Letter to the editor: CENTRAL NEW YORK’S TECH INVESTMENTS NEED AN AI VERIFICATION SKILL

The September 21 release of $1.039 million for Syracuse University’s semiconductor testbed is another sign that Central New York is investing in advanced technology, while SUNY Poly in Utica is building an AI-enabled intelligent-manufacturing workforce. The missing piece is a simple verification skill: workers need to know what evidence to check before accepting an AI recommendation and when to escalate the decision. My letter gives employers and training programs a practical three-question standard that preserves speed on routine work while keeping consequential decisions under clear human ownership.

I am a behavioral scientist and the author of the peer-reviewed book, The Psychology of AI Adoption at Work: From Resistance to Results, published by Georgetown University Press https://press.georgetown.edu/Book/The-Psychology-of-AI-Adoption-at-Work My commentary has appeared regularly in The New York Times, The Guardian, the Toronto Star, and many others https://disasteravoidanceexperts.com/media

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CENTRAL NEW YORK’S TECH INVESTMENTS NEED AN AI VERIFICATION SKILL

Central New York’s technology investments are accelerating. The September 21 release of $1.039 million for Syracuse University’s semiconductor testbed will add specialized manufacturing equipment and laboratory infrastructure. In Utica, SUNY Poly’s Center for Intelligent Manufacturing is explicitly working to build an AI-enabled manufacturing workforce.

That combination should come with a simple verification habit. Before accepting a consequential AI recommendation, workers should ask: What evidence did I check? What would justify overriding the system? Who owns the decision if the stakes exceed my authority?

Routine drafting or brainstorming can move quickly. Decisions involving safety, quality, cybersecurity, significant money or customers deserve a named human owner and a documented check against trusted evidence.

Central New York is investing in the hardware, research and talent behind advanced manufacturing. Adding this human-handoff skill to training would help ensure that faster automation also produces more reliable decisions.

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Gleb Tsipursky, PhD, a behavioral scientist, CEO of Disaster Avoidance Experts, and author of The Psychology of AI Adoption at Work: From Resistance to Results (Georgetown University Press, 2026). https://disasteravoidanceexperts.com/aibook