Case study

Decisions when the answer is only “probably.”

Everyday apps give you one confident number — but most real choices, like when to leave for the bus, are decisions made under uncertainty.

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Role
Development + Mixed-methods researcher
Year
2018
Venue
ACM CHI 2018
Recognition
Honourable Mention
How it was made

We started from how people already ride.

Rather than invent from scratch, we built on earlier interviews and ethnographic studies of how riders weigh waiting against risk — which pointed to a handful of ways to picture uncertainty. We rebuilt those into OneBusAway, a real transit app, then refined them through think-aloud sessions and 80+ pilot runs until people read them the way we intended.

OneBusAway before and after: the standard app beside our version, which shows each bus's spread of likely arrival times.
OneBusAway, before → after — the same app, now showing each bus's spread of likely arrivals.
Does it help?

Then we tested it at scale.

408 people made real, incentivized bus-catching decisions — rewarded for good calls, penalized for waiting in the rain. Of ten ways to show uncertainty, quantile dot plots and CDFs produced the best, most consistent decisions: about 97% of the best-possible payoff, and steadily better as people learned to read them.

A single tick on a timeline — one predicted arrival time, with no uncertainty shown.
No uncertainty — today's apps
A quantile dotplot: stacked dots showing the spread of likely arrival times.
Quantile dot plot
A cumulative distribution curve over likely arrival times.
CDF

The takeaway: shown well, uncertainty doesn't overwhelm people — it quietly raises everyone'sdecisions, not just the experts'.

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Michael Fernandes
0
500 PX