CowPilot: A Framework for Autonomous and Human-Agent Collaborative Web NavigationWeb agents capable of conducting web activities on user behalf have gained attention for their task automation potential. However, they often fall short on complex tasks in dynamic, real-world contexts, making it essential for users to work collaboratively with the agent. We present CowPilot, a framework supporting both autonomous and human-agent collaborative web navigation, and evaluation across task success, user experience, and task efficiency. CowPilot eases human effort by starting with agents proposing next steps, meanwhile allowing humans to execute, pause, or reject agent-proposed steps and take alternative actions instead; supporting seamless action-taking between agent and human participants. We conduct case studies on five websites and find that human-agent collaborative mode achieves the highest 95% success rate while requiring humans to perform only 15.2% of the total steps. Even with human interventions during task execution, the agent successfully drives up to half of task success on its own. CowPilot serves as a useful tool for data collection and agent evaluation across websites, which we hope will facilitate further advances.
