Reactions to Service Bots
| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2025 - 2026 (2) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 3 |