[AISWorld] Call for papers for the Special Issue in Artificial Intelligence and Public Administration: Actors, Governance, and Policies Journal Public Policy and Administration

[J. Ignacio Criado]

Dear colleagues:



We enclosed a *call for papers *for the special issue in *Artificial
Intelligence and Public Administration: Actors, Governance, and Policies,
Journal Public Policy and Administration*.



We do think this may be of interest for this network.



Best regards,



Ramon, Rodrigo and Ignacio


*Public Policy and Administration*. *Call for Papers*

*Special Issue. Artificial Intelligence and Public Administration: Actors,
Governance, and Policies*



*Public Policy and Administration **(PPA) *is the journal of the UK Joint
University Council (JUC) Public Administration Committee (PAC). PPA aims to
publish original peer-reviewed material within the broad field of public
policy and administration. This journal is a member of the Committee on
Publication Ethics (COPE) <http://publicationethics.org/>. PPA is indexed
in Clarivate Analytics' Social Sciences Citation Index (SSCI) (Public
Administration Q2 15/48, 2020, JIF 3.386).



Special Issue Guest Editors

Dr. J. Ignacio Criado (Department of Political Science and International
Relations, Universidad Autónoma de Madrid, Spain)

Dr. Rodrigo Sandoval-Almazán (Political and Social Sciences School,
Autonomous University of the State of Mexico, Toluca, Estado de México,
México)

Dr. J. Ramon Gil-Garcia (Center for Technology in Government and
Rockefeller College of Public Affairs & Policy, University at Albany, State
University of New York, USA).



*Public Policy and Administration *is seeking scholarly manuscripts for a
special issue on *Artificial Intelligence and Public Administration:
Actors, Governance, and Policy* (tentative scheduled for publication in
2023).



AI and algorithms applied in public sector organizations have been scarcely
studied empirically and systematically. Therefore, the purpose of this
special issue on *Artificial Intelligence and Public Administration:
Actors, Governance, and Policy* is to study the use and implications of AI
and algorithms in public administration and policy regarding different
dimensions and levels of applications, including a particular focus on
empirical results about actors involved in the adoption process, governance
strategies, and policy areas of utilization of those applications.



Hence, this special issue on *Artificial Intelligence and Public
Administration: Actors, Governance and Policy* is open to research based on
any kind of technology or system based on algorithms used in the public
sector. The main objectives of this Special Issue on *Artificial
Intelligence and Public Administration: Actors, Governance, and Policy* are
the following.



• To explore different AI strategies and policies from different countries
and regions around the world.

• To link strategies of AI to different governance models in different
contexts worldwide and to identify the different common characteristics,
values, and ideas that share AI policies from around the world.

• To understand the human implications of AI and algorithms in public
sector governance and management.

• To identify the best AI cases and practices in public administration
worldwide.

• To assess the most essential areas of development within AI in public
policy and considering different policy domains.

• To analyze some critical measures adopted by government around the world
to implement IA in the public sector.

• To define and propose models of governance of AI based on key actors
identified in different contexts.

• To emphasize the role of ethics and human rights in AI for public
services.



This special issue will welcome contributions from different perspectives
and research areas related to *Artificial Intelligence and Public
Administration: Actors, Governance, and Policy*. It is oriented to bring
together international, high-quality research to produce theoretical and
empirical insights on the adoption, use, results, and impacts of AI in
public administration and policy. This special issue aims to provide a
broad perspective on the possibilities of AI and algorithms to foster a new
generation of public policies and services and transform public sector
organizations and processes.



This special issue welcomes conceptual and empirical research, including
papers based on qualitative, quantitative, and mixed-methods research
strategies.
Topics may include, but are not limited to, the following:



   - Theories of AI and public sector management.
   - Public values and ethical issues connected to AI in public policy and
   administration.
   - Public policies and strategies for implementation of AI to promote
   more citizen-centric public services.
   - Human aspects related with the development of AI in public services.
   - Data and information management based on AI systems and applications.
   - Challenges and results from the use of AI in public sector management.



*Submission procedure and important dates*



The submission procedure will follow the usual norms and regulations of *Public
Policy and Administration**and SAGE*. The issue is expected to be ready for
publication in 2023 (indicative), based on the following timeline:



Call for Papers (CfP): Beginning 2022

Article proposal due (not more than 1000 words): February 28, 2022

Proposal notification sent: April 1, 2022

Full articles submissions due: July 15, 2022



*The review process will follow the usual times and course of PPA.*



*Article proposals and inquiries* should be directly submitted to *guest
editors via email*: J. Ignacio Criado: ignacio.criado at uam.es Rodrigo
Sandoval-Almazan rsandovala at uaemex.mx and J Ramon Gil-Garcia
jgil-garcia at albany.edu



It is expected that, *prior to full article submissions*, *guest editors* may
conduct an informal online workshop and provide authors with development
feedback.



The full document with the Call for Papers is available *Here*
<https://www.dropbox.com/s/swj13wrt6j6eob5/SpecialIssue_CfP_ArtificialIntelligence_PublicPolicyAdministration.pdf?dl=0>
 (https://bit.ly/3rcTgRV).