국민대 교수, 공공 연구개발 평가를 위한 AI 프레임워크 개발 - 네이트

The research paper, titled "Bridging the maturity-expectation gap: Generative AI in strategic decision-making for public R&D interim review," was published in the international journal Technovation. It addresses the limitations of current public R&D interim reviews, which often depend on the subjective judgment of experts. These traditional methods frequently face criticism for lacking consistency and being prone to evaluation bias. To resolve these issues, the team proposed the Maturity-Expectation Gap (MEG) framework. This model analyzes the difference between the actual maturity of generative AI technology and the performance levels expected by stakeholders. By combining survey data from experts with machine learning-based literature analysis, the researchers quantified how perceptions of AI vary across different groups. "Generative AI has the potential to increase efficiency and consistency in the public R&D evaluation process," said Professor Kim Do-hyung. "However, if the gap between expectations and actual technical maturity is not managed, it can lead to distrust and resistance during implementation. The MEG framework proposed in this study can be used to diagnose these gaps and establish phased introduction strategies." The project was a collaboration between lead author Professor Kim Do-hyung, co-author Professor Kang Song-hee of the Tech University of Korea, and corresponding author Professor Hong Ah-reum of Kyung Hee University. The researchers expect the framework to contribute to more consistent and objective R&D management in the future. (Reference Information) Journal/Source: Technovation Title: Bridging the maturity-expectation gap: Generative AI in strategic decision-making for public R&D interim review Link/DOI: https://doi.org/10.1016/j.technovation.2024.103110 Park Sae-jin Reporter [email protected] ★관련기사 - Copyright ⓒ [아주경제 ajunews.com] 무단전재 배포금지 -