When you sign up for a new app or platform, you’re often asked to “agree” to the terms of service and privacy policies. But what does that consent mean, and is it meaningful?

AI is transforming consumer lending, promising faster credit decisions and greater access. But the reality is more complicated. Many AI-based scoring systems rely on alternative data — utility payments, online behavior, even social media activity — to predict creditworthiness.

AI-powered hiring tools are being adopted by companies large and small, promising to streamline recruitment and reduce human bias. But recent investigations have raised serious concerns that these systems may actually amplify discrimination rather than prevent it.

AI chatbots have become a daily fixture, from customer support and virtual assistants to AI companions. But behind their smooth conversations lies a complex system that even their creators sometimes struggle to fully explain. This opacity is what many refer to as the “black box” problem in AI: we see the inputs and outputs, but not always the logic in between.

Despite growing public awareness and new privacy laws, data broker companies that buy, sell, and aggregate personal information continue to thrive. These firms compile data from credit reports, social media, app usage, and even offline purchases, building profiles that can include thousands of data points per person.

In 2016, computer scientist Joy Buolamwini made a striking discovery at the MIT Media Lab—facial analysis software could not detect her face unless she wore a white mask, due to biased training data favoring light-skinned individuals.

A new IBM global study highlights a troubling gap between AI policy rhetoric and real-world governance. Although 80% of executives say AI governance is critical to responsible innovation, only 20-30% have put robust practices in place.

New Orleans is at the center of a national debate as it considers an ordinance to legalize real-time facial recognition surveillance across the city.

Europe’s landmark AI Act has officially entered the implementation phase, ushering in one of the world’s most comprehensive frameworks for governing artificial intelligence. The law targets high-risk AI systems, including biometric identification, predictive policing, and AI in critical infrastructure, with strict requirements for transparency, human oversight, and risk assessments.