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AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings

The rush to understand new socio-economic contexts created by the wide adoption of AI is justified by its far-ranging consequences, spanning almost every walk of life. Yet, the public sector's predicament is a tragic double bind: its obligations to protect citizens from potential algorithmic ha...

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Detalles Bibliográficos
Autores principales: Kuziemski, Maciej, Misuraca, Gianluca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7164913/
https://www.ncbi.nlm.nih.gov/pubmed/32313360
http://dx.doi.org/10.1016/j.telpol.2020.101976
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author Kuziemski, Maciej
Misuraca, Gianluca
author_facet Kuziemski, Maciej
Misuraca, Gianluca
author_sort Kuziemski, Maciej
collection PubMed
description The rush to understand new socio-economic contexts created by the wide adoption of AI is justified by its far-ranging consequences, spanning almost every walk of life. Yet, the public sector's predicament is a tragic double bind: its obligations to protect citizens from potential algorithmic harms are at odds with the temptation to increase its own efficiency - or in other words - to govern algorithms, while governing by algorithms. Whether such dual role is even possible, has been a matter of debate, the challenge stemming from algorithms' intrinsic properties, that make them distinct from other digital solutions, long embraced by the governments, create externalities that rule-based programming lacks. As the pressures to deploy automated decision making systems in the public sector become prevalent, this paper aims to examine how the use of AI in the public sector in relation to existing data governance regimes and national regulatory practices can be intensifying existing power asymmetries. To this end, investigating the legal and policy instruments associated with the use of AI for strenghtening the immigration process control system in Canada; “optimising” the employment services” in Poland, and personalising the digital service experience in Finland, the paper advocates for the need of a common framework to evaluate the potential impact of the use of AI in the public sector. In this regard, it discusses the specific effects of automated decision support systems on public services and the growing expectations for governments to play a more prevalent role in the digital society and to ensure that the potential of technology is harnessed, while negative effects are controlled and possibly avoided. This is of particular importance in light of the current COVID-19 emergency crisis where AI and the underpinning regulatory framework of data ecosystems, have become crucial policy issues as more and more innovations are based on large scale data collections from digital devices, and the real-time accessibility of information and services, contact and relationships between institutions and citizens could strengthen – or undermine - trust in governance systems and democracy.
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spelling pubmed-71649132020-04-20 AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings Kuziemski, Maciej Misuraca, Gianluca Telecomm Policy Article The rush to understand new socio-economic contexts created by the wide adoption of AI is justified by its far-ranging consequences, spanning almost every walk of life. Yet, the public sector's predicament is a tragic double bind: its obligations to protect citizens from potential algorithmic harms are at odds with the temptation to increase its own efficiency - or in other words - to govern algorithms, while governing by algorithms. Whether such dual role is even possible, has been a matter of debate, the challenge stemming from algorithms' intrinsic properties, that make them distinct from other digital solutions, long embraced by the governments, create externalities that rule-based programming lacks. As the pressures to deploy automated decision making systems in the public sector become prevalent, this paper aims to examine how the use of AI in the public sector in relation to existing data governance regimes and national regulatory practices can be intensifying existing power asymmetries. To this end, investigating the legal and policy instruments associated with the use of AI for strenghtening the immigration process control system in Canada; “optimising” the employment services” in Poland, and personalising the digital service experience in Finland, the paper advocates for the need of a common framework to evaluate the potential impact of the use of AI in the public sector. In this regard, it discusses the specific effects of automated decision support systems on public services and the growing expectations for governments to play a more prevalent role in the digital society and to ensure that the potential of technology is harnessed, while negative effects are controlled and possibly avoided. This is of particular importance in light of the current COVID-19 emergency crisis where AI and the underpinning regulatory framework of data ecosystems, have become crucial policy issues as more and more innovations are based on large scale data collections from digital devices, and the real-time accessibility of information and services, contact and relationships between institutions and citizens could strengthen – or undermine - trust in governance systems and democracy. Elsevier Ltd. 2020-07 2020-04-17 /pmc/articles/PMC7164913/ /pubmed/32313360 http://dx.doi.org/10.1016/j.telpol.2020.101976 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Kuziemski, Maciej
Misuraca, Gianluca
AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings
title AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings
title_full AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings
title_fullStr AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings
title_full_unstemmed AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings
title_short AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings
title_sort ai governance in the public sector: three tales from the frontiers of automated decision-making in democratic settings
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7164913/
https://www.ncbi.nlm.nih.gov/pubmed/32313360
http://dx.doi.org/10.1016/j.telpol.2020.101976
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