Daniel Holman
Papers
2
Total Citations
16
H-Index
2
About
Daniel Holman is an emerging researcher whose work sits at the critical intersection of human-robot interaction, trust, and high-stakes decision-making. His research investigates how humans form and calibrate trust in artificial agents, particularly in scenarios where the consequences of misplaced confidence can be severe or irreversible. Holman's most notable contribution, "Overtrust in AI Recommendations About Whether or Not to Kill" (2024), has already garnered 14 citations and represents a bold step into one of the most ethically charged frontiers in AI research. Using an innovative visual challenge paradigm simulating threat identification — distinguishing enemy combatants from civilians under uncertainty — Holman's work provides empirical evidence that humans can dangerously overtrust AI judgment in life-or-death contexts. His complementary research on virtual reality simulations of emergency evacuation scenarios further demonstrates that people readily defer to robotic guidance even when robots behave erroneously. Together, these studies reveal a consistent and troubling pattern of human over-reliance on autonomous systems. Holman's scholarship carries significant implications for military ethics, public safety policy, and the responsible design of AI systems, making his work essential reading for anyone grappling with the societal integration of autonomous agents.
Research Focus
Key Achievements
Top Papers
- 1
- 2