Giving Compass' Take:

· In a society where technology continues to advance and play a larger role, it's reasonable to have concerns when artificial intelligence in involved in the criminal justice system and decision making. Nature Research discusses concerns about the systems and the researchers working to make algorithms unbiased.

· What can be done to ensure the programmed algorithms are fair and unbiased?

· Read more about the concerns about inequality in algorithms.

In 2015, a worried father asked Rhema Vaithianathan a question that still weighs on her mind. A small crowd had gathered in a basement room in Pittsburgh, Pennsylvania, to hear her explain how software might tackle child abuse. Each day, the area’s hotline receives dozens of calls from people who suspect that a child is in danger; some of these are then flagged by call-centre staff for investigation. But the system does not catch all cases of abuse. Vaithianathan and her colleagues had just won a half-million-dollar contract to build an algorithm to help.

Vaithianathan, a health economist who co-directs the Centre for Social Data Analytics at the Auckland University of Technology in New Zealand, told the crowd how the algorithm might work. For example, a tool trained on reams of data — including family backgrounds and criminal records — could generate risk scores when calls come in. That could help call screeners to flag which families to investigate.

After Vaithianathan invited questions from her audience, the father stood up to speak. He had struggled with drug addiction, he said, and social workers had removed a child from his home in the past. But he had been clean for some time. With a computer assessing his records, would the effort he’d made to turn his life around count for nothing? In other words: would algorithms judge him unfairly?

Vaithianathan assured him that a human would always be in the loop, so his efforts would not be overlooked. But now that the automated tool has been deployed, she still thinks about his question. Computer calculations are increasingly being used to steer potentially life-changing decisions, including which people to detain after they have been charged with a crime; which families to investigate for potential child abuse, and — in a trend called ‘predictive policing’ — which neighbourhoods police should focus on. These tools promise to make decisions more consistent, accurate and rigorous. But oversight is limited: no one knows how many are in use. And their potential for unfairness is raising alarm. In 2016, for instance, US journalists argued that a system used to assess the risk of future criminal activity discriminates against black defendants.

Read the full article about making algorithms fair in artificial intelligence by Rachel Courtland at Nature Research.