Episode 33: Phil Newton

"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 option.

The conversation balances the philosophical and the practical, offering both caution and clarity in an era of accelerating change.

You can follow Phil Newton on LinkedIn at https://www.linkedin.com/in/prof-phil-newton-21966b8a/

(Disclaimer: episode quotes and summary were created using Youtube's Transcript and ChatGPT and edited by a human. Any errors are the responsibility of the human).