Explainable AI plays a central role in validating model behavior. Using established explainability techniques, the study examines which financial variables drive fraud predictions. The results show a ...

Traditional rule-based systems, once sufficient for detecting simple patterns of fraud, have been overwhelmed by the scale, ...

Large language models (LLMs) such as GPT and Llama are driving exceptional innovations in AI, but research aimed at improving ...

Explainable AI (XAI) is a field of AI that focusses on developing techniques to make AI models more understandable to humans. Explainable AI (XAI) is a field of AI that focusses on developing ...

Machine learning and artificial intelligence are helping automate an ever-increasing array of tasks, with ever-increasing accuracy. They are supported by the growing volume of data used to feed them, ...

Explainable AI helps companies identify the factors and criteria algorithms use to reach decisions. (Photo by Jens Büttner/picture alliance via Getty Images) Artificial intelligence is biased. Human ...

Companies are generating an increasing volume of data at a CAGR of 61%. As a result, enterprises have been transitioning toward a data-driven decision model to build a competitive advantage. The ...

Johanna Pingel is product marketing manager, MathWorks. AI is transforming engineering in nearly every industry and application area. With that, comes requirements for highly accurate AI models.

While machine learning and deep learning models often produce good classifications and predictions, they are almost never perfect. Models almost always have some percentage of false positive and false ...

The first consideration when discussing transparency in AI should be data, the fuel that powers the algorithms. Companies should disclose where and how they got the data they used to fuel their AI ...