人工智能和随机恐怖主义——应该这样做吗?

Bart Kemper
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引用次数: 0

摘要

人工智能和机器学习技术的使用似乎是打击媒体激发的“孤狼攻击”所需的工具,通过实施“随机恐怖主义”的概念,针对有害的媒体影响。机器学习目前被用于整理社交媒体数据,以评估仇恨言论。人工智能目前被用于解释机器学习处理的数据和趋势,用于寻找犯罪网络等任务。问题变成了“随机恐怖主义能被证明吗?”以及“这应该被实施吗?”给某人贴上“恐怖分子”的标签,不管这个词的修饰词是什么,都会给这个人或组织贴上政府和社会严厉的、可能致命的反应的标签。刑事指控在伦理上不能随随便便,也不能没有充分的理由。由于在这个问题的各个方面都存在偏见的记录问题,使用这些计算工具来建立权威人士、政治家或其他人的媒体言论与“独狼”行为者的暴力之间的法律因果关系,不符合美国法理学的要求,也不符合人工智能可解释、透明和负责任的伦理原则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI and Stochastic Terrorism – Should it be done?
The use of Artificial Intelligence and Machine Learning technology may seem to be the tools needed to combat media-inspired “lone wolf attacks” by implementing the concept of “stochastic terrorism,” targeting harmful media influences. Machine Learning is in current use to sort through social media data to assess hate speech. Artificial Intelligence is in current use to interpret the data and trends processed by Machine Learning for tasks such as finding criminal networks. The question becomes “can stochastic terrorism be proven” and “should this be implemented.” Labeling someone as a “terrorist,” regardless of any modifier for the term, tags the person or group for severe, potentially lethal, response by the government and the community. Criminal accusation cannot ethically be done casually or without sufficient cause. Due to documented problems with bias in all aspects of the issue, using these computational tools to establish legal causation between media statements by pundits, politicians, or others and the violence of “lone wolf” actors would not meet the requirements of US jurisprudence or the ethical principles for Artificial Intelligence of being explainable, transparent, and responsible.
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