A Framework for Effective AI Recommendations in Cyber-Physical-Human Systems

arXiv:2403.05715v1 Announce Type: cross
Abstract: Many cyber-physical-human systems (CPHS) involve a human decision-maker who may receive recommendations from an artificial intelligence (AI) platform while holding the ultimate responsibility of making decisions. In such CPHS applications, the human decision-maker may depart from an optimal recommended decision and instead implement a different one for various reasons. In this letter, we develop a rigorous framework to overcome this challenge. In our framework, we consider that humans may deviate from AI recommendations as they …

abstract ai recommendations applications artificial artificial intelligence arxiv cs.ai cs.hc cs.lg cs.sy cyber decision decisions eess.sy framework human intelligence maker making platform recommendations responsibility systems type