Biasly
Artificial intelligence (AI) to detect and correct misogynistic language.
About the Project
Biasly is an AI research project leveraging cutting edge natural language processing algorithms to identify and correct misogynistic language in written text, whether such text is expressed overtly or covertly.
Biasly is being developed to explain why language can be interpreted as misogynistic and suggest ways of rephrasing to reduce or remove the misogynistic implications.
How it Started
Biasly was originally devised by Andrea Jang, Carolyne Pelletier, Ines Moreno and Yasmeen Hitti during their summer training at the AI4Good Lab. Their goal was to build a machine learning tool capable of detecting and correcting gender bias in written text. To bring their idea to fruition, the team decided to undertake a Humanitarian AI Internship with Mila, where they developed a taxonomy for gender bias in text. Although their internship has since ended, Mila’s team of researchers has continued to pursue this work to fulfill Biasly’s vision.
Taking Biasly to a New Level
Biasly’s current team has been strategically assembled to ensure the responsible and high impact delivery of this work.
Our ML researchers are Anna Richter* (MSc in Cognitive Science) and Brooklyn Sheppard* (MSc in Speech and Language Processing).
The project is being managed by Senior Projects Manager, Allison Cohen, in collaboration with experts from the field; including Linguistics expert, Dr. Elizabeth Smith; Gender Studies specialist, Dr. Tamara Kneese; Natural Language Processing Advisor, Dr. Yue Dong and Language Processing Engineer, Carolyne Pelletier.
The project has also been fortunate to have had the insight and expertise of AI Researcher, Dr. Ioana Baldini and Gender Studies Expert, Dr. Alex Ketchum.
What’s Next
The Biasly team expects to release the dataset and code open source in 2024. The team's publications have been submitted to AI conference venues and will be made publicly available once the conference venues' decisions have been finalized.
Meet the Team
Mila Members
Collaborators
Dr. Yue Dong (University of California, Riverside)
Dr. Tamara Kneese (University of California, Berkeley)
Carolyne Pelletier (Mantium)
Dr. Elizabeth Smith (UQÀM)
*Dr. Ioana Baldini (former collaborator, IBM Research)
*Dr. Alexandra Ketchum (former collaborator, McGill University))
*Anna Richter (former collaborator, Mila)
*Brooklyn Sheppard (former collaborator, Mila)
News
Partners
This project has benefited from the generous support of DRW.
