Remove Document Remove Measurement Remove Risk Management
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Where CIOs should place their 2025 AI bets

CIO Business Intelligence

Deloittes State of Generative AI in the Enterprise reports nearly 70% have moved 30% or fewer of their gen AI experiments into production, and 41% of organizations have struggled to define and measure the impacts of their gen AI efforts.

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Managing machine learning in the enterprise: Lessons from banking and health care

O'Reilly on Data

After the 2008 financial crisis, the Federal Reserve issued a new set of guidelines governing models— SR 11-7 : Guidance on Model Risk Management. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk. Model risk management. AI projects in financial services and health care.

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From project to product: Architecting the future of enterprise technology

CIO Business Intelligence

Documentation and diagrams transform abstract discussions into something tangible. By articulating fitness functions automated tests tied to specific quality attributes like reliability, security or performance teams can visualize and measure system qualities that align with business goals.

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Sweat the small stuff: Data protection in the age of AI

CIO Business Intelligence

As concerns about AI security, risk, and compliance continue to escalate, practical solutions remain elusive. as AI adoption and risk increases, its time to understand why sweating the small and not-so-small stuff matters and where we go from here. training image recognition models to misidentify objects).

Risk 105
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AI and cybersecurity: A double-edged sword

CIO Business Intelligence

As a secondary measure, we are now evaluating a few deepfake detection tools that can be integrated into our business productivity apps, in particular for Zoom or Teams, to continuously detect deepfakes. Companies like CrowdStrike have documented that their AI-driven systems can detect threats in under one second.

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Why you should care about debugging machine learning models

O'Reilly on Data

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. The study of security in ML is a growing field—and a growing problem, as we documented in a recent Future of Privacy Forum report. [8]. That’s where model debugging comes in. Residual analysis.

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How Birmingham’s $48M Oracle ERP project turned into an epic failure

CIO Business Intelligence

When this review finally occurred and identified key issues, its findings were ignored, highlighting a systemic failure in the councils risk management approach, the report added. There are multiple reports including one from a manager at BCC highlighting the discrepancies at the Council, way back in June 2023.