Explainable AI (XAI) is a term from the fields of Artificial Intelligence, Big Data and Smart Data, as well as Cybercrime and Cybersecurity. It describes artificial intelligence systems whose decisions are understandable to humans. The goal of Explainable AI is to create transparency and strengthen user trust.
AI decisions often seem like a „black box“ – they provide a result, but nobody understands how it was reached. Explainable AI changes this by showing the rules or data an AI acts upon. This is especially important when decisions are made about people, for example, in credit scoring or diagnosing illnesses.
A clear example: A bank uses AI software to assess loan applications. Thanks to Explainable AI, the employee can see which factors (such as income, credit report, and profession) contributed to the rejection or approval. This allows the bank to explain its decision and advise applicants better.
Explainable AI is therefore an important building block for the safe and responsible use of artificial intelligence in everyday life.
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