Qian Yang / Human-AI Interaction Design at Scale: Practices, Methods, Challenges / 10.22.21

Qian Yang is an assistant professor in information science at Cornell University. As a human-AI interaction researcher, she helps translate AI’s algorithmic advances into valuable real-world applications that serve human ends. Yang has so far designed several high-consequence AI applications: from decision support systems for life-and-death healthcare decisions (i.e. artificial heart implants and cancer diagnoses) to context-aware mobile services, from Natural Language Generation systems to autonomous cars. Building upon this related vein of practice, she works to inform a basic understanding of AI as a material for HCI design. In addition, she innovates methods and tools for the UX design and HCI practicing communities, helping them to better integrate AI into their day-to-day practices.

Talk: Human-AI Interaction Design at Scale: Practices, Methods, Challenges

Abstract: Some claim AI is the “new electricity” due to its growing ubiquity and significance. My work examines this vision from a human-centered design perspective: How can we situate AI’s algorithmic advances in ways people perceive as valuable and unobtrusive? How can we design interactions to improve the user-perceived AI fairness and agency? In this talk, I discuss a number of past and ongoing research projects that systematically investigate these questions. Projects include designing assemblages of decision support systems for clinical practice and designing an intelligent writing assistant using large language models. In each project, we met users and stakeholders in their real-world contexts. Each project illuminates how HCI and design methods can help improve user adoption and appreciation of AI’s algorithmic advances. Each identifies new research opportunities in scaling up human considerations, especially in the age of large foundation models and AI assemblages.

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