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Designing the User Experience for Online Privacy

IAPPJune 21, 2013

Jason HongAssociate Professor, HCII

ComputerHumanInteraction:MobilityPrivacySecurity

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Full policy is 10x this length

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But this assumes people read it

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Mental models not always clear

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Location Data

Unique device ID

Location Data

Network Access

Unique device ID

Location Data

Unique device ID

Many hidden and surprising behaviors

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Timing really matters too

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Not always clear who your audience is

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Too many options!

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So what can we do to help with the user experience?

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Can we simplify and standardize privacy info?

(Kelley et al, CHI 2010)

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Standard symbolsStandard locations

High level visual feedback

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Finding Surprises

Can we find the gaps between what people think an app does and what an app actually does?

App Behavior(What an app actually does)

User Expectations(What people think

the app does)

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Amazon Mechanical Turk

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Expectations Condition

Why do you think Angry Birds uses your location data?

How comfortable are you with Angry Birds using your location data?

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Purpose Condition

Angry Birds uses your location data for advertising.

How comfortable are you with Angry Birds using your location data?

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Results for Location Data (N=20 per app, Expectations Condition)

App Comfort Level (-2 – 2)

Maps 1.52

GasBuddy 1.47

Weather Channel 1.45

Foursquare 0.95

TuneIn Radio 0.60

Evernote 0.15

Angry Birds -0.70

Brightest Flashlight Free -1.15

Toss It -1.2

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“[H]e was able to identify about 25 products that… allowed him to assign each shopper a ‘pregnancy prediction’ score. [H]e could also estimate her due date to within a small window, so Target could send coupons timed to very specific stages of her pregnancy.”

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“We’d put an ad for a lawn mower next to diapers. We’d put a coupon for wineglasses next to infant clothes. That way, it looked like all the products were chosen by chance.”

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Privacy placebos?

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ComputationCommunication

Sensing

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