刑事政策與犯罪研究論文集(25) 王正嘉，預測性警察活動在犯罪偵防運用與問題

近年來隨著人工智慧（AI）與大數據（big data）的發展，警察活動逐漸走向數據導向與預測性，逐漸形成預測性警察活動（predictive policing）的風潮。這項發展在美國結合到電腦軟體，開發出多樣以地點、人與時間的預測性警察活動程式，運用到犯罪偵防與偵查上，雖然成效卓著，但同時也引發諸多問題。
本文的主要目的即在探討此問題，從預測性警察活動的演進、運用，乃至於所衍生問題，做一個鳥瞰式的評估，並從美國學者的論述，檢討我國未來可能發生問題，找出一條解決之道。

In recent years, with the advancement of artificial intelligence (AI) and big data, policing activities have gradually evolved into data-driven and predictive practices, spurring the widespread trend of predictive policing. In the United States, this development has been integrated with computer software, resulting in the creation of various predictive policing programs based on location, individuals and time, which have been deployed for crime prevention and investigation. While these applications have yielded notable results, they have also sparked a range of concerns and issues.

The primary purpose of this paper is to explore this topic: to conduct a panoramic assessment of the evolution, application, and resulting problems of predictive policing, and to draw on the scholarly arguments of American researchers to examine potential future challenges in our country and identify a feasible solution path.

搜集汇总

背景与挑战

背景概述

该数据集是刑事政策与犯罪研究论文集的一部分，聚焦于预测性警察活动在犯罪侦查中的运用与问题。内容探讨了随着人工智能和大数据发展，预测性警察活动的兴起、成效及其引发的争议，并基于美国经验评估了我国未来可能面临的挑战和解决方案。