International Journal of Knowledge Based Computer System

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

An Empirical Model Integrating AI into Government


Affiliations
1 University of Oxford Alumni- (Research Group, Alumni Association, Northern California, United States
     

   Subscribe/Renew Journal


This study explores the evolution of global AI dynamics by discussing its role in government with a focus on aspects of development and governance of social and technological systems (STS). This document reports three research questions, including the extent of the analysis: (1) theories regarding the concept of AI in the public sector; (2) expectations regarding the development of AI in the public sector; and, (3) the challenges and opportunities of AI in the public sector. This experimental study provides an experimental framework for a comprehensive approach to measuring the magnitude of AI policy that allows for the methods of evaluating different governance practices and policy priorities in different countries. The study sheds light onto areas of policy that have the potential to implement AI programs and strategies; administrative functions open to the acceptance of AI applications and strategies; and the challenges/risks that community managers may face in defining AI policies and projects in the public sector including how to deal with cyber-troops

Keywords

AI, Cyber-troops, HCI,, Misinformation, Socio-technological Systems, Tech Policy
Subscription Login to verify subscription
User
Notifications
Font Size


  • P. E. Agre, “Surveillance and capture: Two models of privacy,” The Information Society, vol. 10, no. 2, pp. 101-127, 1994.

  • J. Allen, Topologies of Power: Beyond Territory and Networks. London: Routledge, 2016.

  • B. Bratton, The Stack: On Software and Sovereignty. MIT Press, 2015.

  • T. Bucher, If...Then: Algorithmic Power and Politics. Oxford University Press, 2018.

  • L. Castañeda, and N. Selwyn, “More than tools? Making sense of the ongoing digitizations of higher education,” International Journal of Educational Technology in Higher Education, vol. 15, no. 1, 2018.

  • M. Decuypere, “Open education platforms: Theoretical ideas, digital operations and the figure of the open learner,” European Educational Research Journal, vol. 18, no. 4, pp. 439-460, 2019a.

  • M. Dieter, C. Gerlitz, A. Helmond, N. Tkacz, F. Vlist, V. Der, and E. Weltevrede, “Store, interface, package, connection: Methods and propositions for multi-situated app studies,” CRC Media of Cooperation Working Paper Series No. 4, 2018.

  • J. Drucker, Visualization and Interpretation: Humanistic Approaches to Display. MIT Press, 2020.

  • M. Decuypere, “The topologies of data practices: A methodological introduction,” Journal of New Approaches in Educational Research, vol. 10, no. 1, 2021.

  • K. N. Gulson, S. Lewis, B. Lingard, C. Lubienski, K. Takayama, and P. T. Webb, “Policy mobilities and methodology: A proposition for inventive methods in education policy studies,” Critical Studies in Education, vol. 58, no. 2, pp. 224-241, 2017.

  • K. N. Gulson, and S. Sellar, “Emerging data infrastructures and the new topologies of education policy,” Environment and Planning D: Society and Space, vol. 37, no. 2, pp. 350-366, 2019.

  • S. Hartong, “The power of relation-making: Insights into the production and operation of digital school performance platforms in the US,” Critical Studies in Education, pp. 1-16, 2020.

  • S. Hartong, and A. Förschler, “Opening the black box of data-based school monitoring: Data infrastructures, flows and practices in state education agencies,” Big Data & Society, vol. 6, no. 1, 2019.

  • S. Lash, “Deforming the figure: Topology and the social imaginary,” Theory, Culture & Society, vol. 29, no. 4-5, pp. 261-287, 2012.

  • B. Latour, “Visualization and cognition: Thinking with eyes and hands,” Knowledge & Society, vol. 6, pp. 1-40, 1986. [Online]. Available: http://hci.ucsd.edu/10/readings/Latour(1986).pdf

  • J. Law, After Method: Mess in Social Science Research. Psychology Press, 2004.

  • S. Lewis, “Providing a platform for “what works”: Platform-based governance and the reshaping of teacher learning through the OECD’s PISA4U,” Comparative Education, vol. 56, no. 4, pp. 484-502, 2020.

  • S. Lewis, and I. Hardy, “Tracking the topological: The effects of standardised data upon teachers’ practice,” British Journal of Educational Studies, vol. 65, no. 2, pp. 219-238, 2017.

  • B. Light, J. Burgess, and S. Duguay, “The walkthrough method: An approach to the study of apps,” New Media and Society, vol. 20, no. 3, pp. 881-900, 2018.

  • M. Lindh, and J. Nolin, “Information we collect: Surveillance and privacy in the implementation of Google apps for education,” European Educational Research Journal, vol. 15, no. 6, 2016.

  • C. Lury, and S. Day, “Algorithmic personalization as a mode of individuation,” Theory, Culture & Society, vol. 36, no. 2, pp. 17-37, 2019.

  • C. Lury, R. Fensham, A. Heller-Nicholas, and S. Lammes, Routledge Handbook of Interdisciplinary Research Methods. London: Routledge, 2018.

  • C. Lury, L. Parisi, and T. Terranova, “Introduction: The becoming topological of culture,” Theory, Culture & Society, vol. 29, no. 4-5, pp. 3-35, 2012.

  • C. Lury, M. Tironi, and R. Bernasconi, “The social life of methods as epistemic objects: Interview with Celia Lury,” Diseña, vol. 16, pp. 32-55, 2020.

  • C. Lury, and N. Wakeford, “Introduction: A perpetual inventory,” in C. Lury, and N. Wakeford, (eds.), Inventive Methods: The Happening of the Social. Culture, Economy and the Social (CRESC). London: Routledge, 2012, pp. 1-24.

  • L. Martin, and A. J. Secor, “Towards a post-

  • mathematical topology,” Progress in Human Geography, vol. 38, no. 3, pp. 420-438, 2014.

  • N. Piattoeva, and A. Saari, “Rubbing against data infrastructure(s): Methodological explorations on working with(in) the impossibility of exteriority,” Journal of Education Policy, pp. 1-21, 2020.

  • J. C. Plantin, C. Lagoze, P. N. Edwards, and C. Sandvig, “Infrastructure studies meet platform studies in the age of Google and Facebook,” New Media and Society, vol. 20, no. 1, pp. 293-310, 2018.

  • R. Prince, “Local or global policy? Thinking about policy mobility with assemblage and topology,” Area, vol. 49, no. 3, pp. 335-341, 2017.

  • H. Ratner, “Topologies of organization: Space in continuous deformation,” Organization Studies, pp. 1-18, 2019.

  • H. Ratner, and C. Gad, “Data warehousing organization: Infrastructural experimentation with educational governance,” Organization, vol. 26, no. 4, pp. 537-552, 2019.

  • H. Ratner, and E. Ruppert, “Producing and projecting data: Aesthetic practices of government data portals,” Big Data & Society, vol. 6, no. 2, pp. 1-16, 2019.

  • E. Ruppert, J. Law, and M. Savage, “Reassembling social science methods: The challenge of digital devices,” Theory, Culture & Society, vol. 30, no. 4, pp. 22-46, 2013.

  • L. Suchman, “Configuration,” in C. Lury, and N. Wakeford, (eds.), Inventive Methods: The Happening of the Social. Taylor and Francis, 2012, pp. 48-60.

  • G. Thompson, and I. Cook, “Becoming-topologies of education: Deformations, networks and the database effect,” Discourse: Studies in the Cultural Politics of Education, vol. 36, no. 5, pp. 732-748, 2015.

  • G. Thompson, and S. Sellar, “Datafication, testing events and the outside of thought,” Learning, Media and Technology, vol. 43, no. 2, pp. 139-151, 2018.

  • K. van de Oudeweetering, and M. Decuypere, “Understanding openness through (in) visible platform boundaries: A topological study on MOOCs as multiplexes of spaces and times,” International Journal of Educational Technology in Higher Education, vol. 16, no. 1, 2019.

  • K. van de Oudeweetering, and M. Decuypere, “In between hyperboles: Forms and formations in open education,” Learning, Media and Technology, Advance Online Publication, pp. 1-18, 2020.

  • B. Williamson, “Learning in the “platform society”: Disassembling an educational data assemblage,” Research in Education, vol. 98, no. 1, pp. 59-82, 2017.

  • K. Fedorova, Tactics of Interfacing: Encoding Affect in Art and Technology. MIT Press, 2020.

  • O. Goriunova, “The digital subject: People as data as persons,” Theory, Culture & Society, vol. 36, no. 6, pp. 125-145, 2019.


Abstract Views: 212

PDF Views: 0




  • An Empirical Model Integrating AI into Government

Abstract Views: 212  |  PDF Views: 0

Authors

Arslan I AyseKok
University of Oxford Alumni- (Research Group, Alumni Association, Northern California, United States

Abstract


This study explores the evolution of global AI dynamics by discussing its role in government with a focus on aspects of development and governance of social and technological systems (STS). This document reports three research questions, including the extent of the analysis: (1) theories regarding the concept of AI in the public sector; (2) expectations regarding the development of AI in the public sector; and, (3) the challenges and opportunities of AI in the public sector. This experimental study provides an experimental framework for a comprehensive approach to measuring the magnitude of AI policy that allows for the methods of evaluating different governance practices and policy priorities in different countries. The study sheds light onto areas of policy that have the potential to implement AI programs and strategies; administrative functions open to the acceptance of AI applications and strategies; and the challenges/risks that community managers may face in defining AI policies and projects in the public sector including how to deal with cyber-troops

Keywords


AI, Cyber-troops, HCI,, Misinformation, Socio-technological Systems, Tech Policy

References