Criminal Responsibility of Artificial Intelligence Committing Deepfake Crimes in Indonesia

Asri Gresmelian Eurike Hailtik, Wiwik Afifah
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Abstract

The development of technology that continues to evolve has given birth to an innovation called artificial intelligence or artificial intelligence which is usually called "AI". The development of AI has sparked an algorithm called deepfake technology. Deepfakes use machine learning and neural network technology, which are methods in AI that teach computers to process data in a way inspired by the human brain. This study aims to determine the regulation of AI as perpetrators of deepfake crimes and to determine the criminal responsibility of AI who commit criminal acts in Indonesia. The research method used is normative legal research using a statutory approach (statue approach), conceptual approach (conceptual approach), and comparative approach (comparative approach). AI is classified as an electronic system and electronic agent which when viewed to the characteristics of AI that has a match with the definition of electronic systems and electronic agents. If AI commits deepfake crimes, it can violate several articles in Law No. 19 of 2016 concerning Electronic Information and Transactions. In California, legislation has been passed to address deepfakes related to pornography, fraud, and defamation: Calif AB-602 and Calif AB-730. There are three AI criminal liability models that commit criminal acts, namely Perpetration-via another model (PVM), Natural-Probable-Consequence Liability Model (NPCLM), and Direct Liability Model (DLM). In Indonesia, AI has not been recognized as a legal subject so that if you commit a criminal act, the person who must be responsible is the creator of AI or AI users
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人工智能在印度尼西亚实施深度伪造犯罪的刑事责任
技术的不断发展催生了一种创新,即人工智能或人工智慧,通常被称为 "AI"。人工智能的发展引发了一种名为深度伪造技术的算法。Deepfakes 使用机器学习和神经网络技术,这是人工智能中的一种方法,它教会计算机以一种受人脑启发的方式处理数据。本研究旨在确定对作为深度伪造犯罪实施者的人工智能的监管,并确定在印度尼西亚实施犯罪行为的人工智能的刑事责任。采用的研究方法是规范性法律研究,使用法定方法(法规方法)、概念方法(概念方法)和比较方法(比较方法)。人工智能被归类为电子系统和电子代理人,从人工智能的特征来看,这与电子系统和电子代理人的定义相吻合。如果人工智能实施深度伪造犯罪,则可能违反 2016 年第 19 号法律《电子信息和交易法》中的若干条款。加利福尼亚州已通过立法来解决与色情、欺诈和诽谤有关的深度伪造问题:加州 AB-602 法案和加州 AB-730 法案。实施犯罪行为的人工智能刑事责任模式有三种,即通过他人实施模式(PVM)、自然-可能-后果责任模式(NPCLM)和直接责任模式(DLM)。在印度尼西亚,人工智能尚未被承认为法律主体,因此,如果您实施了犯罪行为,必须承担责任的人是人工智能的创造者或人工智能的使用者。
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