Abstract
This study investigates the contribution of technology in the public administration discipline by illustrating how and why public administration and technology are connected. A qualitative thematic analysis conducted using a sample of U.S. public affairs schools/colleges sheds light on the main topics of technology-related courses in the United States academia. The findings seem to confirm the positive interest in integrating technology in the public administration discipline. In particular, the top U.S. public affairs/administration colleges provide a variety of technology-related courses. The main topics covered are cybersecurity, big data, and information technology, among others. Nevertheless, the analysis stresses the importance of considering the dark side of technology tools applied to the public sector. Indeed, the critical theoretical review discusses some major concerns regarding accountability, bias decisions, discrimination, and inequality.
TopIntroduction
Public administration is both an academic and a professional discipline that concentrates on the public sector and – in particular – on its processes used to carry out public policies and programs. It is considered interdisciplinary because it often uses concepts and theories from law, political science, organizational psychology, sociology, anthropology, business management, international relations, and information systems (Klingner, 2003). Many scholars studied the gap between theory and practice in public administration (McQuiston and Manoharan, 2020). In particular, some of them defined public administration as a “pracademic” discipline (Posner, 2009) also highlighting how the two dimensions (the academic and the practitioner) are both relevant to the discipline (e.g. see Box, 1999; O’Leary and Vij, 2012; Peters and Pierre, 2003; Streib et al., 2001; Welch and Wong, 1998).
Despite “the most essential expertise of the public administrator is political skill and knowledge that facilitate the melding of technical knowledge with “public” knowledge and judgment in the process of forming public policy” (Radin et al., 1989), the last decades experienced major changes investing the global scale and required different and more sophisticated approaches to public administration. For example, with the advent of globalization, Internet boom, Big Data, the affirmation of paradigms of the New Public Governance (e.g. see Osborne, 2006), and the public value (e.g. see Benington and Moore, 2010; Moore, 2013; O'Flynn, 2007, Shaw, 2013), the need to invest in technical knowledge became an imperative. In this sense, many academic programs have not included the necessary practical knowledge for the challenges that employees working in the public sector face nowadays (Braga, 2020; Newland, 2000; Ospina and Dodge, 2005; Stivers, 2000). Furthermore, “technological change is a powerful shaping influence on public administration, but one which is seldom directly addressed by most public administration scholars” (Pollitt, 2010: 31).
As a discipline, public administration has continually been marked with a “self-imposed” identity crisis (e.g. see Braga, 2020, Hafer, 2016; Rutgers, 1998; Raadschelders, 1999). This crisis “has been at the center of the discipline since its inception” (Morgan et al., 2010: 626). From the Education point of view, Braga (2020: 285) points out that public administration “has become less attractive, because academia encourages political science and public policy […] and the system is more concerned about teaching policy rather than governing”. Nonetheless, public administration is continually searching for its distinctive identity, by establishing common disciplinary narratives (e.g. see, Haque, 2019; Ni, et al., 2017; Ospina and Dodge, 2005; Ospina, 2011; Riccucci, 2010). A part of its identity can be found within the relationship with technology. As highlighted by Hustedt et al., (2020), in the current era of digital transformation, technology and public administration need to work together. In this sense, public administration Education needs to support the relationship with technology, because we live in a digital world (Ganapati and Reddic, 2016). Hence, Higher Education systems should contribute to strengthening the relationship between public administration and technology through the provision of IT/technology courses within programs of public affairs/administration schools and colleges.
Key Terms in this Chapter
Artificial Intelligence: It is a scientific field that combines computer science and robust datasets, to enable problem-solving and to make intelligent machines and computer programs, by trying to replicate human intelligence.
New Public Governance: It is the twenty-first Century public administration approach (paradigm) addressing the delivery of publicly-funded services. It developed in response to some of the effects of the New Public Management approach. New Public Governance scholars are known for analyzing collaborative relationships between profit and nonprofit organizations that deliver publicly-funded services and government representatives who outsource them and then fund and monitor their services and their outcomes.
Big Data: It is a large, more complex data set, especially from new data sources data that contains greater variety, arriving in increasing volumes and with more velocity. Big data can be used to address business problems that cannot be dealt with by simple data collection.
Blockchain: It is a technology that allows data management and autonomous peer-to-peer connectivity within networks by improving security when exchanging sensible information within the Internet (or networks in general).
New Public Management: It is an approach (paradigm) explaining how to run public service organizations that are used in government and public service institutions and agencies, at both sub-national and national levels. The term was first introduced by academics in the UK and Australia to describe approaches that were developed during the 1980s as part of an effort to make the public service more “business-like” and to improve its efficiency by using private sector management models.
Machine Learning: It is a branch of artificial intelligence (AI) and computer science which focuses on the use of data and algorithms to imitate the way that humans learn, gradually improving its accuracy. Through the use of statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects. This output drive decision-making within applications and businesses, ideally impacting key growth metrics.
Co-Production (of Public Services): The term refers to a way of working where service providers and users, work together to reach a collective outcome. The approach is value-driven and built on the principle that those who are affected by a service are best placed to help design it.
Smart City: It is a designation given to a city that incorporates information and communication technologies (ICT) to enhance the quality and performance of urban services – such as energy, transportation, and utilities –to reduce resource consumption, wastage, and overall costs. The main goal of a smart city is to optimize city functions and promote economic growth while improving the quality of life for citizens by using smart technologies and data analysis.