What are quantum-resistant algorithms—and why do we need them? When quantum computers become powerful enough, they could theoretically crack the encryption algorithms that keep us safe.

Why have algorithms become the focus of our collective societal ire in the digital era? Today’s collections of code are blamed for nearly every problem we confront today. Looming all-powerful ...

Artificial Intelligence developed at Rutgers has deemed "Mona Lisa" not so great after all.

Key points Many companies use algorithms to make important decisions. These algorithms are often as flawed as the humans who create them. Algorithms tend to fail when they have the wrong data or ...

The A-level fiasco is a strong lesson in why we need to reconsider the importance of fairness in algorithms, their data and the mathematical models that govern them.

When we tested our algorithms with the widely used sample data sets, we were surprised at how well they performed relative to open-source algorithms assembled by IBM.

There are three key reasons why predictive algorithms can make big mistakes. 1. The Wrong Data An algorithm can only make accurate predictions if you train it using the right type of data.