Balance Scale/Bias Board
Overview
Completed through IUPUI, the objective of this project was to design a social computing system prototype that would in some way address an important challenge facing the world today.
Duration
8 Weeks, Final Project for Interaction Design Practice (IUPUI)
The Team
Ashish Durgude, MS/HCI Madison Anderson, MFA/VCD Heidi Bloesch, MS/HCI
My Role
I worked with my teammates to conduct research and explore and define the problem space. At my suggestion, we chose to focus on Facebook specifically.
Tools
Sketch, Invision
Discovery
Our Challenge
In the world today, we are constantly faced with misinformation and disinformation. To tackle such a complex issue, we focused on echo chambers and filter bubbles as root causes of the spread of misinformation.
Design Process
—Echo-chambers and filter bubbles often form on Facebook because the algorithms that underpin the platform reinforce user’s confirmation bias by continually recommending news and information that aligns with their past activity—
User Research
We chose to conduct user interviews to gain a first-hand understanding of how or if people use Facebook to consume news items.
Participants included a wide age range of regular Facebook users, from 20s to 60s.
In addition to being a Facebook user, one participant had a higher knowledge of misinformation.
Key Interview Insights
Problem Statement
How might we give Facebook users exposure to news and information outside of their personal echo chambers and filter bubbles?
As a Facebook user, I want to have a way to obtain news and information outside of my personal viewpoints.
Affinity Diagram
Ideation
From our affinity diagram, we were able to find our key requirements:
1.
Help the users to be more aware of their own biases.
2.
Help the user to become more exposed to news and information outside of his / her existing point of view
3.
Minimize confirmation bias, filter bubbles, and echo chambers for Facebook users
4.
Enable the user to engage in a more diverse Facebook news and information experience
Wireframes
How to evaluate our bias scale rating?
To maintain as neutral as possible, we adopted the Media Balance Scale rating system from allsides.com. All Sides generates a bias rating score for news outlets based on blind surveys of people across the political spectrum, multi-partisan analysis, editorial reviews, third-party data, and tens of thousands of user feedback ratings.
Final Visual Designs: Media Balance Scale
Final Visual Designs: Bias Board
User Testing
Product Evaluations
From our user evaluations: Overall, all of the users who evaluated the product felt that it was a unique and effective solution. The primary concerns were around the transparency and neutrality of the assigned ratings. Even with questions on transparency, the users felt that this tool could allow them a more informed and well-rounded opinion on political topics with friends and family they may disagree with politically. Lastly, they were skeptical about allowing Facebook to make a judgment call and determination about the political leanings as they do not view Facebook as a neutral party in the current political discourse. Looking ahead, it seems that being able to convince users to trust in the rating system would be the biggest barrier to product success.
From our expert evaluations: Every evaluator felt that our solution was well thought out and appropriate to address this complex problem. With that said, each of our expert evaluators raised questions about building trust and providing transparency with users. They felt that in order for the solution to be effective in the long term we would have to provide more information about the AllSides Rating methodology. They felt that users would be skeptical or resistant to trusting Facebook in providing bias ratings and that it would be very important to build user’s trust in AllSides and effectively communicate the non-partisan methodology used to generate the bias ratings.
Further feedback:
Bias Board tab was difficult to locate especially if you did not know it was there to begin with
The action to “balance your bias” could be emphasized or made more evident to the user
The rating scale could be emphasized in a way that makes it more easily detected
Not immediately clear how to navigate through the dashboard data
Challenges and Considerations
There is skepticism around Facebook as a neutral party in the current political discourse. A future challenge would be to gain user’s trust in the rating system.
Exposure to differing opinions does not guarantee a change of opinions or beliefs.