Stanford Seminar - Rethinking the AI-UX Boundary for Designing Human-AI Experiences

For more information about Stanford’s Artificial Intelligence programs, visit: stanford.io/33zZ93L
Hari Subramonyam
Stanford University
October 22, 2021
In conventional software development, the boundary between user experience (UX) design and engineering is well defined: designers create specifications based on end-user needs, then engineers build to those specifications. However, AI application design poses a challenge to this "separation of concerns." Emerging Human-AI guidelines show that human-centered design extends beyond the user interface and into the design of AI sub-components and training data, thus 'puncturing' this separation. In this talk, I will share insights about collaboration challenges at the AI-UX boundary and discuss approaches to operationalize the vision for human-centered AI. Based on studies with industry practitioners, I will describe how "leaky" abstractions afford collaboration across expertise boundaries and discuss the critical role of end-user data in generating both AI and UX design specifications. Finally, I will present an approach for prototyping AI-powered interfaces for diverse users and use contexts by directly incorporating end-user data and machine learning models within UX workflows.
Learn more about Stanford's Human-Computer Interaction Group: hci.stanford.edu
Learn about Stanford's Graduate Certificate in HCI: online.stanford.edu/programs/...
View the full playlist: • Stanford CS547 - Human...
0:00 Introduction
0:56 Human-Centered Software Design Workflow
5:47 Human Centered AIX
9:48 USER INTERFACE
10:31 Design-Engineering Boundary INTRODUCES KNOWLEDGE BLINDNESS
13:09 Design-Engineering Boundary RESTRICTS COLLABORATION
14:05 "Al-First" Design Workflow
16:16 Leaky Abstractions ALLEVIATE KNOWLEDGE BLINDNESS
17:25 Leaky Abstractions PROMOTES DESIGN COLLABORATION
18:21 Leaky Abstractions SUPPORTS AIX EVALUATION
26:08 What should Al do for Humans?
29:09 A Process Model for Co-Creating Al Experiences
36:42 DESIGN SPACE FOR MIP
40:31 Expertise & Collaboration
#ux #artificialintelligence