As AI Replaces Jobs, Here Is the Impact It Will Have on College Women

A McKinsey report notes that automation — which includes the use of robots, document processing systems, and generative AI tools, such as ChatGPT — is reshaping job demand. The jobs most susceptible to being impacted by AI are those in clerical support, food services, and customer service, which are disproportionately occupied by women.

Furthermore, a study by the University of North Carolina’s Kenan-Flaglar School of Business found that 8 out of 10 women in the U.S. workforce are in occupations considered to be highly exposed to AI’s impact.

As dire as these statistics may seem for college women entering the workforce, impact does not mean replacement. By implementing various measures, including upskilling, addressing gender biases in algorithms used by employers to identify job candidates, and creating inclusive work environments, employers may support college women’s success in an environment where the future of work is rapidly changing.

In an attempt to avoid the gender biases that historically surface when humans screen applications, employers are relying on algorithms to identify job candidates.

The algorithms are essentially a set of instructions that an employer develops based on various characteristics, including skills required for the job and attributes from past successful candidates that led to good performance, and inputs these instructions into a database. A set of recommendations is then generated from existing candidate profiles on sites such as LinkedIn and Indeed.

But while such algorithms may seem objective, they are developed by humans, which means they are still not devoid of the same gender biases that surface when humans make hiring decisions.

For example, a study on the hiring algorithm used by Amazon found that it gave consistently higher employability scores to men than women. In an interview with BestColleges, Dr. Robbie Nakatsu, a professor in Information Systems and Business Analytics at Loyola Marymount University and an expert in AI/Machine Learning, gave the following example:

Imagine a tech company that is looking to hire programmers. The company is bombarded with resumes and may decide to screen them using an AI program that was trained on who the successful applications for programming positions have been in the past. The company may have a track record of hiring mostly male employees (not uncommon in the tech industry), and its algorithms may, unwittingly, screen out well-qualified female candidates based on past hiring practices.

Women also face gender biases in the recruitment and selection stage and in promotion decisions. According to the 2021 Women in Tech Report by TrustRadius, 39% of women believe that gender bias is a barrier to promotion.

Given the inhospitable work environments they often encounter, 50% of women who take a job in the tech industry leave before the age of 35. Left unaddressed, the same gender biases that adversely impact women in the workplace may impact job opportunities for college women and exacerbate the gender digital divide that leaves men and women on unequal playing grounds in the future of work.

The reason why most women’s jobs will be impacted is because they occupy white-collar jobs, requiring knowledge creation, which is a capability that AI tools now have. Approximately 70% of women’s jobs are white collar and 30% blue collar, while men have a fairly even 50-50% split, according to a report by the Kenan Institute at the University of North Carolina, Chapel Hill.

When examining the top 15 occupations most impacted by AI, the report found that women currently occupy more of these jobs (58.87 million) than men (48.62 million), even though there are more men (84.21 million) than women (74.08 million) in the workforce.

While there is a significant gender difference in access to technology globally, in the U.S., the greatest difference is in the representation of women relative to men in the tech industry. In 2022, women made up only 22% of the tech workforce and were most underrepresented in the occupations expected to see the biggest increases by 2030, including engineering (15%), computers (25%), and physical sciences (40%).

But not all is doom and gloom. Provided that employers and educators address the aforementioned biases, college women can thrive and learn to leverage AI through a couple of avenues:

Given the shift to automation, employers will be hiring based on skills. STEM and healthcare are the two career fields that are expected to see the biggest increases in labor demands. College women may consider these fields as they explore career options.

Even if they decide not to enter a technical field, taking computer science degree programs or programming courses will help make women more competitive job candidates. Employers are increasingly focused on skills-based hiring. Listing specific skills on their resumes, such as Javascript or Python, rather than simply coding skills, will also strengthen women’s job prospects.

Other skills that cannot be automated will also be in demand. Emotional intelligence, empathy, and collaboration will become increasingly necessary when working with teams and in roles that require AI-human interactions. Developing these skills can also support women’s advancement in a changing landscape.

Viewing technology and AI systems as resources rather than threats to one’s job security can also help empower women. By learning how AI may be used in their professions to increase their productivity and creativity, women can maintain a competitive advantage in the job market.

When asked how AI can enhance educational platforms and make learning more accessible, Dr. Nakatsu noted:

A more optimistic viewpoint (one that I subscribe to) is that AI will level the playing field for online learning and education. Generative AI tools like ChatGPT, Bing Chat, and Google Bard are good examples. They are easy to use — you can just jump right in with little to no training on how to prompt them … I believe they will be a huge boon for online learning and education. Fortunately, they are available to all socio-economic classes and all types of people and don’t require anything other than a computer and a good Internet connection.

Preparing women for an AI-driven world starts early. Studies find that girls’ interest in STEM fields is high in grammar school, but it wanes as they age.

Research conducted by Dr. Shalini Kesar, an associate professor in the Department of Computer Science and Information Systems at Southern Utah University, found that 38% of girls in middle school believe that careers in programming and coding are not for them, and that percentage increases to 58% when they start college. Organizations such as Girls Who Code can be instrumental in exposing girls at an early age to STEM.

Universities can also help empower women by connecting them with industry professionals who may serve as mentors and role models to answer questions and provide guidance. Increasing the number of courses that focus on building AI and other tech skills and publicizing them during student orientations can also be effective in preparing college women for the workforce. Making technology courses available to high school students can also expose students to these fields before they go to college.

Employers, especially those in fields with the greatest labor demand, may also be proactive in recruiting women by establishing relationships with local universities and helping to develop their talent pipeline. Once hired, providing newly graduated and early-career women with seasoned professional mentors can better ensure their retention and advancement.

While research suggests that women’s jobs will be most impacted by AI, it does not mean they will be replaced. As Richard Baldwin, professor and economist at the Geneva Graduate Institute in Switzerland, noted, AI will not take your job. It’s somebody using AI that will take your job. In a fast-evolving employment landscape, continuous learning will be key.

On an individual level, college women can effectively compete in the job market and move toward greater automation by developing the technical and soft skills employers seek. On an organizational level, employers may level the playing field and ensure women have the same employment opportunities as men by addressing the gender biases that surface when using algorithms for employee recruitment and selection and by creating inclusive environments to increase women’s retention.