재량처분에 대한 사법심사기준 정량화 방안의 모색

Abstract

In previous cases related to judicial review of discretionary actions in administrative law, the focus has been on determining whether there was an abuse or deviation of discretionary power, resulting in insufficient assessment of individual reasons and explanation. Identifying specific reasons for judicial review of discretionary actions is necessary, as it influences the claims and evidentiary directions of the parties involved in administrative litigation and affects administrative authorities' actions. This study explores the possibility of quantitatively extracting individual judgment elements through attempts to concretize and typify the reasons for judicial review. As a premise for finding a quantitative method for judicial review criteria, Chapter 2 of this study collected and analyzed cases related to discretionary actions by building a database and utilized ChatGPT in the process. Although ChatGPT could not directly derive analytical results, it was confirmed that it could perform tasks that coding experts previously conducted and offer assistance in exploring analysis methods through question-and-answer interactions. Based on this analysis experience, Chapter 3 researched methods to schematize the principle of proportionality, a general judgment criterion for discretionary dispositions. The study expressed and coded the comparative magnitude of public and private interests using decision trees and considered ways to fill in each of the specific elements encompassed within public and private interests. We proposed how these criteria could be utilized in future judicial review outcome prediction systems and in arguments and evidence in actual trials. Quantifying the judgment factors by analyzing the judicial review criteria for discretionary dispositions of administrative agencies means filling in the reasons for judgments at the abstract level to a level that the general public can understand, thereby increasing the predictability of the court's judgments, enhancing trust in administrative precedents, and creating a meaningful link that can lead to reasonable discretionary dispositions and ultimately contribute to the advancement of the rights and interests of the people. In subsequent studies, artificial intelligence is used in the process of subdividing public and private factors and each subdivided element is quantified, so that anyone can understand the difficult discretion of the courts. Additionally, it is hoped that courts can deliver more rational and explainable decisions by being aware of the increasingly fine-grained aspects of judgment.