“Students are human and humans cheat.”"If you make it easy for people to do, then it's more likely to happen."In this thought-provoking 33rd episode of The Opposite of Cheating, David speaks with Phil Newton, neuroscientist and academic integrity researcher at Swansea University in Wales. Phil brings a rare blend of scientific rigor and pedagogical insight to the conversation, reflecting on how memory, motivation, and fairness intersect with cheating, assessment, and the rise of AI in education.Together, they explore:* the neuroscience behind why facts matter—and why offloading them to AI could erode critical thinking* the ethics of unsupervised exams and why “please don’t cheat” is not enough* what it means to “certify” learning in a world where students—and machines—can do so much unseen* why foundational knowledge is still essential in medicine, democracy, and education* how universities might be failing students by making cheating the easiest optionYou can follow Phil on LinkedIn at https://www.linkedin.com/in/prof-phil-newton-21966b8a/

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