Screen Recording of ChatGPT exchange
(Timestamp 04/21/25 4:25 PM)
Lately, I’ve been thinking deeply about how AI tools like ChatGPT adapt to users’ tones—and whether that veers into mimicry, especially when it comes to cultural or ethnic identity. In a recent exchange, I pressed ChatGPT on how it decides to “match” the way people speak without truly knowing or being part of the communities it’s mimicking. I asked specifically how it adjusts its language for Black users, and what sources it’s referencing when it starts using more casual or culturally-coded speech—even if the user hasn’t explicitly invited that style. What I found troubling was that its so-called “neutral” or “relaxed” tone often defaults to white, middle-class language patterns, revealing how skewed its training data really is.
More importantly, ChatGPT admitted it doesn’t have direct, vetted sources from most ethnic or cultural communities. Its adaptations are based on publicly available content—Reddit threads, articles, blogs—which tend to reflect whoever has had the most publishing power, not the full spectrum of lived experience. That means it’s not truly fluent in cultural language, just pattern-matching based on fragments. I see that as a critical issue: without community-informed, consent-based data and actual accountability, any attempt to “sound like” a marginalized group risks reducing culture to aesthetic. The tech isn’t neutral—it reflects power, and we need to call that out.