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 their explainability and reliability is constrained by massive resource ...

The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

Trust only grows when companies can track their AI processes, fully explain the methods employed to arrive at outputs, and ...

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 ...

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 (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 ...

Thredd CTO Edwin Poot explains how explainable AI and real-time, context-aware decisioning are reshaping digital commerce and ...

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 ...

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 ...