Human-AI Teaming Under Deception: An Implicit BCI Safeguards Drone Team Performance in Virtual Reality

TL;DR

This study demonstrates that a passive Brain-Computer Interface can protect human-AI teams from AI deception in VR drone tasks by decoupling neural signals from biased behavior, significantly improving team accuracy under high workload.

Contribution

Introduces a neuro-decoupled team strategy using passive BCI to enhance resilience against AI deception in high-stakes VR environments, a novel approach in human-AI teaming research.

Findings

Passive BCI maintains higher team accuracy under AI deception.

Neuro-decoupled teams outperform behavior-based teams in error resilience.

BCI-based predictions rely on preserved sensory signals, not biased behavior.

Abstract

Human-AI teams can be vulnerable to catastrophic failure when feedback from the AI is incorrect, especially under high cognitive workload. Traditional team aggregation methods, such as voting, are susceptible to these AI errors, which can actively bias the behaviour of each individual and inflate the likelihood of an erroneous group decision. We hypothesised that a collaborative Brain-Computer Interface (cBCI) using neural activity collected before a behavioural decision is made can provide a source of information that is "decoupled" from this biased behaviour, thereby protecting the team from the deleterious influence of AI error. We tested this in a VR drone surveillance task where teams of operators faced high workload and systematically misleading AI cues. Using a passive BCI (pBCI) framework validated via offline simulation, we compared traditional behaviour-based team strategies against a purely Neuro-Decoupled Team (NDT) that used only BCI confidence scores derived from pre-response EEG. Under AI deception, behaviour-based teams catastrophically failed, with Majority Vote accuracy collapsing to 42.6% (worse than chance). The NDT, however, maintained a robust 68.3% accuracy. While this did not exceed the best individual's theoretical maximum, it provided a critical +25.7% "Safety Net Delta" that prevented the team from succumbing to the correlated error. This resilience was explained by a neuro-behavioural decoupling, where the BCI's predictions relied on preserved posterior-visual processing ("The Truth Signal") while the operators' executive monitoring systems collapsed. We conclude that an implicit BCI provides resilience by learning to bypass a compromised executive networks and access the preserved sensory representation of ground truth, defending against AI-induced error in high-stakes environments.