Why Designers Should be Building AI
summary
Designers claim they must build AI themselves and show how a Philips Data-Enabled Design team assembles real systems: connected toothbrushes, shaver, skin device, accelerometers, screens and a conversational UI that creates an evolving interest profile from qualitative prompts plus sensor data. A lab light uses Bayesian surprise to model perceptual crossing; a toothbrush that “won’t switch off” proves personalized rules can emerge and work in situ. Hospital datasets and oncology and bariatric pilots validate the approach.
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chapters (17)
- 0:00Introduction
- 1:17Why designers should be building AI
- 3:45Design Thinking for AI
- 6:17Philips AI
- 7:16Health Care Journey
- 7:43Data and AI
- 9:09Healthcare transformation
- 10:00Experience design
- 10:56Design community
- 13:56Data Enable Design
- 14:45Data in Design
- 15:20Data to Insights
- 20:45Involvement
- 28:58Personalization
- 31:40Caring when it matters
- 32:55Care modules
- 35:30Toothbrush example
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