Autor: Nermin Sefić
The ability to explain a model's recommendation is often worth more than marginal accuracy gains. A commentary by Nermin Sefić.
In a business context, the ability to explain why a model made a given recommendation is often more valuable than marginally better statistical accuracy.
When choosing between two models of similar performance, the one that can explain its recommendation in understandable language usually delivers greater real value than one that is marginally more accurate but completely opaque.
The ability to explain allows the accountable person to review the logic before making the final decision, rather than accepting the model's recommendation without any real means of verification.
A model that cannot explain why it recommended something forces an organisation into blind trust — and blind trust in a system that occasionally errs means the mistake surfaces only after it has already caused damage.
An explainable model also enables regulatory compliance: when an auditor or regulator asks for justification, the organisation needs more than 'the system calculated it that way'.
This commentary is part of the GNK ASG Intelligence Desk system and is informational in nature.
An explainable model also supports regulatory compliance: when an auditor asks for justification, an organisation needs more than 'the system calculated it that way' — it needs a traceable reason.
This preference for explainability over marginal accuracy is not a rejection of performance — it is a recognition that a system's practical value depends on whether people actually trust and use its output, and trust is built through understanding, not through a performance benchmark that most users never see and could not evaluate even if they did.
A model that cannot explain why it recommended something forces an organisation into blind trust — and blind trust in a system that occasionally errs means the mistake surfaces only after it has already caused damage.
An explainable model also supports regulatory compliance: when an auditor asks for justification, an organisation needs more than 'the system calculated it that way'.
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Cjelovit tekst i izvor: https://gnk-asg.hr/en/commentary/an-ai-that-explains-its-decision-beats-a-more-accurate-one/
Autor i urednička odgovornost: Nermin Sefić. Izdavač: GNK ASG d.o.o..
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