SPOT is a deepfake detection and educational application that allows users to learn about deepfake technology and upload their own content to detect the validity of media. SPOT app works in connection with the Facebook platform to run in the background and flag users if deepfake technology is detected within a post. As deepfake technology is continuously advancing the application features modules that allow users to educate themselves on some of the tell tale signs of how to spot a deepfake. The application uses an algorithm to track the eye movement within media to determine the validity of the content. The SPOT app is a multi-disciplinary project developed by 5 students from a variety of backgrounds. The team is comprised of 1 film major, 1 communications major, 2 math majors and myself a design major. Our project is based on the research question “How can we differentiate real videos from DeepFakes videos?” which we have used to structure and develop our project concept. Over the past 8 months we have worked to build concepts, conduct research, and develop application material and our algorithm. 

After conducting preliminary research we developed a project statement to articulate what exactly we wish to accomplish. From our found information we created a list of requirements which would distinguish what our application needed to do and why. 

Our team began our project by conducting research through an online survey. Through our survey we were able to determine the needs of our users and to validate our problem.

Once our goals and requirements were set we created a series of use cases and scenarios. This step would help us to distinguish a flow within our app and determine scenarios that we would use to guide our users through the testing process. 

We compiled all of our use cases into a System map which visually displayed the relationship and between pages on our application. 

Besides developing the prototype and conducting research, I created the branding and style for the application. The branding development allowed me to fully embrace my creativity and create an aesthetic that is friendly and allows users to feel less intimidated by deepfake technology. I was inspired by sci-fi media and gave the application a vibrant colour scheme that is interesting and eye catching. Spot the robot, was created to be the face of the application. Spot is the physical body of the detection algorithm and works very hard to “spot” false media! Spot was created to give the application a personality and helps users to feel more connected and interested in interacting with the app. 

Our math experts took on the challenge of developing an algorithm to enhance our app concept. The algorithm uses eye tracking technology to determine the validity of an online video. This technology was created to be used through our scanning feature which allows the user to scan videos through their phone camera to determine if the video is real or fake.

This project was a huge responsibility and as the sole designer I held alot of weight on my shoulders. As someone who has never developed an app individually before I struggled to grasp the platforms and my interfaces were a bit messy. Without having many other designers in the course to critique or assist me in this process I felt very alone and unsure for the majority of the project development. However, through the support of my group members and the willingness to escape my comfort zone, I was able to take my own direction to this project and fully embrace my skills while continuing to learn and grow as a designer.