In an era where financial decisions are increasingly driven by invisible algorithms, trust has become the most valuabl ...

AI systems now operate on a very large scale. Modern deep learning models contain billions of parameters and are trained on large datasets. Therefore, they produce strong accuracy. However, their ...

When users ask leading questions, AI systems reshape their responses to align with existing biases rather than challenge them ...

Leading expert JM García-Maceiras launches a guide for global financial institutions to bridge the gap between ...

The new OLMoTrace tool builds on the Allen Institute for AI’s open-source initiatives. (Ai2 Image) The Allen Institute for AI (Ai2) released a new tool that links AI-generated text to training data, ...

The new AI disclosure framework aims to help marketers use generative AI responsibly without over-labeling every touchpoint or eroding consumer trust. The post IAB launches AI transparency and ...

Explainable AI (XAI) exists to close this gap. It is not just a trend or an afterthought; XAI is an essential product capability required for responsibly scaling AI. Without it, AI remains a powerful ...

As Artificial Intelligence (AI) becomes an indispensable tool in enterprise financial operations, businesses are swiftly adopting automated solutions for processing invoices, detecting fraud, and ...

Artificial intelligence has penetrated deeply into financial services, powering everything from credit scoring to fraud detection. Yet a fundamental tension exists between AI's computational power and ...

While reliability, transparency, and effectiveness strengthen trust, the study shows that they are not sufficient on their ...

The 2025 AI Policy Year in Review identifies four shifts that will dominate the 2026 landscape, including agentic AI liability, the shift from policies to penalties, the market purge of black box AI, ...