SXSW 2024
Designing Successful AI Products and Services
Description:
Today, most AI projects fail. Teams choose the wrong things to build. Based on 10 years of researching challenges in AI innovation as well as insights from teaching technical, business, and design students how to innovate with AI, we discuss how to brainstorm low-risk, high-value AI concepts, things that are buildable and desirable. Neither user-centered nor technology-centered approaches work. We discuss how to integrate aspects of both while focusing on situations where moderate model performance generates value for users and service providers.
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Takeaways
- Poor ideation causes AI project failures. Data scientists think of things customers don’t want and designers think of things that cannot be built.
- User-centered design fails because the solution must be AI. It turns the innovation team into hammers looking for nails.
- When teams brainstorm, they focus on concepts that need excellent performance. Yet most successful AI systems offer only moderate model performance.
Speakers
- John Zimmerman, Tang Family Professor of AI and HCI, Carnegie Mellon University
- Nur Yildirim, PhD Candidate, Carnegie Mellon University
Organizer
John Zimmerman, Tang Family Professor Of Ai And Hci, Carnegie Mellon University
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