![[OLD SEMESTER] 15-104 • Introduction to Computing for Creative Practice](https://courses.ideate.cmu.edu/15-104/f2022/wp-content/uploads/2023/09/stop-banner.png)
Theodore Kim addresses racial bias in computer graphics and poses solutions to prevent systemic bias. Kim claims that early film technology and procedures from the analog period have biases ingrained in them. For example, “subsurface light transport” is a component of digital design that allows for a skin glow effect, but this doesn’t apply to darker skin tones. This same algorithm can look unrealistic on people with darker skin tones. In addition, there are no algorithms for kinky hair. The use of deep machine learning can offset historical racial bias in computer graphics. He further proposes that this process enables artists to discard outdated rules and produce a futuristic aesthetic for digital media.
Alexia Forsyth
