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Bookmark or Share- 什么是可解释 AI (XAI)？| IBM比较 ai 和 xai “常规”ai 和可解释 ai 之间究竟有什么区别？xai 采用了特定的技术和方法，以确保可以跟踪和解释在 ml 过程中所做出的每个决策。
- What is explainable AI? - IBMExplainable AI is one of the key requirements for implementing responsible AI, a methodology for the large-scale implementation of AI methods in real organizations with fairness, model explainability and accountability.³ To help adopt AI responsibly, organizations need to embed ethical principles into AI applications and processes by building ...
- What Is Black Box AI and How Does It Work? | IBMWhite box AI, also called explainable AI (XAI) or glass box AI, is the opposite of black box AI. It is an AI system with transparent inner workings. Users understand how the AI takes in data, processes it and arrives at a conclusion.
- ¿Qué es la IA explicable (XAI)? | IBM³ "Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI (Inteligencia artificial explicable (XAI): conceptos, taxonomías, oportunidades y desafíos hacia la IA responsable)" (enlace externo a ibm.com), ScienceDirect, junio de 2020.
- Apa yang dimaksud dengan Explainable AI? - IBMExplainable AI digunakan untuk mendeskripsikan model AI, perkiraan dampak, dan potensi biasnya. Hal ini membantu mengkarakterisasi keakuratan model, keadilan, transparansi, dan hasil dalam pengambilan keputusan yang didukung AI.
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