Quick practice: Pick one repetitive task in your company. Keep it in mind as your example while reading.

Two Sides of the AI Coin: Safe vs. Risky

Action tip: Place your selected task in the appropriate column. Surprised by where it landed? Adjust expectations before automating.

When AI Gets It Wrong

Some errors can’t be undone with a single click:

• Irreversible damage: Denying a credit to someone who qualifies, misinterpreting medical data.

• Black box problem: No one can explain why the algorithm failed.

• Bad press and fines: Negative headlines, user loss, regulatory sanctions.

• Hidden costs: Fixing a poorly launched system is far more expensive than pre-checking.

The 3‑2‑1 Rule Before Delegating to AI

Ask yourself:

1. Pain of failure: Will a mistake cause serious damage or just mild inconvenience?
2. Easy to undo: Can it be reversed easily like a “Ctrl + Z”?
3. Clear explanation: Can we track how the AI made its decision?

If all three answers are reassuring, AI can run unsupervised. If any create doubt, human oversight is a must.

Practice: Apply the 3-2-1 rule to your chosen task. Does it need human review?

Good AI Use: Everyday Examples

Supermarkets and bananas
A retail chain predicts how many bananas will sell tomorrow. If it gets it wrong, they offer discounts and avoid waste. Mistake = low cost, easy fix.

→ Use historical data to forecast inventory and track savings.

Photo-sorting app
An app tags “selfies,” “pets,” and “receipts.” If it mistakes a dog for a cat, the user corrects it. No harm done.

→ Try a prototype to classify internal images and test accuracy.

Poor AI Use (or Use with Caution)

Medical treatments without review
A hospital lets AI assign treatments with no human oversight. A mistake here can be fatal.

→ Health professionals should always have final say. AI suggests, not decides.

Automated layoffs
A company fires people based on a program tagging “low productivity” without considering context or health.

→ Use AI to detect warning signs—but always decide with human review.

How to Stay Safe

• Human pilot for critical decisions.

• Continuous monitoring: Complaints ↑ → review the model.

• Transparency: Tell users when AI is involved and how to appeal.

• Update your data: Old models = inaccurate results.

• Focus on value: Automate the tedious, preserve the human.

Three-Level Supervision Architecture

Level 1 – Assistant
AI suggests; human decides.
Example: Email draft generator.
→ Track time saved and acceptance rate.

Level 2 – Copilot
AI acts but alerts when confidence is low.
Example: Ticket routing with threshold.
→ Set a minimum threshold and trigger alerts.

Level 3 – Autopilot
AI operates solo; alerts only for anomalies.

Example: Auto-scaling cloud servers.

AI boosts speed for repetitive tasks. But when lives, rights, or reputations are at stake, human empathy remains irreplaceable. With the 3-2-1 rule, tiered supervision, and a clear dashboard, the robot serves humanity—not the other way around.

Mitch Skolnik

Community Manager
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