人工智能风险辩论中的信念更新:探索对抗性合作的局限性
Josh Rosenberg1, Ezra Karger1,2, Zach Jacobs1
1Forecasting Research Institute, Claymont, Delaware, USA.
概括
人工智能 (AI) 专家认为存在的威胁比预测者更大. 尽管观点不同,但两组都同意到2030年为人工智能风险制定预警指标,风险感知在更长的时间框架内趋同.
科学领域:
- 人工智能安全与存在风险研究研究
- 专家诱导和预测和预测.
- 跨学科合作 跨学科合作
背景情况:
- 人工智能 (AI) 最近的进步引发了人们对人类存在潜在威胁的担忧.
- 专家们对人工智能相关灾难的概率和时间表存在不同的观点.
- 了解这些不同的观点对于有效的风险评估和缓解策略至关重要.
研究的目的:
- 通过对抗性合作,调查专家和预测者对AI相关存在风险的看法.
- 确定可能显著改变长期风险评估的早期预警指标 (cruxes).
- 探索风险感知如何在不同的时间范围内演变.
主要方法:
- 人工智能学科专家和具有相反观点的专家预测者之间的敌对合作.
- 激励参与的重点是尊重的视角采用和论点分享.
- 开发和预先注册到2100年人工智能灾难的预警指标问题 (关键点).
主要成果:
- 人工智能专家表示,与专家预测者相比,人工智能所带来的威胁更高.
- 两组都没有显著改变其长期风险估计,但已经确定了2030年解决方案的预注册关键点.
- 在2100年以后的时间框架中,风险感知差异有所减少,到2500年汇聚到30%-40%的风险.
结论:
- 专家和预测小组对近期人工智能存在风险持有不同的观点,但在风险评估中确定了共同的关键问题.
- 人工智能相关灾难的风险感知在更长的时间尺度上显示了趋同.
- 未来的研究应该通过各种专家样本和替代领域验证这些发现.
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