Netflix used AI to enhance the image quality of an 80s sitcom. The result is not what was expected

Netflix has recently faced some backlash for its attempt to remaster the 80s sitcom “A Different World” using AI. While the goal was to improve the visual quality of the series, the results have sparked widespread criticism. Viewers have noticed significant distortions, particularly in text elements and background details, raising concerns about the limitations of AI upscaling in classic media restoration.

AI upscaling leads to blurry details and distorted texts

The show, a spin-off of The Cosby Show, was recently added to Netflix’s U.S. catalog in high definition, but it did not take long for audiences to realize that something was off. Instead of a clean and natural enhancement, the AI-generated upscaling has resulted in an overly smooth and blurred image. Characters and backgrounds appear artificial, and important details seem to have been lost in the process.

One of the biggest issues reported by viewers is the handling of on-screen texts and signs, which have become unreadable and distorted. AI upscaling struggles with these elements because it does not recognize words as meaningful content but rather as abstract shapes. This has led to bizarre, indecipherable text appearing throughout the series, making certain scenes confusing and difficult to follow.

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Tech blogger Scott Hanselman pointed out that the AI’s inability to properly process text has resulted in incomprehensible “hieroglyphics” on-screen, making the viewing experience frustrating for longtime fans of the show. Many argue that a simple re-release in its original lower resolution would have been preferable to this flawed enhancement attempt.

As AI tools continue to be integrated into media restoration, this case raises questions about the effectiveness of AI upscaling and whether it is a suitable solution for improving classic TV shows. While AI has its place in digital restoration, the controversy surrounding A Different World suggests that it may not always be the right approach.