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Automation, Gender, and Race 10 10 Policy Brief on the Future of Work MARTINDALE CENTER Executive Summary The rise of digital technologies has facilitated the increase of automation in the workplace; however, while increasing high-paying job opportunities that require highly skilled workers, automation will also result in a severe decrease in the need formediumto low-wage labor in theworkforce (Ernst et al.). Furthermore, the rise in automation is expected to disproportionately negatively affect women in the workforce in low-wage sectors and in sectors where women already face barriers to entry (Madgavkar et al.). This risk is also considable in occupational sectors with existing gender imbalances, both in spaces where women are disproportionately over- represented—office administration, for example—as well as in spaces where women are a minority, such as in science, technology, engineering, and mathematics (STEM) fields (Hayasaki). Automation is predicted to displace lower-paying forms of employment where the workforce is predominantly composed of women. For example, in a 2019McKinsey Global Institute report,Madgavkar and colleagues predicted that 52% of all the employment opportunities women will lose will be within the service and clerical sectors. Although automation may have the positive consequence of creating more higher-paying employment opportunities, individuals will have to upskill in order to achieve access to these new positions (Ernst et al.). However, the effort to upskill in order to adapt to an automatedworkplace likelywill prove unfairly difficult for women as a result of long-standing systemic barriers. Due to patriarchal gender norms, a large share of the time women could use to update their skills may be spent on unpaid family care work in a way that does not affect men. Furthermore, other dangers of patriarchy, such as inhibited social mobility because of physical safety and barriers to access educational opportunities and STEM field technologies, may limit the efforts of women to participate in automated environments (Madgavkar et al.). In the samewaywomen facebarriers toaccessingopportunities in an automated environment, so do people of color. In the US people of color areminoritized in society at large and often face racial discrimination in the workplace (Triana). Prevailing social and economic systems result in socioeconomic inequalities that manifest themselves as racialized access to resources, suchas educationand training, andeven inequalities in terms of access to job opportunities (Walters). Even in the context of automation, these long-standing social disparities are expected to perpetuate systemic racial discrimination in the workplace (Chessel). Due to the intersectional nature of systems of injustice, gender and racial inequalities may particularly placewomen of color at added risk of displacement due to automation (Crenshaw). With these issues in mind, this paper intends to investigate what measures the US government might undertake in an effort to ensure that automation does not disproportionately displace women in the US labor force. In order to accomplish this, we will first elucidate the consequences of automation for women, in particular women of color. We will further highlight expected trends in this context, and finally we will make feasible recommendations based on empirical evidence. Issues and Challenges As the world changes, it comes as no surprise that the labor market shifts in response. For centuries, technological developments have been a driving force behind an ever- changing labormarket, with outdated sectors declining as new jobs emerge (Brynjolfsson & McAfee). Today, technological evelopments in artificial intelligence (AI) are driving a new wave of evolution in the labor market, resulting in big changes in occupational demand. Often referred to as the Fourth Industrial Revolution, automation will play a key These Martindale Center Policy Briefs on the Future of Work were prepared by teams of students and young professionals serving as Research Externs with the Lehigh University / United Nations Partnership working in affiliation with the International Labour Organization. Authors: Max Bonzulak • Grace Enriquez • Dan Rudiak • Ami Yoshimura • Sinenhlanhla Zungu Series Editor: Stephen Cutcliffe, Ph.D. February 2021 Automation, Gender, and Race