Yesterday, me (Pranav Vadrevu) and Tejesh from product team attended the Data Awareness Design Jam conducted by TTC labs of Facebook(https://www.ttclabs.net). It was like a hackathon, but for designers. Given my non-designer background, I was curious and a bit nervous to see how I would play into this Design Jam. There were 6 startups at this event, and our goal was to create a prototype for any of the challenges that the startups were facing. Additionally, the event was focused on the issue of data privacy and how companies should effectively communicate to the users what their data is being used for and how it will be kept secure. This is a growingly relevant concern, especially since the news has been recently filled with many controversies like The Facebook–Cambridge Analytica data scandal.
Before “jamming”, we spent the first half of the day on exercises about data privacy and collection from a user’s perspective.
Analyzing data-transparency in-context
The first activity was categorizing different app features in three ways. There are three ways of displaying features: Upfront, in-context, on-demand. Upfront features are shown before the user signs up for an application. For example, terms and conditions are shown before signing up. In-Context features are shown after sign-up. For example, the music service in Ola cabs is shown after you get on the cab. On-Demand features are features that not everyone needs, so the user needs to find it in the application.
Here, we had to classify each feature as Upfront, In-Context or On-Demand. This activity sparked small debates regarding some features like accident detection system for travel apps. Some people suggested that it should be an upfront feature since people need to know before signing up whether data is being collected for accident detection. Others said that it shouldn’t be upfront since people might not care about it.
Design with Words
Our next activity was to reword terms and conditions by replacing technical jargon with simple english. Here, we had to explain terms and conditions to users like they’re five. It was fun to cut through all the complicated sentences and just write the gist of the terms and conditions.
AI explainability spectrum
Personally, the AI explainability spectrum exercise was the biggest hit. Here, we went through different apps like Apple Music, Netflix, Google Maps and Facebook to evaluate to what extent it was easy for a user to understand what type of data was being collected from them and how it was being used. There were interesting discussions, some steered into small arguments about where each app fell in the explainability spectrum. The main takeaway was to understand how we can effectively communicate with users regarding the purpose of data collection and the benefits they avail.
After the brain-sharpening exercises, it was time for the jam. There were 6 startups (and 3-4 representatives from each startup). The participants were slotted into different startups teams. As a team, we needed to identify a challenge for the team we were part of.
I was part of the InnerHour startup team. InnerHour’s product is an app of the same name. What is it? A personalized self-therapy assistant. In the app, the user chooses what course to enroll in. Some of the available courses include “Battling Depression” and “Tackling Anxiety”. After selecting a course, the user fills in a questionnaire. Based on that, the app creates a personalized plan for the user to help them overcome their problem.
The app uses a dashboard to layout its plan and show the progress of the user throughout their course. The challenge with the dashboard was information overload. There was too much thrown on the screen, which can overwhelm the user. Additionally, it wasn’t clear what user information the app was using to make the plan.
The event organizers wanted us to sketch ideas for the solution based on the challenge defined for each startup.
We got to sketch out possible designs of the interface of the dashboard. Each of us in the team diverged and recreated the dashboard by throwing together paper, pen, pencils and sharpies. We explained each of our designs and we selected the best elements from the designs and created the final paper sketch. Below are paper sketches from 2 startup teams (FTCash and InnerHour).
Finally, it was time to create our mockup design and present it. Our team split up so that half were handling on the presentation and the other half were creating the prototype. I was helping shape the layout, structure and text of the presentation. We got together the mockup design and presentation together and presented it.
At the end of each presentation, the event organizers held some time for QnA and critique where moderators and members of the audience asked questions about the solution proposed by the startups.
This event was an invaluable experience in that I was exposed to startups and challenges that they face. The “Design Jam” also helped me come out of my comfort levels and collaborate with designers on designing possible user interfaces for the dashboard for startups. The exercises also widened my horizon as I worked with different people’s perspective towards the same issue. I would definitely love to attend another design jam and learn more about UI/UX design from expert designers.
AI in Manufacturing: Drastically Boosting Quality Control Imagine the factory floors are active with precision… Read More
Did you know the smart factory market is expected to grow significantly over the next… Read More
Effective inventory management is more crucial than ever in today's fast-paced business environment. It directly… Read More
Gramener - A Straive Company has secured a spot in Analytics India Magazine’s (AIM) Challengers… Read More
Recently, we won the Nasscom AI Gamechangers Award for Responsible AI, especially for our Fish… Read More
Supply chain disruptions can arise from various sources, such as extreme weather events, geopolitical tensions,… Read More
This website uses cookies.
Leave a Comment