在人工智能模型中,通过基于DAO的审议和投票进行民主治理,为包容性决策进行投票
Tanusree Sharma1, Yujin Potter2, Jongwon Park3
1College of Information Science and Technology, Pennsylvania State University, University Park, 16802, USA. tanusree.sharma@psu.edu.
Scientific reports
|March 3, 2026
概括
分散的自治组织 (DAO) 使得服务不足的群体能够塑造人工智能发展. 一项研究发现,将二次投票与平等的权力分配相结合,促进了更公平的AI决策,减少了AI模型中的偏见.
科学领域:
- 人工智能伦理学 人工智能伦理学
- 人与计算机的交互
- 社交计算社会计算
背景情况:
- 人工智能开发面临透明度问题,导致歧视和违反法规,不成比例地影响受服务不足的人群.
- 传统的社会科学方法不足以捕捉数字时代的用户需求,因为审议和达成共识的限制.
研究的目的:
- 开发和评估使用分散的自治组织 (DAO) 进行民主决策框架,让服务不足的群体就人工智能问题进行审议.
- 通过利益相关者的投入,在文本对图像人工智能系统中减少刻板印象偏见,特别是性别偏见.
主要方法:
- 使用2x2实验设计与随机在线实验 (n=177) 进行了一项案例研究.
- 来自全球南方的参与者和残疾人评估了治理配置,包括排名与二次聚合方案以及相等与20/80差异决策权力分配.
- 这项研究研究了治理机制如何影响人们对决策过程和人工智能模型规范的看法.
主要成果:
- 参与者集中在关键方面:用户控制图像生成,多个输出选项,以及人工智能生成图像的社会适当性和准确性.
- 二次偏好聚合 (赋权少数群体) 和平等的决策权分配的结合被认为是最公平和最民主的方法.
- 尽管背景不同,但参与者在关键的人工智能发展考虑方面达成了共识.
结论:
- 适当的治理机制对于民主决策在AI调整中至关重要.
- 基于DAO的框架可以有效地促进多样化和服务不足的人群在AI开发方面达成共识.
- 这些发现突出了通过整合以用户为中心的治理来实现更具包容性和公平的AI系统的途径.
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