AI, Take the Wheel: What Drives Delegation and Trust in Human-Computer Cooperative Question Answering?
arXiv:2605.28255v1 Announce Type: new Abstract: AI systems are fallible, and humans can make mistakes in deciding whether to trust AI over their own judgment. Thus, improving human-AI collaboration requires understanding when, why, and how humans decide to rely on AI. We study two distinct reliance decisions: the delegation choice -- deciding when to let AI act autonomously without knowing its output, and the adoption choice -- evaluating AI suggestions and deciding how to use them. Both of these decoupled reliance patterns shape collaboration, but prior work rarely studies them together in re
The rapid advancement and deployment of generative AI necessitate a deeper understanding of human-AI interaction patterns, particularly concerning trust and delegation in collaborative tasks.
Understanding the dynamics of human-AI trust and delegation is crucial for designing effective AI systems, ensuring user adoption, and mitigating risks associated with over-reliance or under-utilization of AI capabilities.
The explicit decoupling and study of 'delegation choice' versus 'adoption choice' provides a more nuanced framework for analyzing human-AI collaboration beyond simple trust metrics, influencing future AI development and human-AI interface design.
- · AI ethics researchers
- · Human-computer interaction (HCI) designers
- · AI system developers
- · Organizations deploying AI for critical tasks
- · AI systems with opaque decision-making
- · Human-AI collaboration models lacking nuance
- · Sectors with high-stakes autonomous AI deployment
This research will directly inform better design principles for AI systems that need to seamlessly collaborate with humans.
Improved human-AI collaboration could accelerate the integration of AI agents into complex workflows, potentially collapsing certain white-collar tasks faster.
A refined understanding of trust could lead to regulatory frameworks differentiating between AI delegation and adoption, affecting liability and accountability in autonomous systems.
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Read at arXiv cs.AI