In this episode we get to talk with Nishant Bhajaria, author of Privacy by Design and leader of data privacy teams at Google, Uber, Netflix and Nike about designing and developing ways to protect your users and their data.

• Privacy by Design available on Manning Publications

• 35% off code: podaizen21

• Nishant Bhajaria on LinkedIn

• IBM Trust Center for security and privacy

We all have implicit biases and assumptions that come into play whenever we're designing and building shtuff. Jen and Andrew share the sad, the horrifying and the sometimes amusing stories of what happens when we don't ask what we don't know and just keep on going without identifying our blindspots.

• Jen's Medium article on what the heck is Kubernetes >

*Jen and Andrew would like to make a boulder sized apology to Sisyphus for mistaking him for Atlas.

Andrew and Jen bounce ideas around with futurist Clayton Bunyard, Ph.D., about biological design thinking, weird skills we'll need in the future, STEM vs STEAM, and how video conferencing tools are going to get much, much better.

• The Future of Organizational Creativity by Clayton Bunyard, Ph,D.

• Microsoft Holoporter

• PeTal

• Magic Leap

• University of Houston, Master of Science in Foresight

Andrew asks Jen about her methods for helping teams vet and prioritize all the ways AI could be designed into their products.

Jen and Andrew get into the inner workings of a few simple AI applications and exactly HOW those magic-like experiences are built.

AI has done so many good things for us already. For Thanksgiving, Andrew and Jen reflect on how AI is improving our lives, our world, and our futures.

1. Examples of AI making our life better - 01:12

• Saving us time - 01:56

• Saving the world - 03:50

2. Things AI has made us more aware of - 07:50

• Bias - 08:17

• Diversity - 10:33

• Behavorial Change - 12:35

• Designing for Ethical AI - 13:33

• Accessibility - 16:00

3. Opportunities AI gives us for the future - 18:03

• Fun new problems to solve - 18:20

• Democratizing AI - 21:12

• Cool new jobs already here - 22:13

Three tales of AI nightmares and apocalyptic robots

Andrew and Jen go to the dark places of our possible horrific futures with AI, discuss what it would take for them to become reality, and decide how scared you should really be before you go to bed tonight…

Story 1: The Skynet Singularity of Doom (1:00)

Story 2: Giving up Control (18:15)

Story 3: They Took Our Jobs! (24:15)

Keith Vertrees, Director of User Research with a background in data science, talks data driven design, the data skills designers need, the business skills data scientists need, why we should spend 90% of our time identifying the problem, how data and design should function together, and Jen has the Earth shattering realization that Andrew is a data scientist, not an AI scientist.

0:30 - Intro to user research

2:00 - What a user does vs what they want

6:20 - Being data driven

8:45 - Adapting user research for AI

11:25 - Data aware vs data informed vs data driven

18:00 - A real life example of user research saving the day

23:45 - Skills we need to support data projects

References

• Keith Vertrees, Director of User Research for IBM Cloud

• Designing with Data: Improving the User Experience with A/B Testing

• How to Win Friends & Influence People

What's going happen as data and design teams work closer and closer together to continuously deliver AI? Will roles overlap? Will skills transfer? Do we need to get aligned on our meme references now or are we already meme compatible?

00:30 Roles on data science and design teams

14:00 The value of kicking off with a face-to-face workshop

23:00 Could designers help with model maintainence?

Why can’t I just launch my AI widget and be done? Andrew tells us about what to expect and plan for once you've set your AI free and talks through a hypothetical chatbot where new questions about GDPR came from users after the initial chatbot was deployed.

Did you know you can design your AI system to tell you how it needs to be fixed? In episode three we talk about some real world examples of false/positives, true/negatives and all the things to confuse your brain matrix. Plus, cool ways to get feedback from your users to improve your system!