This highly interactive workshop invites participants to collaborate in building upon the IA-for-AI framework that was first presented at IAC 2021. We will work through what it means to understand, translate, and describe the types of situations where human-machine interaction occurs, and the way the relationship between the human and machine changes in real-time.
Participants will identify methodological approaches and dynamic documentation structures that support teams (including UX designers, data scientists, engineers, etc.) in AI system development and ongoing evolution. Participants will collaborate on capturing models, vocabulary, and designs that will be relevant and useful to their team. This workshop covers a wide range of AI application areas such as conversational agents, semi-autonomous and autonomous vehicles, AI-assisted research, decision support systems, and ideally additional contributions by the participants.
Participants will gain an understanding of the opportunities and responsibilities that IA brings to human-AI relationships; ability to identify vital approaches for creating a shared, coordinated interaction between a person and a machine in AI environments; and what needs to be learned from users – and when – throughout the lifecycle of research, design, development and ongoing use.
Workshop attendees are not presumed to currently work on AI systems, but rather this is a step forward in preparing IAs to do that work. Even without experience, the discussion aims to teach attendees vocabulary and sensitize them to the responsibilities and role of IA within an AI team.
About the speakers
Duane Degler is a partner in Design for Context, a Washington DC/Baltimore-based usable design consultancy. He specializes in the design of sophisticated interactive applications and search experiences, with an eye to making rich data resources usable and relevant. He has led web and software projects for commercial and government clients in the US and Europe. He authored the “Dynamic IA” chapter in the book Reframing Information Architecture (2014). Since 2003, he has focused on the unique challenges and opportunities that arise when designing specifically for linked data and semantically-enabled applications.
Carol Smith (@carologic) is a Senior Research Scientist in Human-Machine Interaction at Carnegie Mellon University’s Software Engineering Institute and an adjunct instructor for CMU’s Human-Computer Interaction Institute (HCII). She has been conducting user research to improve the human experience across industries for 20 years and working to improve AI systems since 2015. Carol holds an M.S. in Human-Computer Interaction from DePaul University. She is an active community organizer – including helping to plan the World IA Day celebrations in Pittsburgh, PA – where she enjoys outdoor activities with her family, running and playing soccer.