AI systems are increasingly incorporated into human decision-making. Yet, human decision-makers are often affected by cognitive biases – defined as mental shortcuts to make faster but less deliberate decisions. The use of AI systems can trigger, amplify and exacerbate cognitive biases in their users. In critical settings like medical diagnosis, criminal judgment, or information consumption, cognitive biases and AI systems together influence decision making, thereby resulting in dangerous decisions and negative societal impact.

The role of cognitive biases in human-AI collaboration has become a growing discourse in the CSCW community. Diverse forms of studies address the question of how cognitive biases manifest themselves and how they could be effectively mitigated. Understanding and effectively mitigating cognitive biases are challenging tasks, however, particularly due to the inherent property of cognitive biases in which people are not aware of them, while many individual, contextual, and situational factors affect how cognitive biases would manifest.

In this one-day workshop, we seek to foster discussions on ongoing research around cognitive biases in human-AI collaboration and identify future research directions to understand, quantify, and mitigate the effects of cognitive biases. We will explore cognitive biases appearing in various contexts of human-AI collaboration: what can cause them?; how can we measure, model, mitigate, and manage cognitive biases?; and how can we utilise cognitive biases for the greater good? We will reflect on workshop discussions to form a research community around cognitive biases and bias-aware systems.

Submit your contribution if you are interested in attending. Please refer to Call for Particiation for the submission formats.