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一个对抗性风险分析框架用于软件发布决策支持
Refik Soyer1, Fabrizio Ruggeri2, David Rios Insua3
1Department of Decision Sciences, George Washington University, Washington, District of Columbia, USA.
本研究引入了一个新的AI风险分析框架,以帮助开发人员决定何时发布人工智能 (AI) 产品,考虑可靠性,成本和竞争.
科学领域:
- 软件工程 软件工程 软件工程
- 人工智能风险管理 人工智能风险管理
- 决策分析 决策分析
背景情况:
- 严格的质量约束和竞争激烈的市场需要谨慎的AI系统发布决策.
- 人工智能系统的可靠性,安全性,故障分析,成本和竞争对手的行为使发布时间变得复杂.
- 当前的人工智能风险管理框架需要强大的方法来做出市场发布决策.
研究的目的:
- 为AI系统发布决策提出一个新的一般对抗风险分析框架.
- 支持人工智能开发人员应对进入市场的复杂性.
- 在不确定性下提供一个结构化的方法来评估AI产品发布.
主要方法:
- 开发一个多代理对抗风险分析框架.
- 在框架内,将生产者和买家作为不同的代理类型进行建模.
- 用实例说明框架的实施情况.
主要成果:
- 拟议的框架为人工智能开发人员提供了一种评估发布时间的方法.
- 该框架考虑了生产者和买家之间的敌对互动.
- 讨论了多个生产者和买家的扩展,提高了适用性.
结论:
- 新的对抗风险分析框架为AI发布决策提供了宝贵的工具.
- 解决不确定性和竞争动态对于成功部署人工智能产品至关重要.
- 该框架可以扩展到涉及多个利益相关方的更复杂的市场场景.
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