As artificial intelligence becomes part of everyday work, understanding what AI does well and where human intelligence remains essential is increasingly important.
In this episode of Candello’s MedMal Matters podcast, Matthew Hays, Ph.D., Senior Vice President of Research and Analytics at Amplifire, joins host Michael Paskavitz for a conversation about artificial intelligence, human cognition, and the science of learning. Matt explores where today’s AI excels, where it can struggle, and why human knowledge and judgment remain critical as these tools become more widely used.
The conversation turns to an especially important challenge in healthcare: people do not always know when their knowledge is wrong. Matt explains Confidently Held Misinformation™, which occurs when someone is confident in incorrect knowledge. Unlike uncertainty, which may prompt someone to seek help or verify an answer, misplaced confidence can lead directly to action. In healthcare, identifying and correcting these misconceptions can play an important role in reducing risk and supporting patient safety.
Matt also explores a counterintuitive lesson from cognitive science: learning that feels easy is not necessarily learning that lasts. Techniques such as spacing and interleaving can make learning more challenging in the moment while strengthening long-term retention. These principles reflect the brain science behind Amplifire’s approach to learning, which focuses instruction on what each learner needs to master rather than spending equal time on what they already know.
So where does AI fit? Matt argues for using AI where its strengths can complement human intelligence, particularly for tasks with clear patterns and ways to verify the output. In learning, the opportunity is not simply to add AI to traditional training. It is to design AI learning experiences around how people actually build, retain, and apply knowledge. That means using AI to support personalized instruction while keeping learning science at the foundation.
For healthcare leaders navigating the rapid growth of AI, the conversation offers an important perspective: new technology may change how we work, but it does not change how the human brain learns.