The Human Factor in AI Red Teaming: Perspectives from Social and Collaborative Computing

Rapid progress in general-purpose AI has sparked significant interest in "red teaming," a practice of adversarial testing originating in military and cybersecurity applications. AI red teaming raises many questions about the human factor, such as how red teamers are selected, biases and blindspots in how tests are conducted, and harmful content's psychological effects on red teamers. A growing body of HCI and CSCW literature examines related practices-including data labeling, content moderation, and algorithmic auditing. However, few, if any, have investigated red teaming itself. This workshop seeks to consider the conceptual and empirical challenges associated with this practice, often rendered opaque by non-disclosure agreements. Future studies may explore topics ranging from fairness to mental health and other areas of potential harm. We aim to facilitate a community of researchers and practitioners who can begin to meet these challenges with creativity, innovation, and thoughtful reflection.

The Users Aren't Alright: Dangerous Mental Illness Behaviors and Recommendations

In this paper, we argue that recommendation systems are in a unique position to propagate dangerous and cruel behaviors to people with mental illnesses.

To Infinity and Beyond! Accessibility is the Future for Kids' Search Engines

Research in the area of search engines for children remains in its infancy. Seminal works have studied how children use mainstream search engines, as well as how to design and evaluate custom search engines explicitly for children. These works, however, tend to take a one-size-fits-all view, treating children as a unit. Nevertheless, even at the same age, children are known to possess and exhibit different capabilities. These differences affect how children access and use search engines. To better serve children, in this vision paper, we spotlight accessibility and discuss why current research on children and search engines does not, but should, focus on this significant matter.

Pink for Princesses, Blue for Superheroes: The Need to Examine Gender Stereotypes in Kid's Products in Search and Recommendations

In this position paper, we argue for the need to investigate if and how gender stereotypes manifest in search and recommender systems.As a starting point, we particularly focus on how these systems may propagate and reinforce gender stereotypes through their results in learning environments, a context where teachers and children in their formative stage regularly interact with these systems. We provide motivating examples supporting our concerns and outline an agenda to support future research addressing the phenomena.