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测量算法注入的社会
Claudia Wagner1,2,3, Markus Strohmaier4,5,6, Alexandra Olteanu7,8
1GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany. claudia.wagner@gesis.org.
Nature
|July 1, 2021
概括
需要新的社会理论来理解算法注入的社会. 开发可靠,可审计和公正的测量模型需要透明和参与的方法来确保质量和减轻损害.
科学领域:
- 社会科学
- 计算社会科学
- 技术社会学
背景情况:
- 传统的社会科学理论和测量模型并没有为算法的普遍影响而设计.
- "算法注入的社会"的兴起为理解人类行为和社会结构带来了新的挑战.
- 现有的框架难以解释由算法和人类行动共同塑造的社会现实.
研究的目的:
- 应对算法注入社会所带来的挑战,特别是关于测量质量和理论限制.
- 倡导新社会理论的发展, 整合算法系统的影响.
- 在计算社会科学中提出可信,可审计和公正的测量模型的要求.
主要方法:
- 在算法影响的背景下对现有社会科学方法的概念分析.
- 论证新的理论框架和数据集成方法的必要性.
- 建议以透明和参与的方式开发测量模型,强调质量保证和危害识别.
主要成果:
- 测量质量不足,测量错误的复杂后果以及当前社会理论的局限性是主要挑战.
- 认为新的社会理论对于理解和分析算法注入的社会至关重要.
- 强调需要可靠,可审计和公正的测量模型,以及透明和参与的开发流程.
结论:
- 计算社会科学家必须在算法注入的社会中重新思考测量策略.
- 未来的研究应该专注于开发强大的方法来将数据整合到理论构建中.
- 在测量开发中优先考虑透明度,参与和道德考虑对于推进社会科学研究至关重要.
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