Governments Creating Precrime Child Abuse Algorithms to Predict Child Abuse - Or Just to Kidnap More Children

In the effort to find and help vulnerable children, authorities are looking at precrime intervention in the form of artificial intelligence and data processing to find at-risk children before they are harmed. The world of sci-fi precrime, like that depicted in Minority Report, is heading towards a reality near you.

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In the U.K., child protective services are said to be 800 million pounds short in funding according to The Guardian who covered the move by Bristol authorities to experiment with algorithms and AI to remove children from homes before they are harmed. But this raises some moral/ethical questions. Can this work? Or will it criminalize parents and kidnap children from families where they were not in any real danger at all?

Bristol council's predictive system is overseen by Gary Davies, and sees the advantages. Instead of removing humans from the process, Davies argued it will mean that data will be looked at to stop humans from making mistakes:

"It's not saying you will be sexually exploited, or you will go missing. It's demonstrating the behavioural characteristics of being exploited or going missing. It's flagging up that risk and vulnerability."

But his comments seem to suggest that the fate of families will be inthe hands of computers who will categorize children's behaviors or their parents as promoting an environment that favors being exploited, and hence call for attention from the child "protective" services. As many victims of CPS know, once the Child Procurement Syndicate targets you as a threat to a child, there is a high probability that your child will get taken from you and you have to battle your way to get them back.

Could the cost-cutting of services be a problem-reaction-solution in order to bring in more Orwellian-dystopian micromanagement and control over our lives? Maybe. In explaining how useful the system could be, The Guardian talks about the AI efficiency of data mining of consumer behavior to promote how useful it could be when applied to family and child behavior:

Machine learning systems built to mine massive amounts of personal data have long been used to predict customer behaviour in the private sector.

Computer programs assess how likely we are to default on a loan, or how much risk we pose to an insurance provider.

The way it would work for children, is looking at indicators that predict the emergence of an outcome. They want to compile data from children who enter the child care system which would give them a model to target other children for child care services:

They then attempt to identify characteristics commonly found in children who enter the care system. Once these have been identified, the model can be run against large datasets to find other individuals who share the same characteristics.

What characteristics would be looked at as "predictive indicators", for example?

... history of domestic abuse, youth offending and truancy.

But that's not all. The Guardian mentions other indicators that are often used to treat parents as unfit and therefore harming their children: unemployment. Some indicators didn't make it, such as "rent arrears and health data", luckily, but will it stay that way in the future? Any non-positive life circumstances can be used to "predict" how a parent is creating an unfavorable or harmful environment for a child.

Data prediction metrics used in other areas are not 100% accurate, with about an 80% track record on accuracy. Think about that in terms of families and parents. What happens to the 20% who are falsely accused of being bad parents or child abusers outright, and nothing would have happened to the children? Well, that doesn't matter compared to the greater good of protecting 80%, right? Wrong. That's not including the 80% who match the predictive indicators but wouldn't have led to child abuse anyways.

Data privacy is also a concern, as The Guardian points out. Some people think that this must be pursued with the aim of "balancing" protection of the vulnerable and protecting people's rights to privacy. Automated predictive profiling is a pretty open area as there is no national oversight on what authorities are doing and how much they disclose what their doing.

Michael Veale, a researcher in public sector machine learning at University College London is in favor of the system it seems, as he justifies the false positive of innocent parents who get dragged through the mud and court system, causing trauma to children, as he is favorable to casting a wide net:

"When you predict events like these, you tend to get false positives. If you want to make sure you don’t miss children who are at risk, you’re going to play it safe and cast your net widely."

I see this system being used to favor more kidnapping of children from parents who are no threat, further terrorizing families and parents and spreading trauma to children who have unfavorable characteristics that match predictive indicators. This will of course be welcome for the social workers, foster system and agencies who will have more justification for what they do and the need for more funding.

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Thank you for your time and attention. Peace.

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