Technology has advanced enormously in the 30 years since the introduction of the first Children Act, which shaped the UK’s system of child safeguarding. Today a computer-generated analysis – “machine learning” that produces predictive analytics – can help social workers assess the probability of a child coming on to the at-risk register. It can also help show how they might prevent that happening.
But with technological advances come dilemmas unimaginable back in 1989. Is it right for social workers to use computers to help promote the welfare of children in need? If it is right, what data should they draw on to do that?
Maris Stratulis, national director of the British Association of Social Workers England, first voiced concerns last year. She remains worried. “Machine learning in social care still raises significant issues about how we want to engage with children and families,” she says. “Reports on its use in other countries, such as New Zealand, have shown mixed results including potential unethical profiling of groups of people.”Advertisement
Stratulis is also concerned at the role of profit-making companies in the new techniques. “Rather than focusing on learning from machines and algorithms, let’s focus on good, relationship-based social work practice,” she says.
Machine learning is an application of artificial intelligence (AI). Computer systems enable councils to number-crunch vast amounts of data from a variety of sources, such as police records, housing benefit files, social services, education or – where it is made available – the NHS. In children’s services, a council may ask for analysis of specific risk factors which social workers would otherwise not know, such as a family getting behind on the rent, which can then be triangulated with other data such as school attendance.