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Automation, Gender, and Race 11 11 role in defining the future of the labor force. As a result of the automation of tasks, there has been a decline in demand for certain jobs in categories such as office support, customer interaction, and predictable physical work (Madgavkar et al.). Meanwhile, these same technological developments have driven an increase indemand for technology professionals, care providers, and builders. When looking at the issue from a gendered perspective, the jobs in decline are held roughly equally by men and women, where their difference in wages mirrors the national average (Madgavkar et al.). However, amongst growing jobs, those predominantly held by women are significantly lower paying than those predominantly held bymen (Catalyst). This can be attributed to the fact thatmanyof theemerging, technologically driven jobs are in areas with existing gender gaps, such as engineering, math, and computer science (Hayasaki). By examining expected job gains, a concern for gender equality in the labor force arises: “These technological changes will create new kinds of jobs while displacing others. Men will see nearly 4million job losses and 1.4million gains (approximately onenew job created for every three lost). In comparison, women will face 3million job losses and only 0.55million gains (more than five jobs lost for every one gained)” (Hayasaki). A recent World Economic Forum study reported that existing gendergaps inSTEM-dominatedfieldswoulddiminishwomen’s professional presence in the coming years (Rubery). When we expand this analysis and make the comparison between declining-job and growing-jobwage gaps for race, the difference is evenmore stark. Emergent jobs predominantlyheldbypeople of color pay significantly less than those predominantly held by white workers (Census Bureau). Additionally, women of color face significant barriers whichmake it difficult for access into these emerging fields: “In 2017, while more American women held college degrees compared to American men, they only accounted for 29% of workers employed in the STEM field…, [while] women of color only accounted for 11.5% of workers in STEM” (National Science Foundation). Moving forward, it is important to examine the ways inwhich automation, AI, andmachine learning will impact women, in particular, women of color. In the coming years, as we pursue higher levels of automation, “Jobs lost, gained, and changed imply that many millions of women may need not only to transition between occupations and sectors, but also tomake substantial changes in theway theywork in their existing jobs” (Madgavkar). In order to promote and uphold the principles of gender equity, it is crucial that we address growing disparities. Policy Options Given the complex nature of the relationship between automation, women, and race, it is essential that the US governmentmove toward implementing policies that promote gender equity in the workplace, in order to combat possible externalities of automation and AI development, which may hurt progress toward gender equality more broadly. Policies that empower women, and women of color, are necessary to target current and future gender gaps. Taking action is critical, especially during a time in which the ongoing global pandemic has led to regressive effects on gender equity. Additionally, the world’s economic recovery following the global pandemicwould benefit greatly if countries all around the world implement social and economic policies benefiting women, as “gender- parity improvements by 2030 could lead to $13 trillion of incremental GDP in that year” (Madgavkar). However, these benefits canbe achieved only if action takes place immediately. Some policies to consider include easier access to education, upskilling, and re-education for women and women of color (specifically STEMeducation); legislationproviding improved maternal and paternal leave; strengthening childcare benefits for parents; ensuring that women and women of color have an active role in policy implementation; and promoting diverse working environments throughout the country. In order for American women to successfully and equally transition to an economy changed by automation, easier access to education and skill training in fields that are projected to grow the most is an essential step toward decreasing gender gaps in theworkforce.Worries exist that womenwill have “low representation in sectors where job growth is expected,” as a result of automation (Gutierrez). However, only “66 percent of executives saw addressing potential skill gaps related to