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Auditability Of Recommendation Decisions

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The property of a recommendation system that lets engineers and stakeholders answer 'why was this item picked?'. Nicolò Rebughini highlights it as a critical non-ML advantage of the amplifier scoring engine: every multiplication is stored, parameters have names, and top-three runners-up are kept as metadata. Proper machine learning would have sacrificed this auditability — a frequent stakeholder question with Cometeer's coffee picks.

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Auditability Of Recommendation Decisions concept
Auditability is the main trade-off driving the non-ML design.

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