In the landscape of American education, disparities in technological access create significant inequalities that impact students’ academic experiences and opportunities. This article explores how the availability of technology affects educational outcomes, particularly in high schools across Chicago, highlighting the urgent need for equitable access to AI and digital literacy resources.
During my tenure as an evaluator for a Chicago nonprofit that supports high school students, I noted a consistent trend: the quality and availability of technological resources at schools often predicted their capability to address students’ diverse needs effectively. Take Lincoln Park High School in a prosperous neighborhood, where the student population is 75% white. In comparison, those statistics are starkly different at Raby High School, which is in the economically challenged East Garfield Park area, where 83% of students are Black.
Lincoln Park High School boasts a modern and extensive array of technological tools, alongside a strong offering of computer science classes and an esteemed International Baccalaureate program for high-achieving students. Conversely, a 2013 initiative by former Mayor Rahm Emanuel aimed to transform Raby High School into a tech-forward STEM institution did not reach its objectives. Today, Raby struggles with limited technological offerings and a scant selection of tech-related courses.
Students from neighborhoods like East Garfield Park often experience inferior educational outcomes and exhibit lower graduation rates compared to their counterparts in affluent areas. Sociologists commonly link these challenges to segregation and community disinvestment. Additionally, educators in Title 1 schools face significant challenges, being underpaid, under-supported, and undertrained. The issue isn’t limited to urban settings; rural institutions, which have long struggled with technological access, are similarly at risk of falling behind.
The rapidly evolving AI in education sector is anticipated to grow exponentially, expected to amass a global market value of approximately $7.1 billion this year and projected to reach a staggering $112.3 billion by 2034. The implications are significant: students from low-income backgrounds may not be able to access AI’s dynamic tools, which aid in generating ideas, conducting research, and completing assignments, limiting their academic success compared to their peers from affluent backgrounds. Moreover, as AI capabilities expand, the gap in achievement between those proficient in AI and those who are not could become increasingly pronounced, disproportionately affecting racial minority students.
According to a 2024 report by RAND, around 61% of primary teachers serving predominantly nonwhite students have not received any training in AI, compared to roughly 35% of those teaching primarily white students. As school districts with majority white populations invest more heavily in AI resources, the gap in access to innovative technologies is only set to widen. This disparity translates to white students gaining not only early access to advanced AI tools but also acquiring essential skills that will drive their future success in the global economy.
While some of my colleagues advocate against increasing young students’ exposure to AI, fearing it may lead to “cognitive offloading” and dependency, other critics highlight AI’s existing biases, raising concerns that students may unknowingly absorb cultural prejudices from AI tools. Although there are currently few guidelines for AI implementation in educational settings, many—including educators like myself—believe the potential advantages of AI for student learning significantly outweigh the drawbacks. However, astrategic approach to fostering students’ AI skills is imperative.
At present, acquiring AI skills encompasses two critical areas: AI literacy and AI competency. AI literacy refers to understanding AI’s purposes, functions, and ethical implications, while competency involves developing technical skills, such as effectively using an AI chatbot for information retrieval or data analysis. A considerable number of middle and upper-income jobs, particularly in fields such as engineering, finance, law, and healthcare, will soon prioritize candidates who are adept at using and maintaining AI systems.
Alarmingly, Black and Latino students from low-income backgrounds already face a significant disadvantage regarding digital skills, largely due to their limited access to technology. According to a national survey by the Urban Institute, about 48% of Black youth and 31% of Latino youth lack basic digital skills—such as using word processing software or seeking job opportunities online—compared to just 16% of their white peers.
Even in fields where AI does not fully replace roles, there is a likelihood that it will diminish their scope, converting full-time roles into part-time or hourly positions with fewer benefits. Young people—especially those without a college degree—who are entering the workforce over the next decade may find themselves especially susceptible to this transition. At present, Black workers are overrepresented in the top five occupations vulnerable to automation, such as office support and food services. This trend could lead to reduced wages in these sectors and heightened unemployment risks, contributing to an estimated $43 billion annually widening of the wealth gap between Black and white households over the next two decades.
There is a growing consensus among experts advocating for early and thoughtful exposure to AI for young learners. Fortunately, teenagers express optimism regarding AI’s potential positive influence on their education. This enthusiasm can be harnessed through various initiatives.
Currently, a significant funding gap poses the greatest challenge to rectifying the AI divide, but the increased federal interest in expanding AI access presents new opportunities. Recently, President Trump signed an executive order aimed at establishing a K-12 education system that can cultivate an AI-ready workforce. It is imperative that the task force created from this order prioritize funding for Title 1 schools and those communities most affected by the persistent digital divide, as well as those likely to suffer the greatest job losses due to AI.
Policymakers and school leaders should also design AI learning standards that emphasize teaching students AI ethics, recognizing AI, understanding its mistakes, and executing fundamental tasks like information aggregation. Establishing such standards will ensure that schools are actively working towards developing both AI literacy and competency among students while holding educators accountable.
Importantly, there is a need to redefine school-industry partnerships, which are essential for advancing AI within educational systems. As Nidhi Hebbar, the former education lead at Apple, noted in a 2023 interview, when tech companies collaborate with schools, they primarily engage with more affluent, predominantly white institutions that already possess substantial resources. Policymakers must encourage these companies to form long-term partnerships with underprivileged districts, focusing on enhancing educator skills through ongoing AI training and providing students with access to complimentary AI tools and resources. Such a commitment should also involve supporting community-centered initiatives that educate youth about AI entrepreneurship and opportunities for internships in AI fields.
AI has the potential to help America regain its place in global education and promote equity across racial lines—an aspiration that has often been elusive. However, this cannot be achieved if our institutions continue to prioritize access for the privileged while neglecting the educational needs of underfunded youth.
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