Neural Signatures of Trust During Human-Automation Interactions
Abstract
The objective of this proposal was to investigate the similarities and differences of the neural systems of human-automation trust (HAT) and human-human trust (HHT) in a series of three studies that combined an X-ray luggage-screening task with functional magnetic resonance imaging by manipulating the reliability of advice from a human or automated luggage inspector framed as experts. HAT and HHT were measured as the acceptance rates of advice either giving by the machine or the human agent. Comparing HAT with HHT, those studies provide first neural evidence that reliable (study 1) and unreliable (false alarm [study2] and misses [study 3]) human-automation interactions evoke unique brain activation patterns linked with the reward network for reinforcement learning (e.g., dorsal striatum head, ventromedial prefrontal cortex), the mentalizing network for evaluating personal characteristics and traits (e.g., precuneus, temporoparietal junction), and the salience network for interoception (e.g.,insula, anterior cingulate cortex). The findings are relevant to the Air Force Office of Scientific Researchs mission aimed at investing in the discovery of the foundational concepts of trust building and trust calibration during complex human-machine interactions.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 01, 2016
- Accession Number
- AD1008319
Entities
People
- Frank Krueger
Organizations
- George Mason University