[AISWorld] SSCR Journal Special Issue on AI in Government
rm.digi at cbs.dk
Tue Feb 26 04:30:41 EST 2019
Apologies for cross-posting.
Social Science Computer Review
Special Issue on Artificial Intelligence in Government
Special Issue Guest Editors:
Rony Medaglia, Copenhagen Business School (rony at cbs.dk<mailto:rony at cbs.dk>)
Theresa A. Pardo, State University of New York
J. Ramon Gil-Garcia, State University of New York
Artificial Intelligence (AI) technologies have been defined as any device that perceives its environment and takes actions that maximize its chance of success at some goal (Russell & Norvig, 2016). Such technologies include, among others, machine learning, rule-based systems, natural language processing, and speech recognition (Eggers, Schatsky, & Viechnicki, 2017).
After a series of rises and falls in popularity, AI technologies are now experiencing a surge in diffusion, and are also beginning to be adopted in areas of the public sector (Desouza, 2018). These include, for instance, public education (Rockoff, Jacob, Kane, & Staiger, 2010), social policy (Chandler, Levitt, & List, 2011), public health regulation and healthcare provision (Kang, Kuznetsova, Luca, & Choi, 2013; Meskó, Hetényi, & Győrffy, 2018), law enforcement (Goldsmith & Crawford, 2014), and tax services (Nuance Communications, 2016).
Despite the wide array of areas of the public sector in which AI has potential transformative effects, research on AI and government is still scarce, and assumptions on the impacts of AI in government are still far from conclusive. On the one hand, AI applications are seen as increasing efficiency and effectiveness by automating cognitive labour, freeing up high-value work, providing predictive capabilities for decision-making, and improving services to citizen queries (Eggers et al., 2017). On the other hand, the introduction of AI is accompanied by fears related to the destruction of jobs caused by automation (McClure, 2018), the infringements of privacy caused by digital surveillance (The Economist, 2016), and the reinforcement of biases in policy-making caused by algorithmic governance (Janssen & Kuk, 2016). Few existing empirical accounts have started to provide a general mapping of challenges of adopting AI in the public sector (Sun & Medaglia, 2018).
This Special Issue of the Social Science Computer Review calls for research that can unbox the potentials, challenges, impacts, and theoretical implications of AI in government. We welcome research from different social science perspectives, including Public Administration, Information Systems, Sociology, Information Science, and Management, that can combine relevant research foci, with rigorous methodological approaches. Interdisciplinary submissions and submission with novel theoretical implications are also encouraged.
Potential topics include (but are not limited to):
* Organizational Factors and Adoption Challenges of AI in Government
* AI for Public Policy and Services
* AI and Algorithmic Public Governance
* AI and Public Regulation
* AI, Data and Advanced Analytics in Government
* AI and Data Management and Stewardship in Government
* Maturity and Sustainability of AI in Government
* Smart Cities in the Age of AI
* The Ethics of AI in Government
* The Dark Side of AI in Government
* Theoretical Implications of AI in Government
The Special Issue will apply a two-step reviewing process.
* In the first step, we require the submission of an extended abstract of maximum 2000 words (excluding references) that presents the study’s research question(s), theoretical framework, methodology, preliminary and/or expected findings, and expected contributions to research and practice. This extended abstract is mandatory and will be used by the editors for selecting which abstracts will be invited to make full paper submission. The Guest Editors will make selections based on topic relevance, novelty, and potential contributions of the study.
* In the second step, the completed submissions will be managed by the Guest Editors, and will be reviewed by at least two expert reviewers per paper, in a double-blind process. The submissions will undergo a maximum of two rounds of review. Papers with a final acceptance are expected to be published online in the second half of 2020.
February 26, 2019 – Call issued
May 1, 2019 – Extended abstracts due (mandatory)
May 15, 2019 – Authors receive feedback on extended abstracts
September 1, 2019 – Submission of completed papers (23h59m Greenwich time)
December 1, 2019 – First round of reviews returned
March 1, 2020 – Revised papers submitted
May 1, 2020 – Second round of reviews returned
July 1, 2020 – Final revisions due
Second half of 2020 – Expected online publication date
Format and guidelines
Extended abstracts and completed papers are to be submitted to Ms. Iseul Choi at ichoi at albany.edu<mailto:ichoi at albany.edu>.
Completed papers may not exceed 10000 words (excluding references and appendices). Both extended abstracts and completed paper manuscripts must be submitted as a Word document, double-spaced, non-justified, in 12-point font. Tables and figures should be numbered and embedded in the text body. The reference style to be followed is the APA 6th edition.
Submitted papers should not be under review for any other journal or conference, should be significantly different from previously published work (at least 60% unpublished material), and should present original contributions. Duplicate submissions will be rejected. In case the manuscripts are an extension of previously published work (e.g., conference article), the authors need to disclose all information about the previous work upon submission.
If you have questions or concerns, please contact the lead editor, Rony Medaglia, at rony at cbs.dk<mailto:rony at cbs.dk>
About the Journal
Social Science Computer Review (SSCR) is an interdisciplinary journal covering social science instructional and research applications of computing, as well as societal impacts of information technology, and is in its 37th year of publication. In the most recent year for which data are available (2017), SSCR ranked 2/98 journals in its field (interdisciplinary social science); 20/105 in Computer Science, Interdisciplinary; and 14/88 in Information Science & Library Science. SSCR has an Impact Factor of 3.253.
About the Special Issue Guest Editors
Rony Medaglia is an Associate Professor at the Department of Digitalization of the Copenhagen Business School in Denmark, and the President of the Association for Information System (AIS) Special Interest Group on e-Government (SIGe-Gov). Rony’s research focuses on digitalization in the public sector, from the perspectives of public policy, digital service provision, and citizen engagement.
Theresa A. Pardo is a full research Professor in Public Administration and Policy at the Rockefeller College of Public Affairs and Policy, and the Director of CTG UAlbany, University at Albany, State University of New York (SUNY). She has published over 130 articles, research reports, practice guides, book chapters and case studies, and is ranked among the top five scholars in her field in terms of productivity and citations to her published work.
J. Ramon Gil-Garcia is an Associate Professor of Public Administration and Policy and the Research Director of CTG Ualbany, University at Albany, State University of New York (SUNY). In 2009, he was considered the most prolific author in the field of digital government research worldwide and some of his publications are among the most cited in the field. His research interests include collaborative electronic government, inter-organizational information integration, smart cities and smart governments, adoption and implementation of emergent technologies, digital divide policies, and multi-method research approaches.
Chandler, D., Levitt, S. D., & List, J. A. (2011). Predicting and preventing shootings among at-risk youth. The American Economic Review, 101(3), 288–292.
Desouza, K. C. (2018). Delivering Artificial Intelligence in Government: Challenges and Opportunities. Washington, D.C.: IBM Center for The Business of Government. Retrieved from http://www.businessofgovernment.org/sites/default/files/Delivering%20Artificial%20Intelligence%20in%20Government_0.pdf
Eggers, W. D., Schatsky, D., & Viechnicki, P. (2017). AI-augmented government. Using cognitive technologies to redesign public sector work. Deloitte. Retrieved from https://dupress.deloitte.com/dup-us-en/focus/cognitive-technologies/artificial-intelligence-government.html
Goldsmith, S., & Crawford, S. (2014). The responsive city: Engaging communities through data-smart governance. San Francisco, CA: John Wiley & Sons.
Janssen, M., & Kuk, G. (2016). The challenges and limits of big data algorithms in technocratic governance. Government Information Quarterly, 33(3), 371–377.
Kang, J. S., Kuznetsova, P., Luca, M., & Choi, Y. (2013). Where Not to Eat? Improving Public Policy by Predicting Hygiene Inspections Using Online Reviews. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (pp. 1443–1448).
McClure, P. K. (2018). “You’re Fired,” Says the Robot: The Rise of Automation in the Workplace, Technophobes, and Fears of Unemployment. Social Science Computer Review, 36(2), 139–156.
Meskó, B., Hetényi, G., & Győrffy, Z. (2018). Will artificial intelligence solve the human resource crisis in healthcare? BMC Health Services Research, 18(1). https://doi.org/10.1186/s12913-018-3359-4
Nuance Communications. (2016). Australian Taxation Office Continues Transformation of the Digital Customer Experience by Launching Online Virtual Assistant with Nuance. Retrieved June 4, 2018, from https://www.nuance.com/about-us/newsroom/press-releases/ato-launches-nuance-nina-virtual-assistant.html
Rockoff, J. E., Jacob, B. A., Kane, T. J., & Staiger, D. O. (2010). Can You Recognize an Effective Teacher When You Recruit One? Education Finance and Policy, 6(1), 43–74.
Russell, S., & Norvig, P. (2016). Artificial Intelligence: A Modern Approach, Global Edition. Englewood Cliffs, NJ: Pearson Higher Ed.
Sun, T. Q., & Medaglia, R. (2018). Mapping the challenges of Artificial Intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly. https://doi.org/10.1016/j.giq.2018.09.008
The Economist. (2016). China invents the digital totalitarian state. Retrieved from https://www.economist.com/news/briefing/21711902-worrying-implications-its-social-credit-project-china-invents-digital-totalitarian
Associate Professor, PhD
Department of Digitalization
Copenhagen Business School
Tel.: +45 2479 4327
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