This artificial intelligence model seeks to reduce the gender gap in Wikipedia

An artificial intelligence algorithm developed by a Meta researcher will try to reduce the gender gap in Wikipedia articles. AI expert Angela Fan created a model capable of generating biographies of women based on information from the web and writing them in the encyclopedia format.
Of all the biographies found in the encyclopedia, barely a fifth corresponds to women. A Wikimedia report revealed that 15% of editors are women, and white men from Europe and North America make up the majority of Wikimedians.
This is important, as it influences the publication of biographies and other Wikipedia articles.
How do you write a Wikipedia biography using artificial intelligence?

WikiSum process for creating a Wikipedia biography. Image: Goal

The information is obtained from the content present in the first 10 Google results. According to the researcher, the generation of the text by section uses a caching mechanism similar to Transformer-XL, a machine learning model that allows the understanding of natural language beyond a fixed-length context.
The model is not the definitive solution to reduce the gender gap, since it has its limitations. According to Fan, when evaluating its performance, they found that 68 percent of the text generated in the biography was not found in the reference text.
Example of a biography created with WikiSum. The text in orange is a "hallucination" and cannot be verified. Image: Goal.
After reviewing the content, they discovered that many sentences were partially verifiable, while others — considered "hallucinations" — cannot be fully verified.
Something worth mentioning is that the algorithm is not only dealing with a lack of representation, but also the absence of content about important women on the web. According to the researcher, the current articles do not have enough information, or prioritize her personal life before her achievements.
If this pattern is not changed when writing the original article, the algorithm will learn and replicate this bad practice.

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