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Potential Use of Digital Assistants by Governments for Citizen Services: The Case of Germany

Authors:

Helmut KrcmarAuthors Info & Claims

dg.o '19: Proceedings of the 20th Annual International Conference on Digital Government Research

Pages 81 - 90

https://doi.org/10.1145/3325112.3325241

Published: 18 June 2019 Publication History

Abstract

The German government has recently announced a national strategy for making Germany one of the leading locations for artificial intelligence (AI) worldwide. While the AI technology has been around since 1950s, the rise of it has been inescapable over the past decades. Current developments and widespread applications of intelligent technologies show signs that they will become even more prevalent in our lives. In public administrations, AI can support faster decision-making and increase responsiveness leading to higher citizen satisfaction. Digital assistants can carry out a wide range of functions ranging from checking applications against fraud to approval of state benefits or other claims. Yet, no matter how groundbreaking the technology is, its acceptance by citizens is the ultimate criterion of success, as in the case of all services offered by governments. We argue careful consideration needs to be given to citizen perspective as AI projects have high deployment and maintenance costs. Based on a nationwide representative survey, this research aims to provide some initial insights on the perspective of citizens towards the potential use of digital assistants by the German government for citizen services.

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Cited By

Helmholz PNolte MSchmitt M(2024)AI in Public Governance: An Expert Survey on the Impact of Data Driven Decision Making in PoliticsSSRN Electronic Journal10.2139/ssrn.4787049Online publication date: 2024
https://doi.org/10.2139/ssrn.4787049
Lee Hui Shan AShankararaman VOuh E(2024)Enhancing Government Service Delivery: A Case Study of ACQAR Implementation and Lessons Learned from ChatGPT Integration in a Singapore Government AgencyProceedings of the 25th Annual International Conference on Digital Government Research10.1145/3657054.3657130(645-653)Online publication date: 11-Jun-2024
https://dl.acm.org/doi/10.1145/3657054.3657130
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dg.o '19: Proceedings of the 20th Annual International Conference on Digital Government Research

June 2019

533 pages

ISBN:9781450372046

DOI:10.1145/3325112

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 18 June 2019

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dg.o 2019

dg.o 2019: 20th Annual International Conference on Digital Government Research

June 18 - 20, 2019

Dubai, United Arab Emirates

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Cited By

Helmholz PNolte MSchmitt M(2024)AI in Public Governance: An Expert Survey on the Impact of Data Driven Decision Making in PoliticsSSRN Electronic Journal10.2139/ssrn.4787049Online publication date: 2024
https://doi.org/10.2139/ssrn.4787049
Lee Hui Shan AShankararaman VOuh E(2024)Enhancing Government Service Delivery: A Case Study of ACQAR Implementation and Lessons Learned from ChatGPT Integration in a Singapore Government AgencyProceedings of the 25th Annual International Conference on Digital Government Research10.1145/3657054.3657130(645-653)Online publication date: 11-Jun-2024
https://dl.acm.org/doi/10.1145/3657054.3657130
Wang SMin CLiang ZZhang YGao Q(2024)The Decision-Making by Citizens: Evaluating the Effects of Rule-driven and Learning-driven Automated Responders on Citizen-Initiated ContactComputers in Human Behavior10.1016/j.chb.2024.108413(108413)Online publication date: Aug-2024
https://doi.org/10.1016/j.chb.2024.108413
Lee Hui Shan AShankararaman VOuh E(2022)Learnings from a Pilot Hybrid Question Answering System: CQASProceedings of the 23rd Annual International Conference on Digital Government Research10.1145/3543434.3543661(437-439)Online publication date: 15-Jun-2022
https://dl.acm.org/doi/10.1145/3543434.3543661
Dreyling RTammet TPappel I(2022)Artificial Intelligence Use in e-Government Services: A Systematic Interdisciplinary Literature ReviewFuture Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications10.1007/978-981-19-8069-5_37(547-559)Online publication date: 20-Nov-2022
https://doi.org/10.1007/978-981-19-8069-5_37
Mohamad IHughes LDwivedi YAlalwan A(2022)AI Technologies for Delivering Government Services to Citizens: Benefits and ChallengesThe Role of Digital Technologies in Shaping the Post-Pandemic World10.1007/978-3-031-15342-6_4(38-57)Online publication date: 13-Sep-2022
https://dl.acm.org/doi/10.1007/978-3-031-15342-6_4
Guo JGuo JYang CWu YSun LKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)Shing: A Conversational Agent to Alert Customers of Suspected Online-payment Fraud with Empathetical Communication SkillsProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445129(1-11)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445129

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