Put AI to Work
April 15-18, 2019
New York, NY

Design thinking for AI

Chris Butler (IPsoft)
9:00am12:30pm Tuesday, April 16, 2019
AI Business Summit
Location: Mercury Ballroom
Secondary topics:  AI in the Enterprise, Interfaces and UX
Average rating: *****
(5.00, 1 rating)

Who is this presentation for?

  • Data scientists, engineers, product, design, executives



Prerequisite knowledge

  • Familiarity with AI, ML, and data science (useful but not required)

What you'll learn

  • Explore design thinking-inspired tools, techniques, and workshops to quickly converge on experiments using AI that will positively impact their business


Without human purpose, a computer is just a rock that we tricked into thinking—even if we add AI to it. Without human trust, we are only building novelties that won’t be used for real problems. Any team that is working on hard, meaningful, and purpose-driven problems could benefit from AI/ML, but without the right focus you may end up building toys.

Chris Butler leads you through exercises that borrow from the principles of design thinking to help you create more impactful solutions and better team alignment. You’ll cover problem framing, ideation, empathy mapping for the machine, prototyping through roleplay, and research and leave with the hands-on experience you need to guide your teams and AI projects.

Photo of Chris Butler

Chris Butler


Chris Butler is the chief product architect at IPsoft. Chris has over 19 years of product and business development experience at companies like Microsoft, KAYAK, and Waze. He was first introduced to AI through graph theory and genetic algorithms while studying computer systems engineering at Boston University and has worked on AI-related projects at his startup Complete Seating (data science and constraint programming), Horizon Ventures (advising portfolio companies like Affectiva), and Philosophie (AI consulting and coaching). He’s created techniques like empathy mapping for the machine and confusion mapping to create cross-team alignment while building AI products.

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