{"id":14642,"date":"2020-08-03T22:48:03","date_gmt":"2020-08-04T05:48:03","guid":{"rendered":"https:\/\/www.springboard.com\/?p=14642"},"modified":"2023-11-15T09:00:02","modified_gmt":"2023-11-15T17:00:02","slug":"women-in-machine-learning","status":"publish","type":"post","link":"https:\/\/www.springboard.com\/blog\/data-science\/women-in-machine-learning\/","title":{"rendered":"Why Women Are Making It Big in Artificial Intelligence and Machine Learning"},"content":{"rendered":"\n

It\u2019s no secret that STEM professions\u2014shaped by years of gender and racial bias\u2014lack diversity. Machine learning engineering and research is no exception. Women currently hold around 25% of all computer science-related jobs, and only 12% of machine learning roles, with factors such as a lack of pay and career advancement transparency and a lack of women role models contributing to those numbers.<\/p>\n\n\n\n

But leaders in the machine learning and AI industry have in recent years woken to the value that women bring to the workforce. It doesn\u2019t just look good for a company to have diversity\u2014it\u2019s integral to the success of organizations that build machine learning algorithms and artificial intelligence. Having more women working on machine learning and AI can alleviate the issue of selection bias, which is one of the biggest problems facing AI enterprises. \u201cIn order for organizations to achieve the highest AI maturity levels, it is necessary to mobilize women on a mass scale and include them as part of all enterprise endeavors in artificial intelligence, from research to product launch,\u201d according to a report from Forbes.<\/p>\n\n\n\n

To that end, tech execs have made it their mission to diversify their hires and teams, overhaul toxic cultures, and prevent attrition. Many women machine learning engineers and researchers have also taken matters into their own hands, creating opportunities and support networks for women who are either considering or have already embarked on their technology careers, supporting young women through mentorships, and clearing some of the hurdles that stand in the way of women who have a technical background.<\/p>\n\n\n\n

Women are making meaningful headway in the field of machine learning and artificial intelligence. Read on to learn more about the challenges women are overcoming and the opportunities that are helping close the gender gap.<\/p>\n\n\n\n

How Can We Get More Women in Artificial Intelligence and Machine Learning Careers?<\/h2>\n\n\n\n

Many of the challenges that stand in the way of women building long and satisfying careers in machine learning engineering and research are systemic and have proven difficult for organizations to dismantle. The good news is that many companies, industry leaders, and women have stepped up to the challenge\u2014the issue of diversity is being prioritized in professional conversations, organizations are attempting to build a more supportive environment, and women are finding ways to exchange ideas and share information in ways that help each other advance their careers.<\/p>\n\n\n\n