Explainable AI (XAI)

AI systems designed with transparency to allow humans to understand how they reach their conclusions.

What is Explainable AI (XAI)?

Explainable AI makes artificial intelligence decision-making processes transparent and interpretable. In AI automation, XAI provides insights into how models arrive at their conclusions, which is crucial for building trust and meeting regulatory requirements.

XAI capabilities help users understand and validate their automation workflows, ensuring that automated decisions can be explained and justified to stakeholders, regulators, or end-users.

Why is Explainable AI (XAI) important?

Understanding how AI makes decisions is crucial for businesses, especially in regulated industries or when making important decisions. For companies using Lleverage, XAI enables them to build transparent automation workflows that can be audited and validated. This transparency helps build trust with stakeholders, comply with regulations, and identify potential biases or issues in automated processes.

How you can use
Explainable AI (XAI)
with Lleverage

A financial institution uses Lleverage to automate loan approval processes. Their workflow includes XAI components that provide clear explanations for each decision, showing which factors influenced the approval or rejection. This transparency helps comply with regulatory requirements and allows loan officers to understand and validate the automated decisions.

Explainable AI (XAI)
FAQs

Everything you want to know about

Explainable AI (XAI)

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What are the key components of an explainable AI system?

Key components include feature importance rankings, decision path visualization, and natural language explanations of model decisions.

More references for
Explainable AI (XAI)

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