Alexa, do men talk too much?

Description

Numerous studies have shown that men consistently interrupt women in professional and nonprofessional settings. There’s also a tendency to provide remedial explanations to concepts that are already well known to the target audience. A new word, mansplaining, was added to the Merriam-Webster dictionary that captures this social problem. At its core, mansplaining is when a man talks condescendingly to someone (especially a woman) about something he has incomplete knowledge of with the mistaken assumption that he knows more about it than the person he’s talking to does.

This phenomenon impacts women in all professions at all levels of their career. Any form of privileged explaining can cause women to be uncomfortable in their own careers and can keep women from entering male-dominated fields such as STEM. For women already in these fields, being talked over in a professional setting like a meeting isn’t just frustrating but could be career limiting.

Sireesha Muppala, Shelbee Eigenbrode, and Emily Webber explore this in two ways. First, they build an artificial intelligence- (AI) and machine learning- (ML) based solution that explores the prevalence of mansplaining in professional settings. Then they explore strategies that can be employed to addresses the issue at hand. The goal is to demonstrate the feasibility of using the combination of technology and human actions to raise awareness about and address prevalent issues that have a direct impact on women in technology.

For the technical solution, they used the Kaggle Gender Recognition by Voice dataset. ML, using algorithms that continuously assess and learn from data, enables building automated analytical models that provide insights into hidden patterns in the data. AI-based natural language processing (NLP) and automatic speech recognition (ASR) provides the ability to access these insights in a conversational manner.

The combination of ML and AI were used to build an Alexa skill that can be used to explore questions such as whether or not men talk more than women in meetings, how many women speak up in meetings versus men, and what percentage of women participate in a meeting. The technical solution helps in identifying and raising awareness of the issue, but doesn’t solve the problem of gender identity and equality in professional settings.

Sireesha, Shelbee, and Emily explore strategies for women such as owning the responsibility to have their voices heard by speaking up, asking questions, being an ally to other women, and ensuring young girls and women in technology are getting mentors. They also provide strategies for men, such as being empathetic and realizing that the problem is real and taking feedback from the female colleagues about the issue in order to be more self aware during interactions.

This is crucial now. The number of women in technology is on a downward trend. Just in the field of computer science, in 1984 women held 37% of degrees. Today that number is down to 19%. Even when women do choose STEM careers, only 26% work in technical roles, compared to 40% of men. In technology, women leave the industry at a rate 45% higher than their male peers. Addressing gender identity and gender equality issues at workplaces is a crucial step to reverse the trend.