Chief information officers’ perceptions about artificial intelligence

A comparative study of implications and challenges for the public sector

Authors

  • J. Ignacio Criado Associate Professor / Senior Lecturer in Political Science and Public Administration, Department of Political Science and International Relations, at Universidad Autónoma de Madrid http://orcid.org/0000-0002-9184-9696
  • Rodrigo Sandoval-Almazan Associate Professor at the Political Sciences and Social Sciences Department in the Autonomous University of the State of Mexico https://orcid.org/0000-0002-7864-6464
  • David Valle-Cruz Assistant Professor at the Computing Engineering Department in the Autonomous University of the State of Mexico https://orcid.org/0000-0002-5204-8095
  • Edgar A. Ruvalcaba-Gómez Research Professor at the Universidad de Guadalajara, with affiliation to the Department of Public Policy, and Coordinator in the Research Institute in Public Policies and Government https://orcid.org/0000-0003-0999-0680

DOI:

https://doi.org/10.5210/fm.v26i1.10648

Keywords:

Artificial intelligence, algorithms, survey, CIOs, perceptions, expectations, public administration, Spain, Mexico

Abstract

This article presents a study about artificial intelligence (AI) policy based on the perceptions, expectations, and challenges/opportunities given by chief information officers (CIOs). In general, publications about AI in the public sector relies on experiences, cases, ideas, and results from the private sector. Our study stands out from the need of defining a distinctive approach to AI in the public sector, gathering primary (and comparative) data from different countries, and assessing the key role of CIOs to frame federal/national AI policies and strategies. This article reports three research questions, including three dimensions of analysis: (1) perceptions regarding to the concept of AI in the public sector; (2) expectations about the development of AI in the public sector; and, (3) challenges and opportunities of AI in the public sector. This exploratory study presents the results of a survey administered to federal/national ministerial government CIOs in ministries of Mexico and Spain. Our descriptive statistical (and exploratory) analysis provides an overall approach to our dimensions, exploratory answering the research questions of the study. Our data supports the existence of different governance models and policy priorities in different countries. Also, these results might inform research in this same area and will help senior officials to assess the national AI policies actually in process of design and implementation in different national/federal, regional/state, and local/municipal contexts.

Author Biographies

J. Ignacio Criado, Associate Professor / Senior Lecturer in Political Science and Public Administration, Department of Political Science and International Relations, at Universidad Autónoma de Madrid

J. Ignacio Criado (PhD) is an Associate Professor / Senior Lecturer in Political Science and Public Administration, Department of Political Science and International Relations, at Universidad Autónoma de Madrid. His articles have been published in leading journals, including Government Information Quarterly, Social Science Computer Review, First Monday, Information Polity, Local Government Studies, International Journal of Public Administration, or International Journal of Public Sector Management (among others). His research interests include algorithmic governance and artificial intelligence in the public sector; open government and policies for transparency, participation and public innovation; and social media and big data in government.

Rodrigo Sandoval-Almazan, Associate Professor at the Political Sciences and Social Sciences Department in the Autonomous University of the State of Mexico

Rodrigo Sandoval-Almazan (PhD) is Associate Professor at the Political Sciences and Social Sciences Department in the Autonomous University of the State of Mexico, in Toluca City.  Dr. Sandoval-Almazan is the author or co-author of articles in Government Information Quarterly, Information Polity, First Monday, Government; Journal of Information Technology for Development; Journal of Organizational Computing and Electronic Commerce; International Journal of E-Politics IJEP. His research interests includes: artificial intelligence, social media in government. public innovation, digital government and open government.

David Valle-Cruz , Assistant Professor at the Computing Engineering Department in the Autonomous University of the State of Mexico

David Valle-Cruz (PhD) is Professor at the Computing Engineering Department in the Autonomous University of the State of Mexico, in Toluca City.  Dr. David Valle-Cruz is the author or co-author of articles in Government Information Quarterly, Information Polity, First Monday, International Journal of Public Sector Management, International Journal of Public Administration in the Digital Age, and Digital Government: Research and Practice. His research is related to Applied Artificial Intelligence and Emerging Technologies in Government.

Edgar A. Ruvalcaba-Gómez, Research Professor at the Universidad de Guadalajara, with affiliation to the Department of Public Policy, and Coordinator in the Research Institute in Public Policies and Government

Edgar Alejandro Ruvalcaba-Gómez (PhD) is a Research Professor at the Universidad de Guadalajara, with affiliation to the Department of Public Policy, and Coordinator in the Research Institute in Public Policies and Government. He holds a PhD in Law, Government and Public Policy from Autonomous University of Madrid, Spain. Edgar conducts research related to Open Government, Transparency, Citizen Participation, Open Data, Corruption, Digital Government and Artificial Intelligence, and Public Innovation.

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Published

2020-12-26

How to Cite

Criado, J. I., Sandoval-Almazan, R. ., Valle-Cruz , D., & Ruvalcaba-Gómez, E. A. . (2020). Chief information officers’ perceptions about artificial intelligence: A comparative study of implications and challenges for the public sector. First Monday, 26(1). https://doi.org/10.5210/fm.v26i1.10648