Social Agentics

Matt Ratto, Anastasia Kuzminykh, Shion Guha, Edith Law, John Vines

Abstract: Agentic AI is being heralded as the next step in the development of AI systems. Agentics, complex ensembles of different machine learning, data processing, and generative AI models, can provide new autonomous and proactive decision-making capabilities to organizations, participate in complex workflows, and, when needed, seek guidance from and provide insights to human users in natural languages. Collectively, we wish to explore how and why to design agentic systems to be situated within specific social and organizational contexts, the value of social theory and perspectives to this work, and the potential of this move to address critical issues with AI. Given the focus on social and organization context as essential to agentic design, we see this work as directly related to the CSCW community. We seek to bring together scholars from the diversity of disciplines within CSCW to develop research agendas, projects, and joint teaching initiatives that support the development of social agentic design and analysis.

External IDs:doi:10.1145/3715070.3748276