Examining the effect of explanation on satisfaction and trust in AI diagnostic systems

Abstract

Artificial Intelligence has the potential to revolutionize healthcare, and it is increasingly being deployed to support and assist medical diagnosis. One potential application of AI is as the first point of contact for patients, replacing initial diagnoses prior to sending a patient to a specialist, allowing health care professionals to focus on more challenging and critical aspects of treatment. But for AI systems to succeed in this role, it will not be enough for them to merely provide accurate diagnoses and predictions. In addition, it will need to provide explanations (both to physicians and patients) about why the diagnoses are made. Without this, accurate and correct diagnoses and treatments might otherwise be ignored or rejected.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 03, 2021
Source ID
10.1186/s12911-021-01542-6

Entities

People

  • Lamia Alam
  • Shane T Mueller

Organizations

  • Defense Advanced Research Projects Agency

Tags

Fields of Study

  • Medicine

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Medical or Health Care Field.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy