LEADER 00910nam0-2200325---450 001 990009399030403321 005 20210215105758.0 010 $a9780123749802 035 $a000939903 035 $aFED01000939903 035 $a(Aleph)000939903FED01 035 $a000939903 100 $a20110715d2009----km-y0itay50------ba 101 0 $aeng 102 $aGB 105 $aa-------001yy 200 1 $aDesk encyclopedia of microbiology$feditor-in-chief Moselio Schaechter 205 $a2nd ed. 210 $aOxford$cAcademic Press$dc2009 215 $aXV, 1259 p.$cill.$d28 cm 610 0 $aMicrobiologia$aEnciclopedie 676 $a579$v23$zita 702 1$aSchaechter,$bMoselio 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990009399030403321 952 $a60 579 SCHM 2009$b12756$fFAGBC 959 $aFAGBC 996 $aDesk encyclopedia of microbiology$9765170 997 $aUNINA LEADER 05032nam 22005175 450 001 9910919826103321 005 20250504110025.0 010 $a9798868809835 024 7 $a10.1007/979-8-8688-0983-5 035 $a(MiAaPQ)EBC31862459 035 $a(Au-PeEL)EBL31862459 035 $a(CKB)37093687400041 035 $a(DE-He213)979-8-8688-0983-5 035 $a(CaSebORM)9798868809835 035 $a(OCoLC)1484817296 035 $a(OCoLC-P)1484817296 035 $a(EXLCZ)9937093687400041 100 $a20241228d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPrinciples of AI Governance and Model Risk Management $eMaster the Techniques for Ethical and Transparent AI Systems /$fby James Sayles 205 $a1st ed. 2024. 210 1$aBerkeley, CA :$cApress :$cImprint: Apress,$d2024. 215 $a1 online resource (491 pages) 300 $aIncludes index. 311 08$a9798868809828 327 $aChapter 1 - The Current State of AI Governance and Model Risk Management -- Chapter 2 - AI Strategy and AI Governance Interoperability -- Chapter 3 - How to Sound Like an AI Governance Guru -- Chapter 4 - Designing a Well-Governed AI Lifecycle Model -- Chapter 5 - AI Governance for Trustworthy AI ? The Governances in AI Governance -- Chapter 6 - Designing Your AI Governance Framework -- Chapter 7 - AI Governance and Oversight Model -- Chapter 8 - Managing and Addressing AI Compliance -- Chapter 9 - Integrating AI Governance with Enterprise Governance Risk and Compliance -- Chapter 10 - AI Policy Management and Enforcement -- Chapter 11 - Maintaining Privacy within your AI Governance Model -- Chapter 12 - Human Oversight of AI Systems -- Chapter 13 - The Power of Stakeholder Engagement in AI Governance -- Chapter 14 - Considering the Environmental Impacts of AI Systems -- Chapter 15 - Developing the Protocols for Rapid Response in Case of an AI-Related Crisis -- Chapter 16 - Capacity Building for AI Actors -- Chapter 17 - Intellectual Property Rights with AI Technologies -- Chapter 18 - Auditing AI Systems -- Chapter 19 - AI Model Inventory and Facts -- Chapter 20 - Ramesh -- Chapter 21 ? AI Governance and SDLC Integration -- Chapter 22: AI Through the Lens of Non-Technical Business Leaders: Embracing AI with Caution -- Chapter 23: Navigating the AI Frontier with this Sales Bible: Sales and Marketing Strategies for AI Governance and Risk Management Solutions. 330 $aNavigate the complex landscape of Artificial Intelligence (AI) governance and model risk management using a holistic approach encompassing people, processes, and technology. This book provides practical guidance, oversight structure and centers of excellence, and actionable insights for organizations seeking to harness the power of AI responsibly, ethically, and transparently. By addressing the technical, ethical, and societal dimensions of AI governance, organizations will be empowered to build trustworthy AI systems that benefit both their bottom line and the broader community. Featuring successful mitigating controls based on proven use cases, the book underscores the importance of aligning AI strategy with AI governance, striking a balance between AI innovation, risk mitigation as well as broader business goals. You?ll receive pointers for designing a well-governed AI development lifecycle, emphasizing transparency, accountability, and continuous monitoring throughout the AI development lifecycle. This book highlights the importance of collaboration between stakeholders, i.e., boards of directors, CxOs, corporate counsel, compliance officers, audit executives, data scientists, developers, validators, etc. You?ll gain practical advice on addressing the challenges related to the ownership of AI-generated content and models, stressing the need for legal frameworks and international collaboration. You?ll also learn the importance of auditing AI systems, developing protocols for rapid response in case of AI-related crises, and building capacity for AI actors through education. Principles of AI Governance and Model Risk Management demonstrates its value-added uniqueness by detailing a strategy to ensure a cohesive approach to managing AI-related risks, global compliance, policy, privacy, and AI-human collaboration and oversight. 606 $aArtificial intelligence$xManagement 606 $aArtificial intelligence$xMoral and ethical aspects 606 $aArtificial intelligence$xRisk management 615 0$aArtificial intelligence$xManagement. 615 0$aArtificial intelligence$xMoral and ethical aspects. 615 0$aArtificial intelligence$xRisk management. 676 $a658.155 700 $aSayles$b James$01781309 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910919826103321 996 $aPrinciples of AI Governance and Model Risk Management$94306060 997 $aUNINA