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法律法规可以利用普遍的道德框架来推动极端主义的态度
Rosamunde C Hendricks1,2, Helena Gil-Buitrago1,2, Clara Pretus1,2
1Department of Psychobiology and Methodology of Health Sciences, Universitat Autònoma de Barcelona, Barcelona, Spain.
Annals of the New York Academy of Sciences
|February 12, 2026
概括
生成型人工智能可以使社会两极分化. 大型语言模型 (LLM) 产生的调用道德价值观的信息增加了极端主义的态度和正当暴力的意愿,特别是当被视为神圣的价值观时.
科学领域:
- 社会科学 社会科学 社会科学
- 政治科学 政治科学是指政治学.
- 计算社会科学 计算社会科学
背景情况:
- 社交媒体影响力活动,通常由生成性人工智能 (AI) 提供动力,被怀疑操纵公众论并培养极端主义.
- 这些影响行动改变公众论和促进极端主义态度的确切机制尚不清楚.
研究的目的:
- 调查围绕普遍道德原则构成的简短,大语言模型 (LLM) 产生的论点是否会影响极端政治态度.
- 了解道德问题和神圣价值观在LLM产生的内容对极端主义的影响中介作用.
主要方法:
- 两项研究对美国951名民主党人和共和党人的联合样本进行了研究.
- 参与者接触到LLM产生的论点,这些论点呼吁普遍的道德问题 (福利,权利,公平).
- 统计分析检查了道德框架,将政治立场视为神圣的价值观和极端主义态度之间的关系.
主要成果:
- 发现普遍的道德关注 (福利,权利,公平) 预测了人们将政治立场视为神圣的价值观,这反过来解释了极端主义的态度.
- 由LLM产生的论点强调个人权利和公平性,显著增加了参与者愿意为自己的政治立场而采取极端行动 (战斗,死亡,证明暴力是正当的).
- 这种对极端行动的意愿增加部分归因于人们对政治立场的高度认知,认为政治立场是一种绝对的或神圣的价值.
结论:
- 由LLM产生的信息,特别是当它呼吁道德问题时,有可能使社会两极分化并加剧极端主义态度.
- 利用人工智能的社交媒体影响力活动可以将道德框架武器化,以动员个人以极端措施捍卫政治立场.
- 这些发现凸显了进一步研究减轻人工智能驱动的社交媒体内容的两极分化影响的必要性.
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