-------- Forwarded Message -------- Subject: [AISWorld] CFP: AI, Data Analytics & Automated Decision Making Track of EGOV-CeDEM-ePart 2020 Date: Mon, 27 Jan 2020 14:11:38 +0000 From: Habin Lee (Staff) Habin.Lee@brunel.ac.uk To: aisworld@lists.aisnet.org aisworld@lists.aisnet.org
EGOV-CeDEM-ePart 2020 Linköping University, Sweden 31 August (Monday) - 2 September (Wednesday), 2020 http://dgsociety.org/egov-2020/
Important dates:
* (Hard) deadline for submissions: 17 March 2020 * Notification of acceptance: 30 April 2020 * PhD Colloquium deadline for submissions: May 1, 2020 * Poster submission deadline (non-anonymous-camera ready) 10 May 2020 * Poster acceptance 25 May 2020 * Camera-ready paper submission and author registration: 1 June 2020 * Conference: 31 August -2 September 2020 * PhD Colloquium: 30 August 2020
Paper Submission system: https://easychair.org/account/signin?l=1FmpftqPuXNhKpmP6n3a9t#https://easychair.org/account/signin?l=1FmpftqPuXNhKpmP6n3a9t
AI, Data Analytics & Automated Decision Making Track
As the Fourth Industrial Revolution creates new tools for conducting economic activities in the private sector, it also provides the public sector with tools for creating public value and engaging in digital transformation. While ICT has been fundamental for digitalising public services, the public sector increasingly relies on Internet of Things (IoT), Artificial Intelligence (AI), (Big) Data Analytics (BDA), Blockchain, 5G, Adaptive manufacturing / 3D technologies, wireless and related technologies to accelerate and increase the impact of digital transformation. As citizens are spending more time on the Internet, their digital footprints are becoming easier to collect, forming massive interconnected networks of data. Innovative methods and tools to analyse such data and understand policy implications are in urgent demand. In particular, open data and open government initiatives can create bigger synergy and impact when integrated with new technologies. However, the use of new technologies by government has some serious ethical and policy implications. Complementing or replacing human-made public service with AI, automating decisions of consequence to people's lives, harvesting interconnected data about individuals, etc. raise the risk that exclusion, injustice and privacy violations can happen on a massive scale. Decision made through (Big) Data Analytics and policy modelling tool may generate optimal solutions from an economic perspective, but not from a social inclusion perspective, or give rise to transparency and fairness concerns. Privacy and security issues with regards to citizens' everyday digital footprints also have legal and policy implications. This track invites papers that can advance theoretical, practical and policy questions on those issues. Papers are expected to address the topics including but not limited to:
* Adoption of robotics-based public services * AI and labour displacement in the public sector * AI applications in the public sector * AI and policy monitoring and analytics * AI-enabled smart cities * AI in government and discriminatory bias * Big data analytics for policy modelling * Co-creation via AI and big data analytics * Computational analysis methods for open data * Consequential decisions and AI in government * Decision support system for policy makers * Digital transformation via AI * Disruptive services in public sector * Impact of AI on social cohesion * IoT applications in public services * Privacy issues in big data analytics * Qualitative policy modelling * Quality of AI-enabled public services
Track Co-chairs
* Habin Lee, Brunel University London, United Kingdom * Euripidis Loukis, University of Aegean, Greece * Evangelos Kalampokis, CERTH, Greece
Habin Lee Professor in Data Analytics and Operations Management Divisional Lead, Organizations and People Director, College Research Centre for Digital Governance and Sustainable Operations Management T +44(0)1895 267414 | E Habin.Lee@brunel.ac.ukmailto:Habin.Lee@brunel.ac.uk
Brunel University London Brunel Business School Brunel University London, Uxbridge, UB8 3PH, United Kingdom T +44(0)1895 274000
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