ProText: Unmasking Gender Bias in AI's Writing

Gender bias in AI writing isn't just a bug. It's a feature, baked in from data to deployment. Enter ProText, a dataset crafted to measure how AI models gender or misgender subjects in long-form English texts. This isn't your standard pronoun resolution test. ProText digs deep into the muck of stereotypes and assumptions.

What ProText Reveals

ProText's data spans three dimensions: theme nouns like occupations and titles, theme categories such as gender stereotypes, and pronoun categories covering the spectrum from masculine to gender-neutral. It's designed to expose the cracks in AI model behavior, especially during text transformations like summarization and rewrites.

The dataset has already unmasked systematic gender bias. Particularly glaring is how AI models tend to default to heteronormative assumptions when gender cues are absent. A mini case study using just two prompts and two models was enough to highlight these biases.

Why This Matters

Why should we care? Because AI models are shaping the narratives we consume. They're writing essays, news articles, and even poetry. If they're distorting gender representation, they're reinforcing stereotypes on a massive scale. AI developers need to know this. They need to address it head-on.

Think about it: If a model can't handle gender without defaulting to stereotypes, is it really ready to write the next bestseller or informative article? The game comes first. The economy comes second. If nobody would read it without the algorithm, the algorithm won't save it.

Time for a Reality Check

ProText isn't just a dataset. It's a wake-up call. AI's bias isn't an abstract problem. It's here, and it's loud. How many more ProTexts need to be built before the industry takes meaningful action?

AI needs to be better. Period. Models should serve all of us, not just the outdated norms they were trained on. As more tools like ProText emerge, the industry can't ignore the issue any longer. Retention curves don't lie. AI's credibility depends on it.