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Home Eastern Asia South Korea

Kookmin Univ. study maps gap between AI hype and bureaucratic reality

by Asia Today Team
March 18, 2026
in South Korea
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(EDITORIAL from Korea JoongAng Daily on June 23)

Carmakers intensify rivalry in SDVs


Kookmin Univ. study maps gap between AI hype and bureaucratic reality

Professor Kim Do-hyoung of Kookmin College / Courtesy of Kookmin College

As governments world wide transfer to combine generative synthetic intelligence (AI) into the equipment of public decision-making, a brand new examine means that confidence within the know-how could also be lagging behind its promise.

A analysis group led by professor Kim Do-hyung of Kookmin College proposed a framework to measure what it describes as a important disconnect: the hole between the precise maturity of AI techniques and the expectations positioned on them by stakeholders. The examine, revealed within the peer-reviewed journal Technovation, argues that this divide may assist decide whether or not the know-how advances or falters in high-stakes public analysis and improvement packages.

Searching for a extra systematic strategy, Kim and his co-authors devised what they name the “Maturity-Expectation Hole,” or MEG, framework. The mannequin attracts on survey responses from skilled evaluators and pairs them with a machine studying evaluation of educational analysis, aiming to measure each how prepared the know-how is and the way a lot is predicted of it.

Their findings level to a notable divergence.

Totally different teams — together with evaluators, policymakers and researchers — typically maintain sharply divergent views of how succesful generative AI techniques are at the moment. The place expectations outstrip perceived maturity, the examine discovered, confidence in adopting the know-how tends to erode.

“The bigger the hole, the decrease the willingness to depend on AI in decision-making,” Kim mentioned. “With out managing that hole, implementation might set off skepticism relatively than confidence.”

The analysis additionally factors to uneven prospects for adoption.

Some areas of analysis — significantly these centered on structured information — seem extra readily suited to generative AI. Others, particularly people who rely upon nuanced qualitative judgment, might require additional advances within the know-how or better institutional readiness earlier than they are often reliably put to make use of, in accordance with the examine.

This text was revealed with the help of a generative AI system and edited by The Korea Instances.



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