Microwaving the Future: How We Misuse AI (and What To Do About It)

When my son was nine years old, he left his brand-new airsoft gun outside overnight during a winter snowstorm. The next morning, he found it frozen solid to the ground. Trying to solve the problem himself, he placed it in the microwave.

He knew that by pressing a few buttons, the microwave could melt the ice. He didn’t understand how it would affect metal springs, plastic, and batteries.

The sparks, smoke, and stench of misusing tech.

There was smoke. There were sparks. And of course, a smell that lingered for days.

This story might seem like a cute parenting anecdote (and it is), but it’s also a surprisingly good analogy for how many people are approaching AI right now.

They understand part of the equation: AI is powerful, and it can solve problems. But without a better understanding of how it works and what it does and doesn’t do well, we can unknowingly create a different set of smoke, sparks, and smells.

We risk valuable data, costly mistakes, and fail to capitalize on the true benefits of this powerful tool.

Did You Know? Most generative AI tools don’t retrieve facts—they predict the most statistically likely next word based on patterns in training data. That means confident-sounding outputs can still be wildly inaccurate. Treat outputs as drafts, not truth.

Beyond the Hype: What AI Actually Is

There’s a reason AI feels like a microwave: mysterious, slightly magical, and incredibly powerful. You press a button and something useful happens. But that mystery is exactly the problem.

AI (especially modern generative AI) is not a sentient being, a genie, or even a smart assistant. It’s a complex statistical engine—often built on transformer architecture—trained to recognize patterns and generate outputs based on enormous amounts of data.

When we ask it to make decisions, summarize strategies, or brainstorm creative ideas, we often mistake it for an infinitely wise oracle. But we’re really using an unproven machine that has no understanding of context, no emotional intelligence, and no judgment. It doesn’t know you. It doesn’t even know itself.

The Real Problem Isn’t the Tool—It’s the Assumption

Consider these real-life examples of how this microwave mistake is playing out across industries.

• A small business plugs AI into its customer service inbox, only to find it responding too literally—or too liberally—to nuanced customer concerns.

• A school district rolls out an AI tutoring tool and discovers that while it can generate answers, it often does so without verifying accuracy or aligning to the curriculum.

• A nonprofit automates grant writing and ends up with polished, but content-thin proposals that miss emotional resonance and contextual impact.

• A major tech media site deploys AI to draft articles and discovers—after publishing—that many are riddled with inaccuracies, causing public retractions and damaging credibility.

In each of these cases, the problem wasn’t AI. It was the user's assumption that pressing a few buttons would melt the ice—without understanding how the technology works.

These tools don’t fail because they’re broken. They fail because they’re often treated as a toy, as magic, and with very little thought given to what the technology actually is and how it can be leveraged safely.

Where to Start

So how do we avoid our own microwave moment?

We start with understanding—not just which AI tools exist, but how they function under the hood. What kinds of problems are they designed to solve? Where do they struggle? What patterns are they recognizing, and from what kind of data? That’s the foundation for any responsible and effective use.

From there, we can create informed strategies, set realistic expectations, and put guardrails in place that keep humans thoughtfully involved in the process. AI becomes most powerful when we don’t just delegate—but collaborate—with it.

Organizations with strong AI literacy and human-in-the-loop processes are far better positioned to use these technologies creatively, ethically, and effectively. Those are key areas of focus for all Acord.AI workshops: demystifying the tech, understanding its limitations, and developing the skills to leverage its strengths. 

The future of AI isn’t just about cool tools. It’s about intentional strategy, clear understanding, and thoughtful integration. That can only begin when we stop treating it like magic—and start treating it like the powerful but limited system it is.

Just like a nine-year-old with a frozen airsoft gun.

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If you are interested in learning the technology behind the scenes, check out “Intro to AI: Demystifying the Tech That’s Changing the World” or any of our upcoming workshops and discover how to strategically and safely leverage the latest AI technologies.