AI Ethics and Regulation: a Practitioner's Point of View
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The Key Concepts of Ethics of Artificial Intelligence
This is the author's version of the work. The definite version was published in Vakkuri, V., Abrahamsson, P. 2018, June. The Key Concepts of Ethics of Artificial Intelligence. In 2018 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC). IEEE. http://dx.doi.org/10.1109/ICE.2018.8436265 The Key Concepts of Ethics of Artificial Intelligence A Keyword based Systematic Mapping Study Ville Vakkuri Pekka Abrahamsson [https://orcid.org/0000-0002-1550-1110] [https://orcid.org/0000-0002-4360-2226] Faculty of Information Technology Faculty of Information Technology University of Jyväskylä University of Jyväskylä Jyväskylä, Finland Jyväskylä, Finland [email protected] [email protected] Keywords — Artificial Intelligence; Ethics; AI ethics; Systematic Mapping Study Abstract — The growing influence and decision-making capacities of Autonomous systems and Artificial Intelligence in our lives force us to consider the values embedded in these systems. But how ethics should be implemented into these systems? In this study, the solution is seen on philosophical conceptualization as a framework to form practical implementation model for ethics of AI. To take the first steps on conceptualization main concepts used on the field needs to be identified. A keyword based Systematic Mapping Study (SMS) on the keywords used in AI and ethics was conducted to help in identifying, defying and comparing main concepts used in current AI ethics discourse. Out of 1062 papers retrieved SMS discovered 37 re-occurring keywords in 83 academic papers. We suggest that the focus on finding keywords is the first step in guiding and providing direction for future research in the AI ethics field. -
Comparing the Expert Survey and Citation Impact Journal Ranking
Author's personal copy Journal of Informetrics 5 (2011) 629–648 Contents lists available at ScienceDirect Journal of Informetrics j ournal homepage: www.elsevier.com/locate/joi Comparing the expert survey and citation impact journal ranking methods: Example from the field of Artificial Intelligence a,∗ b Alexander Serenko , Michael Dohan a Faculty of Business Administration, Lakehead University, 955 Oliver Road, Thunder Bay, Ontario P7B 5E1, Canada b DeGroote School of Business, McMaster University, 1280 Main St. West, Hamilton, Ontario L8S 4M4, Canada a r t i c l e i n f o a b s t r a c t Article history: The purpose of this study is to: (1) develop a ranking of peer-reviewed AI journals; (2) Received 1 April 2011 compare the consistency of journal rankings developed with two dominant ranking tech- Received in revised form 18 May 2011 niques, expert surveys and journal impact measures; and (3) investigate the consistency of Accepted 8 June 2011 journal ranking scores assigned by different categories of expert judges. The ranking was constructed based on the survey of 873 active AI researchers who ranked the overall quality Keywords: of 182 peer-reviewed AI journals. It is concluded that expert surveys and citation impact Artificial Intelligence journal ranking methods cannot be used as substitutes. Instead, they should be used as com- Journal ranking plementary approaches. The key problem of the expert survey ranking technique is that in Academic journal Google Scholar their ranking decisions, respondents are strongly influenced by their current research inter- Survey ests. As a result, their scores merely reflect their present research preferences rather than Citation impact an objective assessment of each journal’s quality. -
Submission Data 2015 Minds and Machines: Journal for Artificial Intelligence, Philosophy and Cognitive Sciences (Submitted As A
Submission Data 2015 Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences (Submitted as a comparator for Artificial Intelligence and Law) Bastin Tony Roy Savarimuthu, Guido Governatori, Stephen Cranefield, Marta Poblet Balcell, Pompeu Casanovas 1 Journal Details Request Type: Comparator Title: Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences Acronym: Current Rank: A Publisher Name: Springer ISSN Print Version: 0924-6495 ISSN Electronic Version: 1572-8641 2 Journal Data Journal Webpage URL: http://link.springer.com/journal/11023 Issues/year: 4 Papers in each issue: 10,10,7,5 Papers/year: 32 Pages in each paper: 11,25,23,37,1,24,30,18,24,17,1,3 Table of contents URL: http://link.springer.com/journal/11023/24/4/page/1 Table of contents URL: http://link.springer.com/journal/11023/24/3/page/1 Page Format: single Example paper URL: http://link.springer.com/article/10.1007/ s11023-012-9285-z DBLP journal record URL: http://dblp.uni-trier.de/db/journals/mima/mima17.html 3 Editorial Board 3.1 Editorial Board Board Listing URL: http://www.springer.com/computer/ai/journal/11023? detailsPage=editorialBoard Board Members with h-indices: Andy ClarkH-index:50 https://scholar.google.co.nz/citations?user=FYrnmlIAAAAJ&hl=en Jack Copeland (NO GS) 1 Robert CumminsH-index:50 https://scholar.google.co.nz/citations?user=ShgxnZYAAAAJ&hl=en David DanksH-index:14 https://scholar.google.co.nz/citations?user=1lORpNsAAAAJ&hl=en Luciano FloridiH-index:44 https://scholar.google.co.nz/citations?user=jZdTOaoAAAAJ&hl=en Clark GlymourH-index:NA Stephan HartmannH-index:18 https://scholar.google.co.nz/citations?user=p1- uh0gAAAAJ&hl=en Phillip Johnson-LairdH-index:78 https://scholar.google.co.nz/citations?user=ZF2fKzQAAAAJ&hl=en&oi=ao Frank Keil, NO GS Arthur Paul PedersenH-index:5 https://scholar.google.co.nz/citations?user=L WCGQgAAAAJ&hl=en William J. -
Global Research on Artificial Intelligence from 1990–2014
International Journal of Geo-Information Review Global Research on Artificial Intelligence from 1990–2014: Spatially-Explicit Bibliometric Analysis Jiqiang Niu 1,*, Wenwu Tang 2,3, Feng Xu 1, Xiaoyan Zhou 4 and Yanan Song 4 1 School of Urban and Environmental Science, Xinyang Normal University, Xinyang 464000, China; [email protected] 2 Department of Geography and Earth Sciences, University of North Carolina at Charlotte, Charlotte, NC 28262, USA; [email protected] 3 Center for Applied Geographic Information Science, University of North Carolina at Charlotte, Charlotte, NC 28262, USA 4 School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China; [email protected] (X.Z.); [email protected] (Y.S.) * Correspondence: [email protected]; Tel.: +86-188-3767-2366 Academic Editors: Kathleen Stewart, Alexander Klippel and Wolfgang Kainz Received: 5 February 2016; Accepted: 10 May 2016; Published: 16 May 2016 Abstract: In this article, we conducted the evaluation of artificial intelligence research from 1990–2014 by using bibliometric analysis. We introduced spatial analysis and social network analysis as geographic information retrieval methods for spatially-explicit bibliometric analysis. This study is based on the analysis of data obtained from database of the Science Citation Index Expanded (SCI-Expanded) and Conference Proceedings Citation Index-Science (CPCI-S). Our results revealed scientific outputs, subject categories and main journals, author productivity and geographic distribution, international productivity and collaboration, and hot issues and research trends. The growth of article outputs in artificial intelligence research has exploded since the 1990s, along with increasing collaboration, reference, and citations. Computer science and engineering were the most frequently-used subject categories in artificial intelligence studies.