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KIROI - Artificial Intelligence Return on Invest: The AI strategy for decision-makers and managers

KIROI - Artificial Intelligence Return on Invest: The AI strategy for decision-makers and managers

Start » AI Explainability 360 (Glossary)
9 May 2025

AI Explainability 360 (Glossary)

4.5
(1312)

AI Explainability 360 is at home in the fields of Artificial Intelligence, Big Data and Smart Data, as well as automation. The term stands for an open software platform that helps to make Artificial Intelligence (AI) decisions transparent and understandable.

Often, AI is a „black box“: it makes decisions, but people don't understand why. This is precisely where AI Explainability 360 comes in. It offers tools and methods to uncover the reasons behind AI decisions. This allows developers and companies to understand how the system works and to better evaluate the results. This builds trust and makes the use of AI fairer and safer – especially where decisions have an impact on people, for example, in credit or job applications.

For example, a bank uses AI to make credit decisions. Thanks to AI Explainability 360, it can explain to its customers why a specific application was rejected or approved, for instance, because income or debt level played a role. This way, the platform promotes fairness, transparency, and legal certainty when using artificial intelligence.

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transruption: The digital toolbox for
the digital winners of today and tomorrow

Start » AI Explainability 360 (Glossary)
9 May 2025

AI Explainability 360 (Glossary)

4.5
(1312)

AI Explainability 360 is at home in the fields of Artificial Intelligence, Big Data and Smart Data, as well as automation. The term stands for an open software platform that helps to make Artificial Intelligence (AI) decisions transparent and understandable.

Often, AI is a „black box“: it makes decisions, but people don't understand why. This is precisely where AI Explainability 360 comes in. It offers tools and methods to uncover the reasons behind AI decisions. This allows developers and companies to understand how the system works and to better evaluate the results. This builds trust and makes the use of AI fairer and safer – especially where decisions have an impact on people, for example, in credit or job applications.

For example, a bank uses AI to make credit decisions. Thanks to AI Explainability 360, it can explain to its customers why a specific application was rejected or approved, for instance, because income or debt level played a role. This way, the platform promotes fairness, transparency, and legal certainty when using artificial intelligence.

How useful was this post?

Click on a star to rate it!

Average rating 4.5 / 5. Vote count: 1312

No votes so far! Be the first to rate this post.

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Discover transparency in AI decisions with AI Explainability 360 – learn more now and ensure fairness!

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