论文标题
根据《人工智能法》，法医图像分析中的合规性挑战
Compliance Challenges in Forensic Image Analysis Under the Artificial Intelligence Act
论文作者
论文摘要
在法医图像分析的许多应用中，如今的机器学习方法可以实现最新的结果。但是，对它们的可靠性和不透明的担忧引发了一个问题，即是否可以在刑事调查中使用此类方法。到目前为止，几乎没有讨论这个法律合规性问题，这也是因为没有明确定义机器学习方法的法律法规。为此，欧盟委员会最近提出了《人工智能法》（AI）法案，这是一个可信赖使用AI的监管框架。根据AI法案草案，允许在执法部门中使用的高风险AI系统，但要遵守强制性要求。在本文中，我们回顾了为什么在法医图像分析中使用机器学习为高风险。然后，我们总结了高风险AI系统的强制性要求，并根据两个法医应用，车牌识别和深度假检测讨论这些要求。本文的目的是提高人们对即将到来的法律要求的认识，并指出未来研究的途径。
In many applications of forensic image analysis, state-of-the-art results are nowadays achieved with machine learning methods. However, concerns about their reliability and opaqueness raise the question whether such methods can be used in criminal investigations. So far, this question of legal compliance has hardly been discussed, also because legal regulations for machine learning methods were not defined explicitly. To this end, the European Commission recently proposed the artificial intelligence (AI) act, a regulatory framework for the trustworthy use of AI. Under the draft AI act, high-risk AI systems for use in law enforcement are permitted but subject to compliance with mandatory requirements. In this paper, we review why the use of machine learning in forensic image analysis is classified as high-risk. We then summarize the mandatory requirements for high-risk AI systems and discuss these requirements in light of two forensic applications, license plate recognition and deep fake detection. The goal of this paper is to raise awareness of the upcoming legal requirements and to point out avenues for future research.
