The EQ Blog

From deep dives into test strategy and emerging standards, to honest takes on where the industry is heading.

The COEQ ML Model testing Checklist

What Google tests — and what your organisation should too.

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Data Architecture, AI & Testing — how do they fit together?

Data Architecture provides the ground truth, AI model provides the intelligence and Testing provides the trust.

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The importance of testing for Bias

Inappropriate bias in AI systems can be tied to sensitive attributes like gender, race, ethnicity, sexual orientation, income level or age. Testing for Bias is essential to minimise real world impact on people's life.

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Concept Drift — in a constantly changing world

AI models don’t age well — monitoring and continously testing them against a changing world is essential to ensure no degradation of accuracy.

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Training, Validation & Test Data in Machine Learning

In machine learning, model quality doesn’t start with algorithms — it starts with how data is structured and used across the lifecycle.

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