Monitaur Blog

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A delay in the EU AI Act is not a delay in AI risk

The EU AI Act delay isn't a reprieve. Here's how insurers should use the 16-month runway to build defensible AI governance before December 2027.

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How does bias happen, technically?

How does data bias happen, technically? Despite the media narrative, ML models are incredibly unintelligent, and here’s how they end up biased.

What is the NIST artificial intelligence (AI) risk management framework?

NIST Artificial Intelligence Risk Management Framework (RMF) is being crafted to “better manage risks to individuals, organizations, and society associated with artificial intelligence (AI).” The official framework is expected to be released in early 2023.

AI governance as part of the data science lifecycle

With higher-risk models, data scientists face responsibility to not only follow best practices for building responsible and ethical AI, but also develop common understanding with non-technical stakeholders to support overall business needs. There's a case to made for incorporating AI governance into data science lifecycle to enable developers in their work while also providing assurance to stakeholders.

A brief introduction to AI governance: A model developer's guide

Building and deploying strong, robust AI models is complex work on its own. Here is what technical organizations can do to make AI governance easier.

Bias in AI & ML – Fixing the data will never be enough

Bias in machine learning and artificial intelligence is a human problem that results from human choices. The solution is human oversight of machine decisions.