Algorithms

A California bill replaces cash bail with risk-assessment algorithms, which critics argue will perpetuate the pre-trial detention of minority and low-income defendants.

Algorithmic prejudices can create inequalities. But in doing so, they might help lawyers pinpoint discrimination where they could not in the past.

When the underlying data they rely on is incomplete—and it often is—the growing use of machine learning tools in America's criminal justice system can have devastating effects.

A recent vote over a proposed tool to predict the risk that a person would pose a threat to public safety in Pennsylvania stirred a debate over its unintended consequences.

The criminal justice system has been using predictive algorithms for decades, but research shows even the best algorithms are no better than humans at predicting recidivism—and neither are very good.

We can learn more about our own internal decision-making processes through the language of mathematical algorithms used by AI machines.

When big data uses bad data, discrimination can result.

The latest entry in a special project in which business and labor leaders, social scientists, technology visionaries, activists, and journalists weigh in on the most consequential changes in the workplace.

Corporations are increasingly relying on algorithms to make business decisions, and that raises new legal questions.

Asians are nearly twice as likely to get a higher price from the Princeton Review's SAT test prep services.

The latest entry in a special project in which business and labor leaders, social scientists, technology visionaries, activists, and journalists weigh in on the most consequential changes in the workplace.

The latest entry in a special project in which business and labor leaders, social scientists, technology visionaries, activists, and journalists weigh in on the most consequential changes in the workplace.

Algorithms are fundamentally uncreative. Every set of crunched numbers, every calculated outcome, needs an equal and perhaps opposite human component to bring it to life.

From the NSA to OKCupid.

Understand that human thinking is fuzzy around the edges, which is totally different from how computers compute.

Can a simple Google Trends algorithm beat Wall Street?