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 ...

Algorithms can be used to make decisions: for example, to make a selection from a pool of job applicants or to assess what kind of care someone needs. Joosje Goedhart explains, ‘There are various ...

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

Clearly making algorithms simpler for humans to understand and building trust in these digital decision-makers is good for society, but we have no easy pathways to that outcome.

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.

Most people expect algorithms to make recommendations on the basis of maximizing some specific outcome, and many people are fine with that in amoral domains, according to the researchers. For example, ...

So, an algorithm is the process a computer uses to transform input data into output data. A simple concept, and yet every piece of technology that you touch involves many algorithms.

Algorithms are increasingly being turned to as a way for companies to make objective decisions, including ones that have complex social implications. But they're not always as unbiased as you ...

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.