AI agents will make decisions that affect human lives, wealth and well-being. Yet we've built these systems on black-box architectures.

The black box problem refers to the opacity of certain AI systems. Recruiters know what information they feed into an AI tool (the input), and they can see the results of their query (the output).

Regulating AI in healthcare has been on the legislative agenda in a number of states in recent months, as critics argue that ...

At first glance, this seems like a win for transparency. If an AI explains itself, we can understand its motives, catch ...

Infosys co-founder Nandan Nilekani has criticised the increasing complexity of AI models, arguing that it does not necessarily lead to better results. Speaking at the People+AI Mela in Bengaluru, he ...

AI is advancing at warp speed, and with it comes AI-anxiety, the fear of missing out on the next big breakthrough. Over 70% ...

We’re right on the edge of a new security landscape, because even the white hats are facing a black box in the AI. So far, what ChatGPT and Codex and other large language models are doing is ...

Two Microsoft researchers have devised a new jailbreak method that bypasses the safety mechanisms of most AI systems.

He stressed the need to "open the black box" of AI decision-making, making its processes understandable to regulators, businesses, and the public alike. "Explainability is not just about ...

In a Q&A with Redmondmag, Shiri delves into the complexities of defending AI systems, particularly those operating in black-box environments where model architecture and parameters remain hidden.