The year is 1940. The British government is losing the war. Nazi U-boats are destroying Allied supply ships. Every plan is being intercepted and decoded by Germany’s “unbreakable” machine: Enigma.

So the UK assembles a team of brilliant minds at Bletchley Park to break it. Alan Turing builds a machine that becomes the prototype for modern computing.

But the movie (The Imitation Game) doesn’t end there. What most people forget: The machine didn’t win the war alone. A team of people operated it. Fed it data. Decoded the encryptions. Chose what intel to act on—and what to bury.

The machine assisted. But humans made the decisions. Humans bore the weight.

Fast-forward to today. The machine is AI. And once again, we forget it operates on its own.

The Real Problem → Invisible Labor, Risky Assumptions

We like to think of AI as clean, fast, and efficient—algorithms crunching data in the cloud while we sip coffee and marvel at the outputs.

But beneath that polished interface, there’s a human workforce. (Here’s a great article I read on this, worth the read).

Thousands of contractors—many highly educated—are quietly training and correcting AI models every day.

They’re not engineers. They’re “raters” and content moderators. They grade chatbot responses. Rewrite hallucinated facts. Flag offensive content.

They’re the underpaid minds behind the artificial one.

This isn’t just a labor issue—it’s a business risk.

These workers are overworked, underpaid, and easily discarded. One contractor helping train Google’s Gemini was fired hours after filing a whistleblower complaint. Entire teams have been wiped out for trying to correct the issues.

The companies benefiting—Google, Meta, OpenAI—often deflect responsibility, citing outsourcing contracts and legal loopholes.

But here’s the rub:

These are the people training the tools your business uses to write copy, filter content, answer customers, and power decision-making.

If the labor under the hood cracks, so does the output.

So What?

Start asking better questions about AI:

• Who trained this model?
• What data was used—and how was it labeled?
• Were human raters involved? Were they trained or incentivized properly?
• Is this tool ethically sourced and reasonably maintained?

This isn’t about going full tinfoil hat or being overly humanitarian. It’s about leadership and clarity.

In an age of invisible labor and opaque tech, transparency is power.

The Takeaway

If you’re a leader, strategist, or marketer— don’t outsource your ethics to the algorithm.

AI is here to stay. But your edge won’t come from what it can do. It will come from what you understand about how it was built— And how responsibly you use it.

Let’s not repeat the Enigma mistake. Let’s not worship the machine and forget the human hands behind it.

See you next Saturday. Stay clear. Stay sharp. Stay human.