Automated Risk-Scoring for Benefit Claims
The Case
The BBC have reported that the Department of Work and Pensions (DWP) is facing calls for greater transparency regarding its plans to expand the use of Artificial Intelligence in risk-scoring benefit claims. The DWP aims to leverage AI to identify potential fraudulent claims, particularly in the context of Universal Credit. However, campaigners and watchdogs have raised concerns about potential biases, lack of transparency, and the implications of AI-driven decisions on claimants.The system employs machine learning, a form of AI, to analyse historical benefits data, and predict the likelihood of a new claim being fraudulent or incorrect.The DWP has disclosed intentions to pilot similar AI models in areas with high overpayment rates, such as undeclared earnings from self-employment and incorrect housing costs.
Key Issues
Whilst the use of AI in this context has the potential to ease pressure on public spending, several concerns have been raised. There is a persistent lack of transparency in how AI systems like this actually make decisions, which is likely to undermine the trust in any decisions made, particularly if any erroneous or flawed results are relied upon. Without having a deeper understanding for how systems generate results, or indeed a clear monitoring system to avoid inaccuracies or bias, it’s possible that vulnerable parts of society may be unjustly deprived of crucial support.