Suchergebnisse

In recent years, the topic of artificial intelligence in government has become a major area of study. Governments have been eager to adopt artificial intelligence for a number of purposes, including for the prediction of risk in social services. Child protection services are exploring predictive analytics for the initial screening of cases. While research identifies data quality issues as a major barrier, little is known about the characteristics of these issues in child protection, their relationship to organizational memory contained in administrative data, and their impact on the ability of an organization to adopt these technologies. This study gained insight into the socio-technical limitations of duplicate records when trying to bring organizational memory to bear in predictive decision support by interviewing and observing staff use of information technology systems. The study's findings suggest that record duplication in case management systems in child protection could pose a significant challenge to the introduction of artificial intelligence technologies such as predictive analytics for decision assistance. There is a need to address foundational information management and system issues before artificial intelligence approaches such as this can be introduced in the child protection sector.

In recent years, local government has been undergoing changes which are strongly influenced by the growing digitization of governmental operations. In this paper, we expand on the concepts of Digital Era Governance and its successor, Essentially Digital Government, by introducing the concept of Algorithmic Bureaucracy, which looks at the impacts of artificial intelligence on the socio-technical nature of public administration. We report on a mixed-method study, which focused on how the growth of data science is changing the ways that local government works in the United Kingdom. Under Algorithmic Bureaucracy, the direct and indirect effects of public administrative changes on the level of social problem solving may become positive in two cases: 1) where through artificial intelligence and isocratic administration the explainability of algorithmic processes increases individual and staff competence, and 2) where algorithms take on some of the role of processing institutional and policy complexity much more effectively than humans.

In recent years, local government is undergoing changes which are strongly influenced by the growing digitization of governmental operations. Key features of Digital Era Governance (DEG) appear to be displacing features of the New Public Management (NPM) and are also challenging some underlying aspects of Weberian bureaucracy in public administration. In this paper, we expand on the concepts in DEG and its successor, Essentially Digital Government (EDGE), by introducing the concept of Algorithmic Bureaucracy, which looks at the impacts of Artificial Intelligence (AI) on rationalization and the socio-technical nature of public administration. We report on a mixed-method study, which focused on how the growth of data science is changing the ways that local government works in the UK. Special emphasis is put on how algorithms can build citizen and administrator competence and deal with complexity. Algorithmic bureaucracy, like traditional bureaucracy, is impartial in its application, but can be predictably sensitive to context. Society needs to determine the ends to which it is put and how to assign accountability in this context. We find that algorithmic bureaucracy is in its infancy in local government, so there is space to develop an appropriate ethical framework to harness the technology and enhance social problem solving.

In recent years, local authorities in the UK have begun to adopt a variety of 'smart' technological changes to enhance service delivery. These changes are producing profound impacts on the structure of public administration. Focusing on the particular case of artificial intelligence, specifically autonomous agents and predictive analytics, a combination of desk research, a survey questionnaire, and interviews were used to better understand the extent and nature of these changes in local government. Findings suggest that local authorities are beginning to adopt smart technologies and that these technologies are having an unanticipated impact on how public administrators and computational algorithms become imbricated in the delivery of public services. This imbrication is described as algorithmic bureaucracy and it provides a framework within which to explore how these technologies transform both the socio‐technical relationship between workers and their tools, as well as the ways that work is organized in the public sector.