Mapping and analysing data practices across local government

Source: PSE April/May 2019

Dr Joanna Redden, Dr Lina Dencik, Dr Arne Hintz and Harry Warne, of the School of Journalism, Media and Culture at the University of Cardiff, tell more on the technology they are using for analysing decisions of local authorities across the UK.

Globally, governments at all levels are making greater uses of new data systems as they try to improve service delivery and decision-making. We know that these new systems come with both opportunities and risks. Despite these risks and the extent to which uses of new data systems are changing governance, there is little information available about where and how governments are making use of data systems. This makes it difficult for citizens to engage in debate about whether the changes taking place are ones they agree with.

Our Data Scores as Governance project maps and analyses local government uses of data analytics, with a particular focus on investigating uses of predictive analytics. Our multi-method investigation led to: 1) a comprehensive list and map of data analytics systems across local authorities, 2) a research report that details concrete examples of the different types of analytics systems being used as well as a survey of civil society concerns and 3) an interactive online tool to facilitate greater research and debate. 

We identified 53 councils using predictive analytics. Our list must be viewed as a work in progress, in that it is highly likely there are other systems being used that were not identified. The range of responses we were provided indicate that there is no common understanding of what constitutes predictive analytics in government. We suggest that central and local government agencies should publicly list algorithmic systems in use affecting people, as has been called for by the UK Science and Technology Committee and is happening in other countries.

Predictive analytics is being used in child welfare, policing, fraud detection, public safety and transport amongst other areas. Some councils are developing their own in-house systems, others are working with private companies. Our research demonstrates, as expected, developments across local authorities are distinct. In some cases data sharing and analytics is being used for risk scoring whilst in other contexts databases are used for population level analytics to anticipate future need. We found increased data sharing across our case studies, but for different purposes.

In some cases to make it easier for frontline staff to share information and produce more comprehensive individual and social network profiles and in other cases to enable automated risk analyses to produce alerts when a certain threshold has been crossed. A recurring theme is that the austerity context and the funding constraints faced by local authorities is one of the main reasons for introducing or enhancing data analytics systems. Local authorities are responding to cuts by using data to try and better target resources.

Greater debate is needed about how the use of these systems are changing frontline working practices and reconfiguring access to and delivery of public services. To date, there is too little transparency and discussion about the accuracy of these systems and the limits of auditing. There is little effort to encourage citizen engagement and intervention. There is also little assessment of unintended consequences and of the impact of interventions taken on the basis of data-driven scores. The need for more public engagement, transparency, accountability, and regulation remain key concerns amongst stakeholder groups who recognize that the GDPR will be insufficient to address concerns.

Other concerns are that the data systems being introduced, over the longer term, may shift government priorities with negative outcomes. For example, the focus is on capturing and analysing data in relation to individuals and not on capturing data about the influence of positive or insulating factors that can reduce risk such as the presence of extended family networks or an afterschool program. More broadly it may focus responses solely on the individual or household, bypassing societal factors in the creation of social problems.

An emphasis on risk assessment may lead to a broader shift in state operations as citizens become viewed less as co-creators of the societies they are part of and more as potential risks needing management. There is a significant disparity between practitioners’ and stakeholder groups’ perspectives on the nature of challenges that emerge from uses of data analytics in public services demonstrating the need to bring these groups together and expand cross-sector debate and enhance the means for meaningful citizen participation and intervention.

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