Safely: A Design Sprint Case Study
Overview
Immersion Studio is the University of Washington MHCID program’s orientation-by-fire. A week long rapid sprint from prompt to presentation. The cohort was split into teams half way through the first day and were off to the races. The activities were sequentially setup to have the class identify and narrow down problem spaces, prompted with promoting civic engagement by means of Computer-Supported Cooperative Work (CSCW).
Our Team:
Defining the Problem
The whole class laid out ideas for potential problems. Our team gravitated towards the topic of personal safety. We chose to focus our problem space on our immediate area, the University District of Seattle. Initial research, a few anecdotal experiences shared in class, and a particularly troubling potential shooter false alarm on our second day proved that this was a true problem space. People tend to move to the area from all over the country and the world to attend the University of Washington but are ill-equipped to navigate Seattle’s University District, with its ever present homeless crisis and high crime rates. After some deliberation on the topic and how to utilize CSCW, we settled on the problem statement:
“How might we utilize crowd-sourced information from University District residents to elevate perceived public safety?”
Our Response
Safely is an app that utilizes crowd sources information about safe areas to map safer walking route options to a destination.
Benefits
How It Works
The way it works is simple, users can map to a destination and the app will show them alternative safe routes based on rated “safe zones” from other users. The app would create the shortest path to the destination, touching as many safe zones as possible along the way.
Safe zones are rated based on 4 categories: Clean, Bright, Lively and Familiar. Users will be prompted to add or update their rating of a safe zone as they walk through it, or they can do so at their own leisure. The average rating will then be applied to the safezone. The app would check in with the user at each safezone, to make sure they were still okay. If not, the app would then quickly reroute them to the next shortest safe route. If the user feels in any immediate danger, the app has a panic button to map to the nearest safe zone or call 911.
We felt that this was a simple, yet effective, use of CSCW.
Now, Lets talk a bit about how we got here.
Literature Review
Initial literature review revealed some validating facts and statistics:
In Seattle, both violent and property crimes rose to an average of 10% from 2017 to 2018, most often thefts, armed robberies and assaults.
“Hotspots” are locations with a higher percentage of offenders and victims; characterized by its high population of eateries, pubs, shops, markets and retail. University District falls into this definition.
Information contributed by University District residents on forums like Reddit. People are already sharing their experiences and give warnings to other users.
Interviews and Insights
We narrowed our target demographic to students, aged 19–30 based on the assumption that students are most unfamiliar with the area. We interviewed four female and one male student formed three main insights:
- People’s assessment of public safety is based on personal experience and unconscious bias. The students that had been around the area longer knew more about the best routes and times of day to walk around, hence they felt less afraid than the students that had moved to the University District more recently, who were dealing with the University District’s safety issues for the first time.
- Feeling unsafe walking around seems to be a predominantly female issue. The concern for personal safety seemed to be deep rooted in the female interviewees but not so much in the male. We inferred that men worry about personal safety as it pertains to crime less than women.
- Residents notion of personal safety directly correlates with fear of crime. Any time we mentioned safety, the interviewee seemed to associate that word with crime, not natural disasters or anything else. The University District has a sizable homeless population and a notorious reputation for crime.
We used these insights to narrow our focus to the perception of personal safety as it relates to fear of crime, target women users and that utilizing the wisdom of people who had lived in the University District for longer would allow the newer residents to gain a similar level of perceived safety.
Concepts
Our team formulated some ideas, based on the insights, through a braiding session. Our team many ideas for how we might approach the problem and presented them for critique, narrowing them down to 3 concepts.
The feedback we received during the critique was largely focused on the apps consideration of privacy and validation. Privacy of both of the traveller and the people in the community and validation of the information the app was providing. The feedback helped us form our down selection criteria:
✱ The app should aim to improve perceived safety.
✱ Utilize the wisdom of the community without invading privacy.
✱ The system should be based in a familiar app experience.
These three criteria pointed us to merging two ideas that addressed people’s interest in using well-travelled walking routes that are marked through a feedback-loop from other travellers.
Paper Prototype
We adapted our inital flow into a set of paper prototypes based on having users mark safezones and travel through previously marked safezones.
We conducted some usability testing with classmates and roommates. The notes we received can be summed up in two categories:
Methods
The paper prototype was quick to assemble but did not provide much clarity. We were told that the icons did not read well and they wanted more options for routes that we had not created paper prototypes for.
Context
The most glaring issue was that the user did not know how to trust the safezones if there were no metrics for what constituted “safety”. We realized that we would need to create a whole system for validating safety, even if it was in a low fidelity prototype.
Final Concept
Key Takeaways
People might need incentives to share any kind of data, even in the case of public good.
People have different thresholds of their “perceived safety” and in using this system they could adjust their preferred safe zones based on the criteria that matters to them.
“Safe” is a more concrete concept than “unsafe”.
Restructuring our framework to focus on safety attributes of locations rather than stereotyping “dangerous” people in the community.
Reflections
This week was challenging and very exciting so it is hard to sum up the lessons but I can think of three things that stood out:
✱ Consider accessibiltity.
One of the assumptions we made early on, and believed we had validated with research, was that the feeling of being unsafe when walking alone was predominantly female. Through the process of presenting, we were challenged about our idea to design for “females” rather than “women”, “femme”, or just all people. While we did not reach a consensus on who was most impacted by the problem space, we were able to rethink our process of narrowing our user population.
✱ Good design considers the unseen stakeholder.
Another interesting piece of feedback we received was around our criteria of “safe zones”: Clean, Bright, Lively and Familiar.These criteria could be used to avoid poorer neighborhoods and reduce foot traffic to local businesses there. Initially, I believed that you cannot consider every possible person that could tangentially be affected by your designed product. However, with more time to discuss and learn in this graduate program, I realize that bringing something new into the world comes with many responsibilities on the designer to consider the far reaching implications of their design.
✱ The design process is not absolute.
While this was not the first time I had engaged with the design process, it was different than what i had experienced before. Not only that, but the more I read about it, the more i realized that people change and adapt it, using methods and exercises that best suit their design space. I was initially worried that I would do something “wrong”, but I realize now that there is no “wrong” in design, there is only the clarity with which you tell the story of your process at the end.
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