Knowledge Gathering and Scoping
Abstract
When a healthcare AI system began recommending unnecessary procedures, investigators did not start by analyzing algorithms or examining training data—they began by talking to people. Radiologists revealed that the system’s confidence scores did not match their clinical experience. Data scientists disclosed preprocessing decisions made months earlier under tight deadlines. Hospital administrators explained workflow pressures that affected how recommendations were being interpreted and applied. Only after gathering this human intelligence could investigators determine what technical evidence to collect and how to analyze it meaningfully.
Fields of Study & Subjects
Artificial Intelligence in Healthcare and Education
Explainable Artificial Intelligence (XAI)
Ethics and Social Impacts of AI
Publication details
- Journal / source
- Chapman & Hall/CRC eBooks
- Pages
- 69–88
- Publication date
- 2 February 2026
- Language
- EN
- Document type
- Book chapter