SKETCHBOOK
SKETCHBOOK
SKETCHBOOK
ADDRESSING WICKED PROBLEMS
DATA PRIVACY AND SECURITY WITH SMART HOME DEVICES
6 weeks | Human-Centered Design Project
PROBLEM
How might we improve transparency and privacy for smart home device applications for people who are hesitant to purchase new technology?
PROJECT OVERVIEW
With the rise of artificial intelligence, smart devices from Amazon Alexa to Google Home, and expectations for technological fluency, there’s a large stigma regarding data collection and the breaching of privacy. Applying the human-centered design process, quantitatively analyzing 50+ survey responses and qualitatively accessing 10+ individual and field expert interviews, conducting user and secondary research, our goal was to improve and understand transparency between technology and users. In doing so, we developed implementable solutions that strive to increase awareness about existing smart home device features regarding data security and privacy and UI redesigns to improve app clarity, organization and information flow for the user.
TOOLS
Figma
Otter.ai
Primary User Research
Secondary Research
Prototyping
Ideation
Field Expert Interviews
Miro
COLLABORATORS
Chelsea Tang
Shannon Lin
Anthony Pan
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PROJECT BREAKDOWN
"A balance exists between the potential in personalization and an intrusion of privacy. In an effort to create a more personalized and friendly experience, the individual must give more of their personal preferences to the unknown; whether this decision is offered upfront or hidden behind the UI, this is the paradox that generates uncertainty and skepticism within the public eye. Exploring what options are available to share, and how companies can optimize their utilization grants greater understanding in the benefits or ramifications of customization."
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Qualitative Measurements
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Audio recorded interviews: Transcribed into Otter.ai.
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Used language data visualizer to detect keywords and commonly reoccurring terms
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Located in a private and quiet space for clear video recording
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Recorded responses to interview questions to identify trends and synthesize insights
Quantative Measurements
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Google Form Survey: Initial form for participant feedback
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Identified whether participants use smart home devices based on demographics
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Asked surface level questions on data security/privacy
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Primary to Tertiary Stakeholder Map indicates relevant and affected parties
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The results of our language processing revealed that smart home device users state that they “know” (173) about the device, while non-users tend to assume, abundantly using words like “think” (103) when responding to questions. The main keywords sorted after data cleansing was information, use, tasks, data, and features.
Categorizing people’s skepticism about technology by age group, we discovered that people who are older tended to be more skeptical about smart home devices than college students, regardless of if they owned one themselves; these results corroborated our initial assumptions.
Drawing from 1 on 1 interviews with smart home device users and an expert interview with a current Amazon Alexa employee, we developed 4 primary insights.
(See graphic for primary research anecdotes)
Paradox (Personalization of experience vs. data collection)
Collecting information allows for further customization of smart home devices.
Lack of Privacy Concern
Young people don’t think they are saying important information that needs to be hidden.
Smart Home Device Usages
Smart Home Devices are primarily used for convenience. Most people are not familiar with the app and think it is counterproductive.
Transparency
People don’t know how their privacy is dealt in smart home devices. Information on data security and transparency exists, but it is difficult to find.
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User-Centered Solution 1:
Increase awareness about existing smart home device features regarding security.
Studying Amazon’s privacy and Alexa webpages, when onboarding, users can choose what they want Alexa to know, turn cameras off, tell Alexa their gender, and other personal information. At any time, users can turn on the mute button, and Alexa can’t hear them anymore; they can delete, view, or hear all voice recordings, and Alexa isn’t listening when the user doesn't say the wake word.
Current consumers are often unaware of these features. This could be improved by discussing privacy with the user during onboarding, illustrating these features on the Alexa homepage, incorporating a new section for privacy on the app, and integrating transparent interactions such as “Alexa, why did say that?“ into publicity videos. This would allow everyone to easily access, control, and understand what information Alexa collects
User-Centered Solution 2:
Redesigning UI to improve app clarity, organization, and information flow
Some changes we would like to suggest include:
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Minimizing overlap between what is displayed on the device and what is on the app; Repetition is unnecessary and confusing
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Making the interface less “clunky” and condensed, easy to understand
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Adding a specific page or ability for users to view the user profile Alexa has built on them
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Adding a specific UI page about company data usage and privacy
Language Interface
Another element we would hope to incorporate is increasing accessibility through improving the language processing interface. A common issue we heard during interviews was that Alexa doesn’t recognize people’s foreign accents. After contacting Elena, we learned that Amazon is working on this, specifically with a design conference discussing how Alexa doesn’t recognize black accents, hosted by the department on diversity and inclusion.
DESIGN DECISIONS
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Top 3 Design Principles Applied
Based on the book "The Universal Principles of Design" by William Lidwell
Assumptions & Weaknesses we determined in our research process and solution development