In the modern world we live in, the decision-making process is predominantly influenced by what we see and hear from news sources. However, very often, those decisions can be misguided by suspects or even intentionally misleading sources.
InstaFact, a system that recognizes and analyzes news sources and let people know if what they are listening to or watching is truthful or not by scouring all available sources on the internet to determine the validity of the source.
Since there is no such thing as completely true or false, the system uses color codes along with a percentage scale to let people know the relative validity of the source: Red = 00% - 49% truth = FAKE | Yellow = 50% - 89% truth = BIASED | Green = 90% - 100% truth = FACT.
Once people are no longer being manipulated by false information, a truthful social impact is formed where decisions are being made based solely on facts, which Impart knowledge and ultimately creates a better society.
After reading and watching much of the news involving the Impeachment of the Brazilian President, as well as the complication surrounding the United States Presidential election in 2016, I developed an App concept based on an article from the BBC titled: "How will history look back on Rousseff's impeachment?"
History Map 1
After reading the article, I created a chronologic map story to visualize all the elements (characters) of the story.
I conducted five user interviews and I thought I had all the elements lined up until one of the users shited the focus in a different direction by answering one of the questions unexpectedly:
Question - Who would you fault for the current Brazilian political situation, corrupt politics or the lack of education?
Answer - The MEDIA, I fault the media for the pervasive spreading of fake or, at the very least, biased news.
History Map 2
Then I realized my list of characters was missing the most important player: THE MEDIA. The chronological map was then readjusted to include this new player.
Prototype - Animatic
I created an animatic sketch prototype to enables the user to visualize the experience.
Check the video below to see the results.
Low Fidelity Prototype - UI | IxD
I then started developing the low fidelity prototype to test and collect the first insights. To assure interactivity, I inserted buttons where people could interact with the app by sending their opinions related to the news; sad face meaning not a reliable source, smirk face for a biased source or happy face for a reliable news source.
Mid Fidelity Prototype - UI | IxD
After collecting insights from the first prototype test, I created the mid-fidelity prototype. The call to action buttons were then changed to make the interaction more clear to the user. Instead of simply enlisting emoji faces, this version presented buttons with the words: Review, Stop, and Nice, where the user could click any of them to send their opinions about the current news. Also, to entice younger participants, I added a MEME-MAKER, with pre-selected images and fun texts with a stamp of truthful percentage (as seen in the third image from left).
Mid Fidelity Prototype - UI | IxD
After analyzing and synthesizing all insights collected from the low and mid-fidelity prototype tests, I was then ready to finalize the High Fidelity prototype.
Click here to interact with the prototype: https://invis.io/JAETWV335
Hight Fidelity Prototype - UI | IxD
Mid Fidelity Prototype - Wearable - UI | IxD
Since the concept of this app seemed to work well with a wearable watch, I also designed a Low-Fidelity prototype, so I could test the theory.
High Fidelity Prototype - Wearable - UI | IxD
From the successful results obtained from the Mid Fidelity wearable prototype, I then developed the wearable High Fidelity prototype.
Explanation Video - UI | IxD
Check the video below for a full explanation of how the system works.