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通往负责任的 AI 之路:新兴的最佳实践和监管观点.pdf

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1、P A N E L D I S C U S S I O N The Road to Accountable AI:Emerging Best Practices and the Regulatory View Bojana BellamyPresident,Centre for Information Policy Leadership(CIPL)Kate CharletGlobal Head of Privacy,Safety&Security Policy,GoogleProf.Dieter KugelmannPresident,Authority for Data Protection

2、and the Freedom of Information,Rhineland-Palatinate,GermanyDr.Mark LeiserAssitant Professor,Vrije Universiteit,Amsterdam Law&Technology InstituteACCOUNTABLE AI IN PRACTICEPANEL DISCUSSION THE ROAD TO ACCOUNTABLE AI Building Accountable AI Programs:Mapping Emerging Practices to the CIPL Accountabilit

3、y Framework CIPL Paper 2024Provides concrete empirical evidence from accountable AI programs being deployed on the groundShares best practices and lessons learned from leading global organizationsBuilds global consensus on accountability in AI governancePromotes accountability as an effective strate

4、gy for the responsible development and deployment of AIInforms the global debate on AI regulation,governance,oversight,and enforcementAccountable AI Programs Mapped to CIPL Accountability FrameworkAccountabilityEffective compliance,business sustainability,protection for individualsRisk AssessmentPol

5、icies and ProceduresTransparencyTraining and AwarenessMonitoring and VerificationResponse and EnforcementLeadership and OversightImplementing protective,mitigating measures proportional to the likelihood and severity of the risks of harm while enabling the benefits of AI technologiesCreating effecti

6、ve governance structures,appointing appropriate personnel to oversee them,and promoting awareness and support across all functionsEstablishing internal,written AI policies and procedures that operationalize ethical principles,standards,and legal requirements into concrete actions and controlsProvidi

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本文主要讨论了迈向可解释和负责任的AI之路:新兴的最佳实践和监管视角。Bojana Bellamy、Kate Charlet、Prof. Dieter Kugelmann和Dr. Mark Leiser等专家探讨了如何建立可解释的AI程序以及如何将AI监管与业务实践相结合。 文章指出,AI变革与AI责任是企业的首要任务和业务 imperative。监管机构和政策制定者的指导对于组织实施新兴标准和法规是受欢迎的。多学科和多样化的团队是建立和实施可解释AI治理程序的基础。在AI的生命周期中,采用风险评估和风险管理策略至关重要。 CIPL报告的十大发现揭示了负责任的组织在AI转型、风险评估、政策制定、透明度、培训和意识、监控和验证、响应和执行等方面的最佳实践。这些发现包括:1)AI治理是长期可持续和具有竞争力的业务投资;2)企业高层对负责任的AI程序至关重要;3)监管机构和政策制定者的指导对于组织实施新兴标准和法规是受欢迎的;4)基于风险、与技术无关的AI治理方法是最有效和适当的;5)围绕AI相关的通用术语的趋同是紧迫和必要的;6)组织正在适应和更新其治理框架,以解决新的问题和风险,包括生成式AI(GenAI)引起的问题;7)多学科和多样化的团队是建立和实施负责任的AI治理程序的基础;8)在负责任的AI治理和同行之间建立共识非常有价值;9)AI的开发和部署是一个持续的旅程和迭代的过程;10)将AI程序映射到CIPL问责元素。 总之,文章强调了在AI治理中实施可解释性和负责任性的重要性,并提出了一系列最佳实践,以帮助组织在AI领域取得成功。
实践与监管视角" "如何构建可解释的AI程序?" 如何平衡?"
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