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12-designing-ux-for-ai-applications/README.md

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### Explainability
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When AI helps inform decisions such as imparting knowledge to future generations, it is critical for teachers and parents to understand how AI decisions are made. This is explainability - understanding how AI applications make decisions. Designing for explainability includes adding details of examples of what an AI application can do. For example, instead of "Get started with AI teacher", the system can use: "Summarize your notes for easier revision using AI."
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When AI helps inform decisions such as imparting knowledge to future generations, it is critical for teachers and parents to understand how AI decisions are made. This is explainability - understanding how AI applications make decisions. Designing for explainability includes adding details that highlight how AI arrived at the output. Audience must be aware that the output is generated by AI and not a human. For example, instead of saying "Start chatting with your tutor now" say "Use AI tutor that adapts to your needs and helps you learn at your pace."
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![an app landing page with clear illustration of explainability in AI applications](./images/explanability-in-ai.png?WT.mc_id=academic-105485-koreyst)
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