Here is the framework for a “Human Veto” process:

1. The “Blind Spot” Audit (Contextual Validation)

AI is excellent at processing the data it has, but it is “blind” to everything else.

• The Action: Before accepting an AI result, ask: “What is the AI not seeing?” * The Detail: This means looking for “off-page” factors like current office politics, a client’s recent emotional state, or sudden market shifts that haven’t hit the data sets yet. If the AI suggests a strategy based on last month’s data, the human checkpoint ensures it still makes sense this morning.

2. Cross-Verification via Non-Digital Sources (The Reality Check)

We have a habit of checking digital data with more digital data, which can create an echo chamber.

• The Action: Mandate a “triangulation” step using a human or physical source.
• The Detail: If an AI analysis says a project is on track, don’t just check the dashboard. Pick up the phone. A 30-second conversation with a project lead (a “non-digital source”) can reveal nuances—like team burnout or a vendor delay—that a spreadsheet will never capture.

3. The “Inversion” Test (Checking for Bias)

Algorithms often take the path of least resistance, which can lead to repetitive or biased outcomes.

• The Action: Purposefully argue against the AI’s recommendation.
• The Detail: If the AI flags a specific candidate as the “best fit,” the human checkpoint requires you to ask: “Why might this recommendation be wrong?” or “What would the ‘opposite’ of this recommendation look like?” This forces the professional to use their critical thinking muscles rather than just hitting “Approve.”

Don’t let the speed of AI outrun your common sense. Build your checkpoints today.