I discuss here three important roles where machine intelligence, brain and behaviour studies together may facilitate criminal law. First, brain imaging analysis and predictive modelling using brain and behaviour data enable mental illness, insanity, and behaviour examination during legal investigations. Second, psychological, psychiatric, and behavioural studies supported by machine learning algorithms may help detect lies, biases, and visits to crime scenes. Third, brain decoding is beginning to uncover one's thoughts and intentions based on functional brain imaging data. Having dispensed with achievements and promises, I examine concerns regarding the accuracy, reliability, and explainability of the brain- and behaviour-based assessments in criminal law, as well as questions regarding data possession, security, privacy, and ethics. Taken together, brain and behaviour decoding in legal exploration and decision-making at present is promising but primitive. The derived evidence is limited and should not be used to generate definitive conclusions, although it can be potentially used in addition, or parallel, to existing evidence. Finally, I suggest that there needs to be (more precise) definitions and regulations regarding when and when not brain and behaviour data can be used in a predictive manner in legal cases.
翻译:我在这里讨论三个重要角色,即机器情报、大脑和行为研究可以共同促进刑法。首先,利用大脑和行为数据进行脑成像分析和预测建模,以便在法律调查期间进行精神疾病、精神失常和行为检查。第二,由机器学习算法支持的心理、精神和行为研究可能有助于发现谎言、偏见和对犯罪现场的访问。第三,大脑解码正在开始根据功能性大脑成像数据发现一个人的想法和意图。在免除了成就和承诺之后,我研究了对刑法中大脑和行为评估的准确性、可靠性和可解释性的关切,以及数据拥有、安全、隐私和道德等问题。在目前的法律探索和决策中将大脑和行为解码在一起是很有希望的,但原始的。所产生的证据是有限的,不应用来得出确定的结论,尽管可以对现有证据加以补充或平行使用。最后,我建议,在法律案件中,需要(更精确的)定义和条例,说明何时和何时可以将大脑和行为数据用于预测性的方式。