Assessing African American Women Engineers’ Workplace Sentiment within the AI Field

Abstract

Artificial intelligence (AI) has infiltrated every industry and every aspect of our society. Business leaders have seen the shift AI has created and they are reacting swiftly to stay competitive. They are investing heavily in AI and hiring engineers and other technical professionals to capitalize on AI-based innovations.
 Engineers are problem solvers, innovators, and at the forefront of AI technologies; their daily jobs require the consumption of an enormous amount of information to solve problems, enhance existing products, or create new products. Engineering positions require extensive interaction with peers, experts, and other experienced engineers in a male-dominated field. Male dominance causes many women engineers to experience more biases and challenges than their male colleagues, especially minority women engineers. As AI infiltrates our society, will the challenges faced by minority women engineers subside or increase and will they participate in and drive innovations using AI?
 The purpose of this research paper is to assess the workplace sentiment of African American women engineers in the AI field. To assess African American women engineers’ workplace experiences within the AI field, machine learning text analysis was conducted on data extracted from Twitter. The practical implications of this research highlight African American women engineers’ perspectives and experiences, encourages African American women in engineering, and inspires future engineers in AI related careers.

Awareness of Women's Inclusion in STEM: Twitter Data in Italy

“…Keywords were selected based on the literature, combining "STEM" with terms related to women, common hashtags for women in STEM, and specific STEM fields like math, engineering, and chemistry (Alkhammash, 2019;Stella, 2020;Floyd, 2021).…”

“…Despite the widespread use of Social Opinion Mining (SOM), it's noteworthy that only a limited number of studies have ventured into this domain (e.g., Alkhammash, 2019;Stella, 2020;Floyd, 2021). Furthermore, most of these studies have primarily focused on the English language and have not considered the geolocation of tweets.…”