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Generative AI has quickly become the villain of higher education. Tools like ChatGPT are often portrayed as threats to academic integrity: convenient cheats that allow students to bypass learning. But perhaps the real issue isn’t the existence of AI; it’s that traditional academic structures haven’t evolved to make sense of it. When an algorithm can write a well-structured essay in thirty seconds, the act of essay writing itself is no longer an accurate measure of understanding. Instead of fearing this shift, academia should see it as a signal: grading and assessment models need to evolve.

This fear of technological change is nothing new. The calculator was once banned from classrooms, and Wikipedia was dismissed as unreliable. Over time, both became integral tools for learning. As Si & Chen argue, “every major innovation first appears to threaten knowledge before it deepens it” (2020). The same is true for AI. Universities can either continue treating it as academic misconduct or begin teaching students how to collaborate with it intelligently and ethically.

Personally, experimenting with tools like ChatGPT has changed how I approach learning. When used thoughtfully, AI complements my thinking, not replace it. It helps me explore ideas faster, question my assumptions, and communicate more clearly. It’s a brainstorming partner that still requires my judgment to refine and verify the results. Through this experience, I’ve realized that education shouldn’t be about proving we can work without AI, but about showing we can think beyond it.

To move forward, academia must redefine what it means to “learn.” This means embracing AI literacy, emphasizing transparency in its use, and assessing students on critical reasoning, creativity, and ethical application rather than memorization or rigid essay structures. Collaboration between students, educators, and AI can create richer learning experiences that prepare graduates for a world where AI is ever-present.

As UNESCO’s AI and Education Report (2020) notes, “AI should augment human capacities, not replace them.” If academia embraces that philosophy, AI won’t destroy intellectual honesty – it will redefine it, turning learning into a more reflective, creative, and deeply human-centered process.

References

Si, S., & Chen, H. (2020). A literature review of disruptive innovation: What it is, how it works and where it goes. Journal of Engineering and Technology Management, 56(56), 101568.UNESCO. (2021). AI and education: guidance for policy-makers. Unesco.org. https://unesdoc.unesco.org/ark:/48223/pf0000376709 

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In many societies, prison is treated as the end of the line. A person makes a mistake, they are punished, and that is where the story is meant to stop. But in reality, punishment rarely ends at the prison gates. Once released, many find that time keeps extending: the labor market is locked, employers refuse to trust, and the stigma of a conviction shadows every attempt at reintegration. Faced with closed doors, relapse into crime, recidivism, becomes less a personal choice than a structural inevitability.

The Last Mile, a U.S. based initiative, is trying to rewrite that script. From within four walls that can crush hope, it offers a secure digital platform for education and training that breaks them down. Its curriculum ranges from web development to audio and video production, preparing inmates to become workforce-ready professionals. More importantly, it weaves connections between prisons, NGOs, state officials, and employers – creating an ecosystem of opportunity that extends beyond release.

Yet the program’s biggest challenge isn’t technical. It’s ethical. Most platforms struggle with the chicken-and-egg problem, scaling, pricing, and trust. Uber had to attract riders and drivers; Airbnb needed hosts and guests. The Last Mile faces similar dynamics, but in a different form. Here, the chicken-and-egg is ethical: can society accept ex-prisoners as workers? Scaling is less about numbers than about committed employers. Pricing is political, relying on public funding and NGOs. Trust collides with stigma, not just user reviews. And its main competition isn’t another platform, but the belief that prison should punish, not rehabilitate. Success depends on ethics as much as technology.

A survey on public perceptions of imprisonment (Roberts et al., 2024) illustrates this tension starkly: 42% of respondents said the main purpose of prison is to “protect the public by removing offenders from society,” while only 19% prioritized “rehabilitating offenders.”

For an inmate, that 19% is a fragile lifeline. For the 42%, it’s a nightmare – A belief that reintegration is dangerous or undeserved. Initiatives like The Last Mile cannot succeed unless society itself chooses to believe in second chances. Its platform only works if employers are willing to hire, communities are willing to welcome, and governments are willing to fund rehabilitation over perpetual exclusion.

Would this model work in the Netherlands? Possibly, Dutch justice policy already leans toward reintegration. But it would still hinge on public trust. Platforms live or die not by their code, but by the moral consensus of the societies around them.

And so the real question remains: when punishment ends, do we allow life to begin again – or do we quietly insist that a sentence never truly finishes?