You’ve been using AI tools for months. So why do you have less time than before?

The answer is 150 years old. In 1865, an economist named William Stanley Jevons discovered something deeply counterintuitive: when a technology becomes more efficient, total consumption of the resource it saves tends to go up — not down. More efficient coal engines didn’t reduce coal use. They made coal cheaper to run, so demand exploded.

The same mechanism is running on your calendar right now. Researchers call it workload creep — and it follows a predictable pattern. The faster AI lets you produce, the more output gets expected of you. That efficiency gain doesn’t go to you. It gets absorbed into the new baseline before you ever had a chance to keep it.

In this episode, we break down the Jevons Paradox and what it actually means for leaders deploying AI tools across their organizations. We look at why 95% of large enterprise AI investments are generating zero measurable return — while 90% of workers are successfully using AI on their own outside company systems. We examine the jagged frontier: where AI performs brilliantly and where it silently fails. And we get to the one architectural shift that actually breaks the cycle — the difference between automating a task and automating a workflow.

About the host

Laurence Gill is an IT leader with more than two decades of experience overseeing technology implementation across the U.S. government.. He is a doctoral candidate in cybersecurity with a dissertation focused on federal IT spending, and has spent years training youth and adults in workforce development skills including financial literacy, cybersecurity, entrepreneurship, and AI. That training mission is the reason this podcast exists: making complex, high-stakes knowledge accessible to the people who need it most, without requiring a technical background to benefit from it.

Ransomware attacks on hospitals are not a technology problem — they are a patient safety crisis. In Episode 4, Laurence Gill draws on his background as a doctoral candidate in cybersecurity and two decades of federal IT leadership to break down why healthcare is the number one ransomware target in the country, how these attacks produce documented patient harm, and why the ransom decision is a clinical emergency, not a policy debate. Anchored by the ransomware storyline in The Pitt Season 2 Episode 7 — which aired the same morning the University of Mississippi Medical Center was hit by a real attack — this episode delivers the governance framework every healthcare leader needs before the next crisis lands: how to build resilience before an attack, how to execute during one, and the accountability questions that belong on every leadership agenda right now.

AI doesn’t just get things wrong. It gets things wrong with complete confidence — citing studies that don’t exist, building logical arguments around biological impossibilities, and delivering dangerous recommendations in the fluent, authoritative voice of a clinical expert. In healthcare, that gap between confidence and accuracy isn’t an inconvenience. It’s a patient safety crisis.

In Episode 3 of AI Literacy for Leaders, Laurence Gill breaks down the mechanics of AI hallucination in clinical settings — drawing on guidance from the World Health Organization, UK regulators, and a landmark study that tested whether humans can actually catch AI lies. The findings are more alarming than most healthcare leaders realize.

You’ll learn the three distinct types of AI hallucination that clinicians need to recognize, why experienced physicians miss them more often than you’d expect, and why using a second AI to check the first one doesn’t solve the problem. You’ll get a practical green-yellow-red framework for where AI is safe to use, where it requires careful oversight, and where it should never go near a clinical decision. And you’ll hear about a failure mode that almost nobody is talking about — not AI that lies, but AI that goes dangerously silent.
The episode uses storylines from The Pitt on HBO Max — where a hospital’s AI clinical assistant hallucinates a treatment recommendation and calls the entire tool into question — as a narrative anchor for what real healthcare organizations are navigating right now.

The future of medicine isn’t AI versus doctor. It’s the clinician who knows how to interrogate AI output versus the one who accepts it at face value. This episode gives you the framework to be the former.- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -

Runtime: Approx. 30 minutes

Hosted by: Laurence Gill

Series: AI Literacy for Leaders