Using machine learning to flag gender biased words within free-form text, such as job descriptions

Abstract

Under one aspect, first user input including free-form text is received in a first graphical user interface (GUI). A classification engine of the computer system incorporating a machine learning model classifies words of the free-form text into a male-biased class, a female-biased class, or a neutral class. At least one of the words is classified into the male-biased class or the female-biased class. At least one of the words classified into the male-biased class or the female-biased class is flagged in the first GUI. Second user input is received in the first GUI including at least one revision to at least one of the words of the free-form text classified into the male-biased class or the female-biased class responsive to the flagging. The revised free-form text is posted to a web site for display in a second GUI.