How do we introduce AI into high-stakes human environments without losing trust, safety, judgment, or effectiveness?
This episode features a conversation with Lacey Picazo, CEO and founder of ZoCo Design, a research and design consultancy focused on helping organizations build human-centered digital products and AI experiences. Lacey, a professional product designer by trade, is a serial entrepreneur with strong opinions on the ways customer behavior interplays with AI and can change depending on the application or the environment. With host Shannon Peavey, Lacey discusses a case study where her firm worked with mTuitive, a leader in digital pathology and cancer care, in order to illuminate the way behavioral science, workflow design, and human-centered product thinking can shape whether AI succeeds or fails in clinical environments.
Rather than treating AI adoption as a purely technical challenge, this episode explores how clinicians and patients respond emotionally, cognitively, and behaviorally when AI enters decision-making processes, and why “more automation” is not always better.
This is a thoughtful discussion about innovation, responsibility, understanding the rewards - as well as the risks - of a future that is reckoning with finding the right formulas for human-machine collaboration. Importantly, it also addresses the ways we can support the next generation in an AI-shaped world.
Lacey is part of our exclusive new Product Rising podcast series, where host Shannon Peavey explores the world of AI Ethics, Safety & Responsibility .
00:00 Intro to the topic: AI enters healthcare
01:33 Why healthcare is different from other industries
04:05 Consumer product thinking doesn't always work
05:54 The stakeholder problem: patients, providers, payers, and more
07:02 Trust is kind of a big deal
08:29 Today it's easy to build, but still not easy to get adoption
09:55 Tempted to skip testing? Don't.
12:16 Why human behavior matters more than product features
14:23 Understanding clinicians as users
18:09 Where AI creates hesitation and bad friction
20:09 Professional identity: "Am I the kind of person who uses this?"
21:14 The mTuitive cancer care case study
24:21 Challenging assumptions before building
26:18 How clinician research actually works
28:31 What clinicians really want from AI
30:44 Will resistance to AI fade over time?
32:31 Finding the balance between efficiency and safety
34:23 Why some friction is actually good
36:40 Are companies overestimating automation?
38:35 The skill every AI product leader still needs
40:05 How to build customer intimacy in the AI era
42:56 Ambient listening and the unintended consequences of AI
44:22 The food bank story: how fear shapes behavior
45:58 Slow down: AI's hidden human costs
46:55 Closing thoughts
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