Was ist XAI (Explainable AI)

Definition

Explainable AI (XAI) refers to a set of machine learning methods and techniques designed to make the internal decision-making processes and outcomes of complex AI systems (often referred to as 'black boxes') understandable and transparent to human users.

Explanation

In highly regulated B2B sectors like finance, healthcare, and HR, XAI is a non-negotiable prerequisite for deploying AI in practice. When algorithms make decisions on credit approvals, diagnoses, or candidate selections, businesses must be able to comprehensively explain the underlying criteria for compliance reasons. XAI methods enable developers and users to understand which data features had the greatest impact on a specific model prediction. This minimizes the risk of undetected systematic errors (bias) and significantly increases user trust in the software. Ultimately, in the SaaS sector, the explainability of an AI solution often determines whether a technology gains the necessary market acceptance and regulatory approval.