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A look into IBM’s AI ethics governance framework

IBM Big Data Hub

Yet while 79% of executives say AI ethics is important to their enterprise-wide AI approach , less than 25% have operationalized ethics governance principles. ” As AI use cases expand, broadly defined and abstract principles are proving to be insufficient by not providing clear processes for legal and ethical review.

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The Future of RegTech for AI Governance

IBM Big Data Hub

Central to putting these principles into practice is establishing the appropriate governance mechanisms for AI systems. AI governance will require an agile approach. AI governance will require an agile approach. Integrating RegTech into broader AI governance process.

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Automated governance and trustworthy AI

IBM Big Data Hub

Governments and regulatory bodies around the world are working to establish safety standards. The proposed rules aim to govern automated valuation models to protect borrowers. The announcement highlighted the crucial role of training data, and the terrible consequences of using data that “fails to represent American society.”.

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Judicial systems are turning to AI to help manage its vast quantities of data and expedite case resolution

IBM Big Data Hub

The demand for an automated solution arrives as Germany’s government has mandated that electronic file management be implemented by courts in all civil, administrative, social and criminal proceedings by 2026 as part of digitalization goals established by the European Union (EU).

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Data mesh 101: Domain-driven ownership and the Collibra Data Office

Collibra

Although the four pillars of data mesh are inextricably linked, this blog will focus on the first pillar: domain-driven ownership. The data mesh framework is social and technical. And repositioning the domain expert — as opposed to a centralized source — at the center of the data ecosystem is data mesh’s first principle. .

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IBM ranked #1 for AI lifecycle software market share in IDC report

IBM Big Data Hub

y/y based on the most recent data available. [1] IDC points out in its 2020 report: “Enterprises across industries and geographies are increasingly adopting AI/ML technologies to enable innovative use cases, improve customer experience, enhance employee experience, and accelerate innovation as part of their digital transformational journeys.

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10 reasons you should adopt reliability centered maintenance (RCM) today

IBM Big Data Hub

Unless critical risk factors, histories, material analogies and data on every failure are known, blind spots will stump the experts every time. With incomplete data, technicians can’t guarantee they’ll have the right tooling, inventory and associated materials to fix it.

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