SiMPL #008 The Planning Fallacy & AI Without the Hype

Last week, while working on SiMPL News Episode 007, I had a moment of realization: two things stood out. First, I completely missed out on the perfect James Bond reference (seriously, “007”—what was I thinking?), and second, I needed an AI section for the newsletter. But let’s not dwell on the missed Bond moment. You know what they say—“No, Mr. Bond, I expect you to learn” (well, something like that).

So, instead of mulling over missed opportunities, let’s dive into something that’s been on my mind lately—the planning fallacy.

The Ballad of the Lost Passports!

You know how life loves to throw curveballs at your best-laid plans? Well, I had a front-row seat to that with my mom’s recent trip to Europe. If you missed the backstory, don’t worry, I’ve got you covered.

This all ties into a well-known psychological concept, and trust me, you’ll nod along in sympathy.

So, my mom and her partner started planning a simple trip to Europe—attend a wedding here, hit a few cities there. Easy, right? But that was just Plan #1. What followed was a whirlwind of added cities, changing schedules, and eventually, a missing backpack.

And then, classic planning fallacy in action—they lost their passports in Pisa. Yep, all those meticulously crafted plans went out the window thanks to a stolen backpack. Good times.

As for the trip? It actually ended on a high note—or as high as possible! They had the chance to visit the Grotta di Nettuno (the inspiration for the Count of Montecristo’s cave), enjoy some porceddu, and even snag a “Best Nonno” award! They toured Rome and, in the end, made it home safe and sound.

The Planning Fallacy Strikes Again

If you’ve ever made a plan and thought, “This time will be different; I’ve covered all the bases,” only to realize you absolutely have not, then you’ve experienced the planning fallacy.

Psychologist Daniel Kahneman, in his book Thinking, Fast and Slow, describes the planning fallacy as our tendency to underestimate how long tasks will take or how much effort they’ll require—because we’re too optimistic. We always think, “I’ve got this,” but in reality? Not so much.

In his book, Kahneman uses kitchen renovations as an example—projects that always take longer and cost more than expected. And if you’ve seen The Money Pit, you’ll understand exactly what he’s talking about. It’s both hilarious and a bit tragic.

Joel Explains AI: Can AI Solve the Planning Fallacy?

Speaking of plans, I bet you’ve heard this before: did you know AI can help you plan trips, manage projects, and even predict outcomes? Sounds perfect, right? Well, not so fast. AI might be amazing at crunching data, but it still can’t prevent human errors—like misplacing your passport in Pisa. That one’s still on us.

This got me thinking: SiMPL needs an AI section. Why? Well, while reminiscing about my college years, I remembered using Geoffrey Hinton’s groundbreaking work on neural networks as part of my AI curriculum. Yes, the same Hinton who won the Turing Award in 2018 and Nobel Prize in 2024, aka the “Godfather of AI.” His 1986 publication blew my mind back in the day.

Fast forward to now, and Hinton’s still pushing boundaries in AI. Alan Turing—the man behind the Turing Test—was the namesake of my university’s Computer Science building. Weird connection, I know, but it felt oddly personal.

So What Is AI, Anyway? (SiMPL Version)

Here’s the deal: AI (Artificial Intelligence) is about machines learning from data and applying that knowledge to perform tasks—without needing constant human supervision. Think of it as your super-smart assistant that anticipates your needs.

If you’re like me, growing up on movies like Terminator, Blade Runner, and Short Circuit, AI has always seemed like something from the future. Now? AI is everywhere. Whether it’s your phone predicting your next word or a chatbot helping you troubleshoot, we’re already using AI daily.

But AI is not the magic bullet some people think it is—at least, not yet.

The Parallels Between Electricity and AI

Let me tell you a story. Last year, for my 40th birthday, I didn’t plan anything too extravagant due to strikes in Panama. Restaurants were closing, so I told my wife, “Let’s just go to Bogotá and have a nice dinner there.” We called a few friends, and before I knew it, five of them were hopping on the trip. It turned out to be a blast.

On the way, we started talking about AI, and one of my friends expressed concern about AI replacing her job. I had just finished reading Power and Prediction—today’s book recommendation—and explained that AI isn’t there yet. The reality is, AI’s evolution is much more like the adoption of electricity than the internet.

Before electricity, industries ran on coal and gas. Factories, trains—everything was powered by steam. Coal was the industry’s backbone. Then along came electricity, but it didn’t replace coal overnight. It took around 60 years to adapt processes, build infrastructure, and gradually switch from steam to electric power.

A Lesson from History

Any new product or service introduced to the market follows a process that can be simplified into four key steps: Theory → Discovery → Application → Adoption (both early and widespread). It all starts with theory—someone observes something and theorizes its potential. Then comes discovery, when we figure out how to tap into that potential. Next is application, where the technology is put to use in real-world scenarios. Finally, adoption happens as this new technology gradually integrates into everyday life.

Take your kitchen renovation, for example. Imagine you just installed a gas stove, and then you find out that induction stoves are more efficient and similarly priced. Are you going to rip out your new kitchen setup just for the latest tech? Probably not—you’ll wait for the right moment.

The same thing happened with electricity. It took decades before people and industries fully adopted it. Did you know that before electricity, entire teams of people were hired just to light the gas lamps in cities like New York and London? Those jobs were eventually phased out when electric lighting became the norm.

Here’s a timeline to illustrate the parallels in the journey toward the adoption of electricity and AI. Stick with me—this is SiMPL’s way of showing where we are right now!:

See what I mean?, parallels are there!

The AI Paradox: It’s Here, But We’re Not There Yet

So yeah, AI is here. But like electricity, it’ll take time before we see its full potential. Remember those lamplighters in New York City? Just as they disappeared when electricity took over, some jobs will shift or vanish with AI.

But don’t worry, AI isn’t replacing us just yet. It’s evolving to help us make better decisions. The same way electricity didn’t immediately replace coal, AI is gradually integrating into our lives and industries.

SiMPL Book Recommendation: Power and Prediction

If you’re as fascinated by AI as I am, you’ll love this book. In Power and Prediction, authors Ajay Agrawal, Joshua Gans, and Avi Goldfarb explore the true economic impact of AI.

Their argument? AI isn’t being used to its full potential—yet. We’re still treating it like a fancy consultant instead of a tool that could reshape decision-making on a large scale. Their previous book, Prediction Machines, laid the groundwork for understanding AI’s role as a predictor of outcomes, and Power and Prediction takes it a step further by showing how AI can fundamentally alter the way companies operate.

They argue that AI’s real power lies in its ability to forecast and predict outcomes—turning it into a decision-making tool, not just an assistant. This is where the real transformation will happen. It’s not about fancy robots taking over the world (sorry, Terminator fans), but rather about AI helping us make smarter, faster decisions in everything from business to daily life.

If you’re serious about understanding where AI is headed, this book is a must-read. It’s no-nonsense and packed with real-world insights that go beyond the hype. Definitely worth the read!

My Takeaways

So there you have it— Joel Explains AI is officially a thing! Next week, we’ll dive deeper into AI (no hype, I promise). And remember, whether it’s planning a trip or predicting the future, AI can help—but only if we let it.

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