Machine learning and artificial intelligence have taken organizations to new heights of innovation, growth, and profits thanks to their ability to analyze data efficiently and with extreme accuracy.

When scientists test algorithms that sort or classify data, they often turn to a trusted tool called Normalized Mutual Information (or NMI) to measure how well an algorithm's output matches reality.

New research shows that people recognize more of their biases in algorithms' decisions than they do in their own -- even when those decisions are the same. Algorithms were supposed to make our lives ...

The hype around ChatGPT and other generative-artificial-intelligence technology is highlighting a continuing challenge for businesses: how to keep bias out of their own AI algorithms. Businesses are ...

Bias in AI is pervasive. From dermatological models that discriminate against patients with darker skin to exam-scoring algorithms that disadvantage public school students, you don’t need to look far ...

Algorithms in clinical decision tools have been making it harder for certain racial and socioeconomic groups to receive the healthcare they deserve.

Tech companies acknowledge machine-learning algorithms can perpetuate discrimination and need improvement. By Zachary Small The artist Stephanie Dinkins has long been a pioneer in combining art and ...

Algorithms were supposed to make our lives easier and fairer: help us find the best job applicants, help judges impartially assess the risks of bail and bond decisions, and ensure that health care is ...