Transparency and explainability are only way organizations can trust autonomous AI.
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Improving AI models' ability to explain their predictions
In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output. Concept ...
The promise of artificial intelligence in credit scoring is undeniable. By analyzing vast, non-traditional datasets from ...
Is claude a crook? The AI company Anthropic has made a rigorous effort to build a large language model with positive human values. The $183 billion company’s flagship product is Claude, and much of ...
Researchers at Meta FAIR and the University of Edinburgh have developed a new technique that can predict the correctness of a large language model's (LLM) reasoning and even intervene to fix its ...
ORONO, Maine — From interpreting a medical scan to sorting family photos, artificial intelligence (AI) makes snap judgments that users often trust blindly. Chaofan Chen, assistant professor of ...
AI black box models lack transparency, making investment decisions unclear. White box models are slower but clarify their decision-making processes. Investors should verify AI outputs to align with ...
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