특정인에 대한 범죄예측 시스템의 문제점과 개선방안 (Criminal Legal Issues and Improvements of Crime Prediction System for a specific person)

서지정보

· 발행기관 : 한국형사법학회
· 수록지 정보 : 형사법연구 / 33권 / 3호 / 241 ~ 266페이지
· 저자명 : 김병수

초록

다. 또한 대상범죄를 어느 범위까지 허용할 것인지 명확한 한계를 설정하기 어렵다. 범죄예측 시스템에 사용되는 인공지능 알고리즘은 불명투명성, 편향성, 부정확성의 문제가 있다. 인공지능 알고리즘의 불투명성은 부정확한 범죄예측으로 인한 피해나 그 책임의 소재를 찾는데 어려움을 줄 수 있다. 또한 인공지능 알고리즘이 지닌 잠재적 편향성과 부정확성 때문에 범죄예측이 공정하지 못하다는 비판을 받고 있다. 그리고 범죄예측 시스템은 시민들에게 새로운 통제수단이 되고 있다.
이러한 문제점을 해결하기 위해서는 먼저, 개인정보보호법 제15조 1항 1호에 의해 정보주체의 사전 동의를 반드시 받도록 하여야 할 것이다. 범죄예측을 위한 특정인에 대한 개인정보수집은 합목적적 범위 내에서 필요최소한에 그쳐야 할 것이고, 잘못된 결과가 발생할 경우를 회피 내지 개선할 수 있는 적당한 조치를 사전에 보장하여야 한다. 모든 개인정보수집은 감독기관의 적절한 감독을 받을 것을 보장하여야 한다. 알고리즘의 불투명성을 해결하는 방법으로는 정보 주체나 일반인을 대신하여 알고리즘의 적절성을 심사하고 감시하는 조직이나 기관을 설치하는 방법을 제시할 수 있다. 편향성 및 부정확성 해결방안으로 범죄예측 시스템을 통한 범죄예방의 효과성이 입증되고 공개되어야 하며 범죄예측시스템의 알고리즘의 정확성이 담보되어야 할 것이다. 범죄예측 시스템의 적용대상범죄와 대상자의 선정을 위해서는 재범의 중대성과 위험성이 중요한 판단 기준이 될 것이다. 범죄예측 시스템을 사용한 범죄예측은 살인, 강도, 강간, 방화와 같은 중대범죄여야 할 것이다. 범죄예측 시스템이 시민에 대한 통제장치로서 악용될 우려를 불식시키기 위해서는 범죄예측 시스템도 보안처분과 같이 비례성의 원칙에 의하여 대상자의 권리침해를 최소화하여야 한다. 범죄예측 시스템은 형벌이나 다른 보안처분에 의하여 목적을 달성할 수 없는 최후수단으로서 사용되어야 할 것이다. 대상자의 재범위험성을 근거로 개별적으로 사용하여야 한다. 범죄예측시스템은 행정처분에 의하여 행해져서는 안되고 법원의 사법심사에 의하여 부과되어야 한다.

영어초록

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.

참고자료

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