특정인에 대한 범죄예측 시스템의 문제점과 개선방안

Artificial intelligence based on machine learning and deep learning technology finds correlations between hidden information in the vast data of big data and statistically predicts what will happen in the future. Using AI, there are high-level predictions in many fields of society. This high predictive power of AI is also being used in the field of crime prevention. In developed countries, crime prediction systems using big data and artificial intelligence have been introduced intensively in large cities with high crime rates. And they are producing tangible effects such as a decrease in the crime rate. The methods of such a crime prediction system can be broadly divided into 3 categories: ① crime prediction, ② criminal prediction, ③ crime victim prediction. Because of the limited scope of collection of sensitive personal information and protection of personal privacy, crime prediction, which predicts the time and place of a crime based on the crime risk by region and location, is mainly used rather than predicting criminals and victims. In this situation, the purpose of this study is to raise the problems that may appear in the crime prediction system for a specific person and to find a quick response method. Therefore, in this study, the problem of infringement of individual constitutional and legal rights that may occur when the crime prediction system is used for a specific person, the problem of opacity, inaccuracy and bias of the algorithm of the crime prediction system, and the problem of the crime prediction system as a new control means. We will review the potential problems and seek solutions to them. Since the crime prediction system for a specific person deals with the personal information of a specific person, it inevitably violates the basic rights such as privacy and freedom and the right to self-determination of personal information guaranteed by the Constitution. When targeting a specific person, the issue of equity with the general public may be raised. In addition, it is difficult to set clear limits on the extent to which target crimes are permitted. Artificial intelligence algorithms used in crime prediction systems have problems of opacity, bias, and inaccuracy. The opacity of artificial intelligence algorithms can make it difficult to find the cause of damage or responsibility due to inaccurate crime prediction. In addition, due to the potential bias and inaccuracy of artificial intelligence algorithms, crime prediction is being criticized for being unfair. And the crime prediction system is becoming a new means of control for citizens. In order to solve this problem, it is necessary to first obtain the prior consent of the information subject according to Article 15 (1) 1 of the Personal Information Protection Act. The collection of personal information for a specific person for crime prediction should be limited to the minimum necessary within the scope of the purpose of the crime, and appropriate measures to avoid or improve the occurrence of erroneous results should be ensured in advance. It should be ensured that all personal information collection is subject to appropriate supervision by the supervisory authority. As a method of solving the opacity of the algorithm, it can be suggested to establish an organization or institution that examines and monitors the adequacy of the algorithm on behalf of the data subject or the general public. As a solution to bias and inaccuracy, the effectiveness of crime prevention through the crime prediction system should be proven and disclosed, and the accuracy of the crime prediction system algorithm should be guaranteed. The seriousness and risk of recidivism will be an important criterion for the selection of target crimes and targets for the crime prediction system. Crime prediction using the crime prediction system should be serious crimes such as murder, robbery, rape, and arson. In order to dispel the fear that the crime prediction system will be abused as a control device for citizens, the crime prediction system should also minimize the infringement of the subject's rights according to the principle of proportionality like the security disposition. The crime prediction system should be used as a last resort that cannot achieve its purpose through punishment or other security measures. It should be used individually based on the subject's risk of recidivism. The crime prediction system should not be implemented by administrative disposition, but should be imposed by judicial review of the court.