With the AI models being trained using Reddit data, do you think by now someone somewhere would have gotten shittymorph’ed?

Exploring the Impact of Reddit Data on AI Language Models: Have We Seen the Worst Yet?

In recent discussions about artificial intelligence, an intriguing question has emerged: given that many AI models are trained on data sourced from Reddit, is it possible that some have been exposed to, or even influenced by, more chaotic or offensive content? Specifically, could instances of models generating undesirable or inappropriate outputs—sometimes referred to colloquially as “shittymorphing”—be happening behind the scenes?

Motivated by this curiosity, I conducted an informal test using the AI model Gemini. I prompted it to respond in a “shittymorph” style, expecting to see the model’s reaction when asked to adopt a heavily stylized, rough-around-the-edges tone. The results were surprisingly revealing, affirming that the model indeed demonstrated some awareness of the style, if not the full extent of its own creative boundaries.

This exploration raises a broader question: by delving into the more obscure corners of Reddit’s lore and discussions, can we better understand the scope of what these models have learned? Are there hidden layers of knowledge or biases that surface when models are pushed into unconventional styles?

These inquiries highlight the importance of ongoing research into AI training data, especially as models become increasingly sophisticated and integrated into diverse applications. As we continue to examine how data influences behavior, exploring niche online communities may shed light on the boundaries—and potential risks—of AI language generation.

Do you have ideas on how to further investigate the depths of what these models know? Sharing insights or experimental approaches could contribute significantly to this evolving field.