{"title":"Systematic and axiological capacities in artificial intelligence applied in the public sector","authors":"Edgar A. Ruvalcaba-Gomez","doi":"10.1177/09520767231170321","DOIUrl":null,"url":null,"abstract":"Artificial Intelligence (AI) as a technological development is being implemented in the public sector with the intention of improving service delivery, as well as to help solve complex problems. However, there is a wide range of capabilities that AI can perform and that public officials perceive and implement in different ways. This paper aims to describe and analyze some categories into which AI capabilities in the public sector are divided. Using an Exploratory Factor Analysis (EFA), our results show that the capabilities of AI from the perspective of public officials can be classified into two aspects: systematic factors and axiological factors. Systematic factors are related to the analysis and behavior of data, including monitoring, analyzing, interacting, remembering, and anticipation. Axiological factors refer to the impacts of values, ethics, and decisions, including acting, feeling, moralizing, creating, and deciding capacities. This categorization of AI capabilities in the public sector sheds light on the perception of public officials about the implementation of this technological development.","PeriodicalId":47076,"journal":{"name":"Public Policy and Administration","volume":" ","pages":""},"PeriodicalIF":2.9000,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Public Policy and Administration","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1177/09520767231170321","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC ADMINISTRATION","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial Intelligence (AI) as a technological development is being implemented in the public sector with the intention of improving service delivery, as well as to help solve complex problems. However, there is a wide range of capabilities that AI can perform and that public officials perceive and implement in different ways. This paper aims to describe and analyze some categories into which AI capabilities in the public sector are divided. Using an Exploratory Factor Analysis (EFA), our results show that the capabilities of AI from the perspective of public officials can be classified into two aspects: systematic factors and axiological factors. Systematic factors are related to the analysis and behavior of data, including monitoring, analyzing, interacting, remembering, and anticipation. Axiological factors refer to the impacts of values, ethics, and decisions, including acting, feeling, moralizing, creating, and deciding capacities. This categorization of AI capabilities in the public sector sheds light on the perception of public officials about the implementation of this technological development.
期刊介绍:
Public Policy and Administration is the journal of the UK Joint University Council (JUC) Public Administration Committee (PAC). The journal aims to publish original peer-reviewed material within the broad field of public policy and administration. This includes recent developments in research, scholarship and practice within public policy, public administration, government, public management, administrative theory, administrative history, and administrative politics. The journal seeks to foster a pluralistic approach to the study of public policy and administration. International in readership, Public Policy and Administration welcomes submissions for anywhere in the world, from both academic and practitioner communities.