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Community colleges can become America’s AI incubators

FILE - In this Nov. 29, 2019, file photo, a metal head made of motor parts symbolizes artificial intelligence, or AI, at the Essen Motor Show for tuning and motorsports in Essen, Germany.
(AP Photo/Martin Meissner, File)
FILE – In this Nov. 29, 2019, file photo, a metal head made of motor parts symbolizes artificial intelligence, or AI, at the Essen Motor Show for tuning and motorsports in Essen, Germany.

Millions of students attend community colleges every year, with almost 1,300 schools located in every corner of the United States. With their large student bodies, community colleges are a massive source of potential for expanding the artificial intelligence (AI) workforce, but employers and policymakers alike sorely underestimate their potential. 

If the United States aims to maintain its global lead and competitive advantage in AI, it must recognize that community colleges hold a special spot in our education system and are too important to be overlooked any longer. 

As detailed in a recent study I co-authored as part of Georgetown University’s Center for Security and Emerging Technology (CSET), community colleges have the potential to support the country in its mission for superiority in AI. Community colleges could create pathways to good-paying jobs across the United States and become tools for training a new generation of AI-literate workers.  

Instead, the focus today remains squarely on four-year colleges. Employers routinely only consider applicants with a bachelor’s degree, even though one-third of the AI workforce does not have one. This number reflects the broader U.S. labor force, where 60 percent of workers do not have a four-year college degree. Degree requirements also disproportionately affect communities of color, as nearly 70 percent of Black and 80 percent of Latino workers do not have a bachelor’s degree.  

Employers of the AI workforce need to eliminate arbitrary bachelor’s degree requirements. They disenfranchise a wide swath of diverse talent, shrink the talent pool in an already tight labor market and block pathways to quality jobs for workers everywhere. Instead, these public and private employers need to broaden and diversify their workforce by focusing on credentials that signal competency.  

Undervaluing sub-baccalaureate credentials keeps community colleges from leveraging their many strengths. They reach a diverse student population, are affordable and flexible and have a proven track record of education and training in technical fields. The adaptability of their programs allows them to embed stackable credentials that students can accumulate over time, creating entry and exit points into and out of the education system for students while retaining proof of competencies for employment.   

Community colleges offer a place of learning for those who have full-time jobs, must take care of their families, lack the resources to pay for an expensive four-year degree, or face any of the other career-inhibiting burdens shouldered by millions of Americans.   

While community colleges could become a key feature of the AI workforce training pipeline, achieving this potential is no small task. They are beset by a number of long-standing challenges, such as nebulous and inconsistent funding (and many competing priorities for said funds), staff recruitment and retention difficulties, and a student population with many needs not faced by those at four-year colleges. The result of these challenges is persistently low completion rates, particularly in STEM fields. More recently, community colleges have been heavily impacted by the COVID-19 pandemic, further taxing their limited resources. 

These problems are well known, and efforts by schools to mitigate them have shown progress. Various community colleges across the country are experimenting with promising ideas like guided pathways to address one or more of these challenges. Workforce training programs in other fields also offer a guide on what to do and not do. As community colleges begin to implement AI and AI-related programs, they should make sure to include best practices from these efforts. 

Schools also need to ensure that AI and related credentials will actually lead to quality jobs. One issue they face is that the current credential landscape remains like the Wild West. There are almost 1 million unique credentials in the United States, and they vary dramatically in caliber. Furthermore, there is currently little demand for AI certifications from employers. This will most likely remain the case until there are industry-accepted standards or some other accreditation effort for AI-related credentials.   

That is where the federal government can help. The National Institute of Standards and Technology (NIST), or another suitable government agency, should facilitate the creation of a framework for work roles and competencies for AI jobs. This will help schools design their programs to match them and help industries understand which credentials are valuable. NIST created a similar framework for cybersecurity called the National Initiative for Cybersecurity Education (NICE) which has been hugely successful. Non-government standards-setting organizations (along with industry stakeholders) could also be leveraged, in partnership with or in place of NIST, to help create something similar for AI.  

Leveraging community colleges offers a way for the United States to outpace its competition, create upward mobility for millions of workers and adapt its workforce for the jobs of the future. But they need help to get there. With the right support from policymakers and buy-in from the many other stakeholders needed, they can turn their potential into reality. 

Luke Koslosky is a research analyst at Georgetown University’s Center for Security and Emerging Technology (CSET).  

Tags Artificial intelligence Artificial intelligence arms race community college economy Politics of the United States Workforce development

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