Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study ...

Under the right circumstances, algorithms can be more transparent than human decision-making, and even can be used to develop a more equitable society.

Though meant to make decisions around criminal justice, policing and public service easier, some are concerned algorithms designed by humans come with inherent bias and a need for oversight.

Often, when there’s talk about algorithms and journalism, the focus is on how to use algorithms to help publishers share content better and make more money. There’s the unending debate, for example, ...

For example, the A-level algorithm adjusted results to try to replicate the previous overall achievements of different ethnic groups, which are likely to reflect racial inequality.

How, then, can a single algorithm guide different robotic systems to make the best decisions to move through their surroundings?

For example, an algorithm called CB (color blind) imposes the restriction that any discriminating variables, such as race or gender, should not be used in predicting the outcomes.

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.

For example, an algorithm called CB (color blind) imposes the restriction that any discriminating variables, such as race or gender, should not be used in predicting the outcomes.