Trustworthy XAI and Application
원문 초록
Artificial Intelligence (AI) is an important part of our everyday lives. We use it in self-driving cars and smartphone assistants. People often call it a "black box" because its complex systems, especially deep neural networks, are hard to understand. This complexity raises concerns about accountability, bias, and fairness, even though AI can be quite accurate. Explainable Artificial Intelligence (XAI) is important for building trust. It helps ensure that AI systems work reliably and ethically. This article looks at XAI and its three main parts: transparency, explainability, and trustworthiness. We will discuss why these components matter in real-life situations. We will also review recent studies that show how XAI is used in different fields. Ultimately, gaining trust in AI systems is crucial for their successful use in society.
함께 살펴볼 논문
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Communicating Smartly in the Molecular Domain: Neural Networks in the Internet of Bio-Nano Things
midr: Learning from Black-Box Models by Maximum Interpretation Decomposition
Do Protein Transformers Have Biological Intelligence?
TIMING: Temporality-Aware Integrated Gradients for Time Series Explanation
Addressing the Scarcity of Benchmarks for Graph XAI
Heart2Mind: Human-Centered Contestable Psychiatric Disorder Diagnosis System using Wearable ECG Monitors
토론
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