Navigating the Complexities of AI Governance: Introducing TAIMScore™

TAIMScore™ is the Trusted AI Model Score — a 20-control AI governance framework built by HISPI Project Cerebellum. In this episode of The AI Governance Briefing, Dr. Tuboise Floyd, PhD breaks down how TAIMScore™ turns AI accountability into something you can measure, score, and prove.Four governance domains. Twenty essential controls. Mapped against NIST AI RMF, the EU AI Act, HIPAA, PCI DSS, SOC 2, EU GDPR, and the White House AI Executive Order. If your institution needs a blueprint for AI governance that survives regulatory scrutiny, this is the starting point.AI is already deployed. The institutions that survive will be the ones that can prove they govern it.──────────────────────────────────────WHAT YOU WILL LEARN──────────────────────────────────────∙ Why AI incidents make governance non-negotiable∙ The Project Cerebellum mission: AI should cause no harm∙ How the four TAIM domains — GOVERN, MAP, MEASURE, MANAGE — work as an accountability cycle∙ The 20 TAIMScore™ controls every AI-deploying organization must address∙ How to crosswalk your AI posture against global regulatory frameworks∙ Why the AI kill switch is essential governance — not optional──────────────────────────────────────CHAPTERS──────────────────────────────────────0:00 Welcome and Introduction0:28 Real Risks of AI1:18 Real Generative AI Incidents2:13 Project Cerebellum: AI Should Cause No Harm2:48 Vision and Mission3:33 The Four TAIM Domains5:01 GOVERN — AI Risk Training (Govern 2.2)5:31 GOVERN — Supply Chain Policy (Govern 6.1)6:01 MAP — Establishing Context (Map 1.2)6:26 MAP — System Requirements (Map 1.6)6:55 MAP — Third Party Risk (Map 4.1)7:13 MAP — Impact Documentation (Map 5.1)7:33 MEASURE — Human Evaluations (Measure 2.2)7:51 MEASURE — Reliability (Measure 2.5)8:07 MEASURE — Safety Risk (Measure 2.6)8:23 MEASURE — Explainability (Measure 2.9)8:37 MEASURE — Privacy Risk (Measure 2.10)8:51 MEASURE — Fairness and Bias (Measure 2.11)9:09 MEASURE — Risk Tracking (Measure 3.1)9:23 MEASURE — Feedback Loops (Measure 3.3)9:41 MEASURE — Performance Data (Measure 4.3)9:57 MANAGE — Resource Allocation (Manage 2.1)10:19 MANAGE — Unknown Risks (Manage 2.3)10:35 MANAGE — The Kill Switch (Manage 2.4)10:55 MANAGE — Post-Deployment Monitoring (Manage 4.1)11:11 MANAGE — Incident Communications (Manage 4.3)11:29 TAIMScore™: The Payoff11:52 Framework Crosswalks — HIPAA, SOC 2, EU AI Act13:51 Closing and How to Get Involved──────────────────────────────────────TAIMSCORE™ ASSESSOR WORKSHOP──────────────────────────────────────Virtual. Instructor-led. One day. Six CPEs. Third Friday of every month.🔗 humansignal.io/taimscore_assessor_workshop──────────────────────────────────────FAILURE FILES™ — TAIMScore™ APPLIED──────────────────────────────────────See TAIMScore™ applied to real institutional failures:🔗 humansignal.io/failure-files──────────────────────────────────────RESOURCES──────────────────────────────────────Project Cerebellum — projectcerebellum.comHISPI — hispi.orgHISPI LinkedIn Group — linkedin.com/groups/6624427Email — [email protected]──────────────────────────────────────ABOUT HISPI PROJECT CEREBELLUM──────────────────────────────────────Project Cerebellum is the AI Governance Think Tank of HISPI — the Holistic Information Security Practitioner Institute. The Trusted AI Model (TAIM) is a flagship framework of 72 controls across four domains that harmonize leading AI governance standards into a practical scoring system. TAIMScore™ was created by Taiye Lambo, Founder and Chief Artificial Intelligence Officer of HISPI.──────────────────────────────────────ABOUT THE HOST──────────────────────────────────────Dr. Tuboise Floyd, PhD is the Founder and Chief Sensemaking Officer of Human Signal, Editor in Chief of The AI Governance Record, and a TAIMScore™ Certified Assessor. He holds a PhD from Auburn University and is a member of the HISPI Advocacy & Education Working Group (Project Cerebellum).──────────────────────────────────────CONNECT──────────────────────────────────────Website: humansignal.ioPodcast: theaigovernancebriefing.com/podcastLinkedIn: linkedin.com/in/drtuboisefloydEmail: [email protected] the machine. Or be the resource it consumes.#TAIMScore #AIGovernance #AIAccountability #HISPI #ProjectCerebellum #NISTAIRMF #EUAIAct #AICompliance #FailureFiles #TrustedAIModel #DrTuboiseFloyd #HumanSignal #TheAIGovernanceBriefing #BuilderClass #AIRiskCompanies mentioned in this episode:hispiHolistic Information Security Practitioner InstituteProject CerebellumMicrosoftOpenAIISOIECHIPAAPCIDSSSoC2EU AI ActEU GDPRWhite House AI Executive OrderTakeaways:The podcast episode emphasizes the necessity for organizations to establish robust frameworks for AI governance, particularly through the TAIM model.The TAIM framework is designed to ensure that AI deployments are safe, secure, responsible, and trustworthy, addressing potential risks proactively.A significant focus of the episode is on the real-world examples of AI risks, illustrating the importance of governance in mitigating these risks.Effective AI governance requires continuous monitoring and assessment, ensuring that systems remain compliant with evolving regulatory standards.The TAIM score provides organizations with a concrete evaluation of their AI governance posture against relevant regulatory frameworks.The importance of interdisciplinary collaboration in AI governance is highlighted, underscoring the necessity of diverse perspectives in risk assessment.This podcast uses the following third-party services for analysis: OP3 - https://op3.dev/privacy