Shadow of the smart machine: Algorithm guided decision making in the public sector

Given rising pressure from demographic change and shrinking finances; the public sector is having to look for new ways to support and manage demand. In parallel, there is an on-going explosion in sources and volumes of data available (and a reduction in the technical cost to make sense of this data) to understand and predict future demand. Consequently, there is a growing interest in using this data (and related Big Data technologies) to build algorithms that support more timely and accurate decision making – whether this is to support strategic commissioning decisions or the targeting of interventions. Ethical challenges are often premised on the assumption that algorithms will be implemented as an autonomous system. Although there are a few examples in the private sector (ie financial credit scoring systems) it is highly unlikely that this type of autonomous implementation would occur in the public sector.