Editor,
Meghalaya’s move to hire AI Trainers for Shillong Polytechnic, ITI Rynjah and ITI Tura is a useful investment in local capability. The most durable training will go beyond mastering prompts and producing faster answers. The harder skill is judgment: knowing when an output deserves trust and when it needs correction.
Highland Post recently highlighted Meghalaya students who succeeded at Technothlon through logical reasoning, analytical thinking, creativity and problem-solving. Those are exactly the capabilities AI education should protect.
Every AI course should require learners to verify important outputs against source material, identify uncertainty, explain when a human should override the system, and recover when the tool produces a plausible but wrong result. Trainers should test those behaviors with realistic exercises rather than rewarding speed alone.
Meghalaya can build a stronger AI workforce by measuring what learners can do after training: fewer errors, better decisions, faster completion of appropriate tasks, and clear escalation when the tool reaches its limits.
That combination turns tool familiarity into durable competence.
Gleb Tsipursky
Author of The Psychology of AI Adoption at Work: From Resistance to Results (Georgetown University Press, 2026)
