Tressie McMillan Cottom has been one of my favorite sociologists for a long time, and her mini-lecture on inequality and AI in education demonstrates why:
In her qualitative study reported in Lower Education, she argued that for-profit colleges were so attractive to low-income students (and in the end, so predatory) because of the widespread belief in the "access doctrine" – that the solution to poverty is more education to acquire skills (increasingly in technology) that will enable students from low-income communities to finally catch up with others. When the inequalities that shaped their lives meant that many students couldn't quit jobs or hand off family responsibilities, for-profit colleges promised them flexible programs to attain those "skills" in exchange for high tuition. The advice to "learn to code" sent so many students back to school with dreams of abundant jobs and generous salaries.
And now, Big Tech is promising great things with AI, and colleges are investing a lot in studying how AI can be integrated into the curriculum and the broader work of the university and how campuses can prepare students to be hired in new AI fields.
Her key point:
In the U.S., policy makers believe that people experiencing economic insecurity need "skills not supports" and so invest relatively little (compared to other western nations) in adequately funding schools, community libraries, affordable access to public colleges, income supports, health care, or stable access to adequate food and housing. Instead, if individual students invest their personal resources in acquiring what they're assured are highly marketable skills, they themselves will level playing fields.
She argues that colleges are now jumping into AI not because they are striving to better serve students and do research but because funders and policy makers are enamored with the next shiny tech tool and colleges cannot risk losing the support of either. Those in power will again be spared the costs of public investment in "supports" needed for more equitable opportunity. They'll rely instead on colleges to prepare their next generation of workers, at students' own expense. "Follow the money" she says, to understand why economically insecure people too rarely benefit from the new innovative academic fields that colleges develop in response to shifting employer demands.
Students chasing credentials via for-profit colleges wound up deeply in debt and without jobs, graduates of new "learn to code" courses in community colleges are facing shrinking jobs markets as AI is now writing basic code in many companies, and colleges are cutting humanities and liberal arts programs – the heart of being educated, not merely skilled – while trying to keep up with the ever-shifting STEM fields that donors and policy makers expect.
So many campuses build their work with first-generation students around this same "access doctrine": First generation supports are almost always separate from broader campus equity work that acknowledges structural inequality beyond campus; the goal instead is to prepare students for a fair and open job market while they're in college. The playing field is presumed to be leveled once poor and working-class students catch up with their peers through supportive tutoring and mentoring.
Yet so many poor and working-class students never get to or never finish college, their high school math and science courses often leave them unqualified for admission to competitive STEM degrees, they often graduate deeply in debt, and hiring decisions in the most competitive fields have never been only about formal credentials but also about "fit".
In other western nations, social supports help to equalize pathways to the credentials that lead to stable employment and living wages. In the U.S., poor and working-class college students are encouraged to instead invest their own (unequal) resources in acquiring more skills to compete in an ever-shifting economy.
And McMillan Cottom can succinctly speak to all of this with humor and grace after teaching a late class.
