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CommentaryEducation

AI didn’t break higher education—It exposed the credential trap

By
Jason Benedict
Jason Benedict
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By
Jason Benedict
Jason Benedict
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July 7, 2026, 5:30 AM ET

Jason Benedict is AVP for Information Technology and Chief Information Security Officer at Fordham University.

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Jason Benedict is AVP for Information Technology and Chief Information Security Officer at Fordham University.courtesy of Fordham
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Higher education stands at an inflection point. Increasingly, colleges and universities are evaluated less as intellectual communities and more as economic instruments. Students, facing unprecedented tuition costs, credential inflation, labor-market anxiety, and technological disruption, often approach higher education transactionally: the degree becomes the objective, while learning itself becomes secondary. The resulting tension has profound implications not only for academic integrity but also for the future of professional ethics, workforce preparedness, and democratic society itself. The central challenge facing modern education may therefore no longer be simply how to prevent cheating, but rather how to restore intrinsic value to learning within systems increasingly optimized for credentials.

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Educational psychology provides a useful framework for understanding this phenomenon through the distinction between intrinsic and extrinsic motivation. As psychologists Edward L. Deci and Richard M. Ryan established in their foundational research on Self-Determination Theory, intrinsic motivation refers to engagement driven by curiosity, mastery, intellectual growth, and personal meaning. Extrinsic motivation, by contrast, centers on outcomes such as grades, salaries, social mobility, status, and credential acquisition. Research consistently demonstrates—such as Paul R. Pintrich’s landmark study in the Journal of Educational Psychology—that students motivated intrinsically exhibit stronger academic engagement, persistence, and satisfaction, while those driven primarily by extrinsic outcomes are more likely to adopt surface-level learning strategies and engage in academic dishonesty. A 2024 study titled “Here to Learn or Just Earn” found that intrinsically motivated students displayed significantly higher levels of academic confidence and engagement than their extrinsically motivated peers. The title itself captures a growing societal concern: many students increasingly perceive higher education less as a formative intellectual experience and more as a necessary economic gateway.

This shift toward credentialism is not entirely irrational. In many sectors, as sociologist Randall Collins argued in The Credential Society, degrees function primarily as signaling mechanisms. Employers frequently use educational credentials as filters during hiring, regardless of whether the knowledge gained directly aligns with workplace responsibilities. Simultaneously, skyrocketing tuition costs and compounding student debt burdens—with total U.S. student loan debt now surpassing $1.8 trillion—have intensified pressure on students to maximize their immediate return on investment. Under such conditions, students behave logically within the incentive structure presented to them. If the system rewards credentials more reliably than authentic understanding, optimization behavior naturally follows.

Academic dishonesty emerges predictably within such environments. Educational resources from the Boston College Center for Teaching Excellence note that students are more likely to cheat when they fail to perceive course content as personally or professionally meaningful. Further research into Self-Determination Theory similarly demonstrates that reduced autonomy, diminished relevance, and a lack of intellectual engagement correlate strongly with dishonest academic behavior. In essence, when education is experienced merely as a series of bureaucratic obstacles to overcome rather than opportunities for growth, cheating becomes easier to rationalize.

This dynamic has become particularly visible in the age of generative artificial intelligence. AI has not created the problem of academic dishonesty, but it has exposed longstanding weaknesses in assessment design. Traditional assignments often reward polished outputs more than authentic cognitive processes. When success is measured primarily through deliverables, students naturally gravitate toward tools that maximize efficiency, a reality documented by The Guardian in its deep dive into the university AI cheating crisis. AI-assisted cheating therefore reflects not only student misconduct but also institutional overreliance on industrial-era assessment models poorly suited for a knowledge economy increasingly shaped by automation.

Importantly, the implications extend far beyond academia. In their extensive book Cheating in College, researchers Donald L. McCabe, Kenneth D. Butterfield, and Linda Klebe Treviño identified meaningful correlations between academic dishonesty and unethical professional conduct later in life. This is especially concerning in fields such as cybersecurity, medicine, law, engineering, and finance, where integrity is foundational to public trust and safety. A student who internalizes the idea that outcomes matter more than process may carry that mindset into professional environments where ethical shortcuts can produce systemic harm. The normalization of transactional thinking in education therefore risks cultivating broader cultural acceptance of ethical compromise.

Yet it would be simplistic and unfair to portray contemporary students as intellectually disengaged or morally deficient. Most students occupy a more complex middle ground. They seek employability and economic security while simultaneously desiring meaningful personal growth and intellectual fulfillment.

The root problem lies less with student character than with institutional incentives and the corporatization of the university itself. Higher education leadership has increasingly adopted corporate management models that treat students as customers and degrees as products. As scholars Sheila Slaughter and Gary Rhoades detailed in their critique of “academic capitalism,” universities, driven by an obsession with commercial college rankings like U.S. News & World Report, have hyper-focused their institutional efforts on corporate enrollment metrics, graduation rates, and immediate post-graduate employability statistics. In many cases, universities themselves reinforce the commodification of education by marketing degrees primarily through salary outcomes and career pathways rather than intellectual development. When institutions frame their entire value proposition around economic advancement, they can hardly blame students for treating the classroom as nothing more than a transaction.

The solution, therefore, cannot rely solely on punitive anti-cheating measures or intrusive surveillance technologies. Universities must instead redesign educational experiences to make learning itself meaningful, relevant, and difficult to outsource. As James M. Lang argues in Cheating Lessons, this requires a shift toward authentic assessment models emphasizing critical thinking, synthesis, creativity, collaboration, oral defense, and applied problem-solving. Courses must connect more directly to students’ personal identities, ethical responsibilities, and future societal roles. AI literacy should become central to modern education, not merely as a technological competency, but as a framework for understanding authenticity, cognition, ethics, and human value in an automated world.

Moreover, institutions must reassert a philosophical defense of education itself. The purpose of higher education cannot be reduced exclusively to workforce preparation. As philosopher Martha Nussbaum argues in Not for Profit, universities serve broader civic, cultural, and moral functions. They cultivate judgment, intellectual humility, ethical reasoning, historical understanding, and the capacity to navigate ambiguity. These human capacities may become even more valuable as artificial intelligence automates increasing portions of technical and procedural labor.

Paradoxically, the rise of AI may ultimately strengthen the case for intrinsically valuable learning. As information retrieval and routine production become commoditized, genuinely human qualities such as creativity, empathy, wisdom, ethical discernment, and interdisciplinary thinking grow more important. In such a future, education centered solely on credential acquisition may prove increasingly hollow. The students who thrive will not necessarily be those who optimized most efficiently for grades, but those who developed durable intellectual curiosity and adaptive thinking.

In conclusion, the growing emphasis on credentials over learning represents one of the defining tensions of modern higher education. Economic pressures, institutional incentives, and technological disruption have collectively encouraged increasingly transactional relationships between students and education. This environment contributes directly to rising academic dishonesty and weakens the intrinsic value traditionally associated with intellectual development. However, the solution is not nostalgia for an idealized academic past, nor simplistic condemnation of students. Rather, higher education must evolve toward systems that reward authentic engagement, ethical reasoning, and meaningful human development. The central educational challenge of the coming decade is therefore not simply preventing cheating, but rebuilding cultures in which learning itself is once again perceived as inherently valuable, personally transformative, and socially essential.

The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.

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