充分利用参与式的意义制造和公众与科学接触,以实现人工智能民主化
Collin Lucken1, Tim Elmo Feiten2
1University of Cincinnati, 2800 Clifton Ave, Cincinnati, OH, 45221, United States.
Studies in history and philosophy of science
|March 20, 2025
概括
这项研究将公众参与与科学 (PEWS) 和激进的体现认知科学 (RECS) 联系起来,展示了参与式的创造意义如何增强科学沟通,并为民主化提供AI发展信息.
科学领域:
- 认知科学 认知科学
- 科学传播科学传播
- 人工智能伦理学 人工智能伦理学
背景情况:
- 批判性地检查了科学传播中的"赤字模型"和认知科学中的"信息处理范式".
- 在公众与科学接触 (PEWS) 中被拒绝的观点和激进的体现认知科学 (RECS) 之间有相似之处.
研究的目的:
- 探索富有成效的对话,并在PEWS和RECS之间建立牢固的联系.
- 引入并激发人们对"参与性认知策略"的需求.
- 展示这些策略在民主化人工智能开发方面的潜力.
主要方法:
- 对PEWS和RECS原则进行比较分析.
- 参与性意义化的概念框架开发.
- 在大规模人工智能系统开发中应用案例研究.
主要成果:
- PEWS 和 RECS 有着一致的积极愿景,特别是在参与式的创造意义方面.
- 积极的,对话式的参与科学传播得到了积极的认知科学的验证.
- 社区参与科学和技术提供了对技术文化系统的洞察力.
结论:
- 参与性认知策略对于有效的科学交流和人工智能开发至关重要.
- 整合PEWS和RECS可以带来更民主和更具包容性的AI计划.
- 该研究在概念上为"民主化人工智能"的辩论做出了贡献.
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