当前位置:首页 > 报告详情

避免 AI 治理雷区.pdf

上传人: le****ng 编号:616677 2025-03-07 26页 2.83MB

1、Avoiding the AI Governance MinefieldsSayantan ChakladerHead of Data&AI Governance,Sony EuropeWelcome and introductionWouter MertensSr Director,Product Management at CollibraOpportunityRiskLaws/regulationsCustomers/clientsInternalEmployee productivityCustomer experience Scale&velocityWhere are you no

2、w?Not speaking the same languageManual workflowsRoles not clearly definedDont always trust our dataLimited visibilityGovernance is importantCreates a shared languageBrings people together to collaborateMakes data useableReduces data risksDecision rights&accountability frameworkData GovernanceThree a

3、pproaches to AI GovernanceThe data-centric approach is essential for ensuring effective AI use-case development and risk mitigationHelp data,AI,risk&legal teamsdeliver trusted AI by providing easy access to reliable data and implementing appropriate controls across the AI use-case lifecycle.Data-cen

4、tricCollaboration between AI,data and legal teamsGoal:AI use cases safely in productionHow:Easy use of reliable data,effective collaboration between stakeholdersHelp legal and privacy teams to ensure compliance with laws®ulations by fully documenting and auditing the use of AI.Compliance-centricL

5、ead by legal teamsGoal:compliance&risk managementHow:documentation&attestationHelp AI and data teams to implement AI use-cases effectively by preparing,developing,running and monitoring AI modelsModel ops-centricCollaboration between AI and data teamsGoal:Implement&operate AI use-casesHow:Platform t

6、hat supports the development and running of AI modelsHow do you start?AI use casesProcessPeopleTechnologyChanging hearts and mindsetPrioritize governance mindsetFoster data literacy with training on AI and risksHire the right talentAI Governance is a team sport!AI Governance CouncilCDAOCISOLegalPriv

word格式文档无特别注明外均可编辑修改,预览文件经过压缩,下载原文更清晰!
三个皮匠报告文库所有资源均是客户上传分享,仅供网友学习交流,未经上传用户书面授权,请勿作商用。
本文主要探讨了AI治理的重要性及其在不同领域的应用。文章提出了三种AI治理方法:数据中心方法、合规中心方法和模型操作中心方法。数据治理是确保有效AI应用开发和风险缓解的关键。它通过提供可靠数据和实施适当控制,帮助AI、数据和法务团队共同协作,确保AI应用案例安全进入生产环节。合规中心方法由法务团队主导,重点是实现合规和风险管理。模型操作中心方法强调AI和数据团队之间的协作,目标是实施和运营AI应用案例。文章还介绍了AI治理框架的实施步骤,包括识别和理解数据、文档化模型和结果、定义用例、验证和监控AI用例等。此外,文章还提到了AI治理中的关键角色和数据治理的重要性。最后,作者呼吁大家积极参与AI治理,共同打造一个安全、可靠的AI环境。
"如何确保AI的合规与风险管理?" "如何通过数据治理实现AI的有效使用?" "AI治理如何改变团队之间的协作方式?"
客服
商务合作
小程序
服务号
折叠