The Problem with Privacy in IoT

DinoTank is an internal pitch platform in order to innovate and solve current issues that are relevant to Mozilla’s mission. DinoTank 2016, came with a twist — instead of pitching ideas we focused on pitching problem statements.

To give each DinoTank winner the best possible start, we set up a design sprint for each one. This is the first installment of that series of DinoTank sprints…

The Problem

I work on the Internet of Things at Mozilla but I am apprehensive about bringing most smart home products into my house. I don’t want a microphone that is always listening to me. I don’t want an internet connected camera that could be used to spy on me. I don’t want my thermostat, door locks, and light bulbs all collecting unknown amounts of information about my daily behavior. Suffice it to say that I have a vague sense of dread about all the new types of data being collected and transmitted from inside my home. So I pitched this problem to the judges at DinoTank. It turns out they saw this problem as important and relevant to Mozilla’s mission. And so to explore further, we ran a 5 day product design sprint with the help of several field experts.

Brainstorming

A team of 8 staff members was gathered in San Francisco for a week of problem refinement, insight gathering, brainstorming, prototyping, and user testing. Among us we had experts in Design Thinking, user research, marketing, business development, engineering, product, user experience, and design. The diversity of skillsets and backgrounds allowed us to approach the problem from multiple different angles, and through our discussion several important questions arose which we would seek to answer by building prototypes and putting them in front of potential consumers.

The Solution

After 3 days of exploring the problem, brainstorming ideas and then them narrowing down, we settled on a single product solution. It would be a small physical device that plugs into the home’s router to monitor the network activity of local smart devices. It would have a control panel that could be accessed from a web browser. It would allow the user to keep up to date through periodic status emails, and only in critical situations would it notify the user’s phone with needed actions. We mocked up an end-to-end experience using clickable and paper prototypes, and put it in front of privacy aware IoT home owners.

What We Learned

Surprisingly, our test users saw the product as more of an all inclusive internet security system rather than a IoT only solution. One of our solutions focused more on ‘data protection’ and here we clearly learned that there is a sense of resignation towards large data collection, with comments like “Google already has all my data anyway.”

Of the positive learnings, the mobile notifications really resonated with users. And interestingly — though not surprisingly — people became much more interested in the privacy aspects of our mock-ups when their children were involved in the conversation.

Next Steps

The big question we were left with was: is this a latent but growing problem, or was this never a problem at all? To answer this, we will tweak our prototypes to test different market positioning of the product as well as explore potential audiences that have a larger interest in data privacy.

My Reflections

Now, if I had done this project without DinoTank’s help, I probably would have started by grabbing a Raspberry Pi and writing some code. But instead I learned how to take a step back and start by focusing on people. Here I learned about evaluating a user problem, sussing out a potential solution, and testing its usefulness in front of users. And so regardless of what direction we now take, we didn’t waste any time because we learned about a problem and the people whom we could reach.

If you’re looking for more details about my design sprint you can find the full results in our report. If you would like to learn more about the other DinoTank design sprints, check out the tumblr. And if you are interested in learning more about the methodologies we are using, check out our Open Innovation Toolkit.

People I’d like to thank:

Katharina Borchert, Bertrand Neveux, Christopher Arnold, Susan Chen, Liz Hunt, Francis Djabri, David Bialer, Kunal Agarwal, Fabrice Desré, Annelise Shonnard, Janis Greenspan, Jeremy Merle and Rina Jensen.