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Artificial Intelligence for Democratic Innovation Linked Democracy: Artificial Intelligence for Democratic Innovation Marta Poblet, Pompeu Casanovas and Enric Plaza (eds.) Proceedings IJCAI 2017 Workshop Melbourne, Australia 19 August 2017 Linked Democracy: Artificial Intelligence for Democratic Innovation Proceedings of the IJCAI 2017 Workshop on Linked Democracy: Artificial Intelligence for Democratic Innovation Marta Poblet, Pompeu Casanovas and Enric Plaza (eds.) Melbourne, Australia 19 August 2017 With the support of: RMIT University La Trobe University UAB Institute of Law and Technology Artificial Intelligence Research Institute (IIIA-CSIC) Cover image: Adapted from ‘The Acropolis as viewed from the Mouseion Hill’ by Christophe Meneboeuf (Creative Commons Attribution-Share Alike 3.0 Unported) Copyright © 2017 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors. Foreword The Workshop on ‘Linked Democracy: Artificial Intelligence for Democratic Innovation’ is one of the official workshops of the International Joint Conference on Artificial Intelligence (IJCAI 2017) held in Melbourne (19-26 August 2017). The goal of this workshop is to provide a multidisciplinary forum to address questions such as: How to model the interactions between people, data, and digital tools that create new spaces and forms of civic action in the digital era? How to analyse emerging properties and types of knowledge in these contexts? How to design socio-technical systems that effectively leverage data and knowledge for deliberation (or other types of participation) and collective decision making? Can we design the meta-rules of the emergent ecosystems? The Workshop brings together participants from universities and research centers in Australia, New Zealand, Spain, Brazil, Israel, UK, and the USA. The workshop received 10 submissions, covering a number of different areas in AI (e.g. multi-agent systems and machine learning), economics, political sciences, and law. All submitted versions were reviewed by at least two members of the Program Committee. These proceedings finally include nine of these papers and an invited keynote speech by Patrick Keyzer.1 We sincerely thank the Program Committee members for reviewing all submitted papers and providing feedback to improve their revised versions. We are also grateful to the IJCAI 2017 chairs (Program Chair Carles Sierra, Workshops Chair Daniele Magazzeni and Local Arrangements co-Chair Andy Song) for their support in preparing this workshop. Last but not least, we would like to thank the participants who submitted their papers and afterwards produced the revised versions that are now composing these proceedings. Marta Poblet, Pompeu Casanovas, and Enric Plaza Workshop Chairs 1 The submission not published in this volume can be found at Cohensius, G., Mannor, S., Meir, R., Meirom, E., & Orda, A. (2017). Proxy Voting for Better Outcomes. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems: 858-866. Program Committee Tanja Aitamurto (Stanford University, US) Michal Araszkiewitz (University of Cracow, Poland) Amir Aryani (Australian National Data Service, AU) Thomas Bruce (Cornell University, US) Danièle Bourcier (CNRS, France) Alissa Centivany (University of Western Ontario, Canada) Joel Chan (Carnegie Mellon University, US) Yosem Companys (University of California Santa Barbara, US) Mathieu D’Aquin (Open University, UK) Louis de Koker (La Trobe University, AU) Virginia Dignum (Delft University, The Netherlands) Aldo Gangemi (LIPN-CNRS-Paris13-Sorbonne, France) Asunción Gómez-Pérez (UPM, Spain) Jorge González Conejero (UAB, Spain) Guido Governatori (Data61, CSIRO, AU) Juho Kim (KAIST, Korea) Sabrina Kirrane (Vienna University of Economics and Business, Austria) Mark Klein (MIT, US) Gilly Leshed (Cornell University, US) Karen Levy (Cornell University, US) Wolfgang Mayer (University of South Australia, AU) Brian McInnis (Cornell University, US) Tarik Nesh-Nash (Mundiapolis University, Morocco) Pablo Noriega (IIIA-CSIC, Spain) Danuta Mendelson (Deakin University, AU) Julian Padget (University of Bath, UK) Ugo Pagallo (University of Turin, Italy) Monica Palmirani (University of Bologna, Italy) Jeremy Pitt (Imperial College, UK) Iddo Porat (College of Law and Business, Israel) Jason Potts (RMIT University, AU) Victor Rodriguez Doncel (UPM, Spain) Magda Roszczynska-Kurasinska (University of Warsaw, Poland) Giovanni Sartor (European University Institute, Italy) Geoffrey Stokes (RMIT University, AU) Markus Stumpfner (University of South Australia, AU) Tom van Engers (University of Amsterdam, The Netherlands) Bart Verheij (University of Groningen, The Netherlands) Roland Vogl (Stanford University, US) Julian Waters-Lynch (RMIT University, AU) Mark Whiting (Carnegie Mellon University, US) Adam Wyner (University of Aberdeen, UK) John Zeleznikow (Victoria University, AU) Table of Contents Open Rights or Secret Risk Assessments? New Challenges for Public Law in an Age of Artificial Intelligence and the Law Patrick Keyzer (Keynote speech) …...………………..………….………………………………………….6-14 Towards a Linked Information Architecture for Integrated Law Enforcement Wolfgang Mayer, Markus Stumptner, Pompeu Casanovas and Louis de Koker …........15-37 Bounded-Monitor Placement in Normative Environments Guilherme Krzisch, Nir Oren, and Felipe Meneguzzi ……………………………………………...28-37 The Perils of Classifying Political Orientation From Text Hao Yan, Allen Lavoie, and Sanmay Das ………………………….……………………………………38-50 Democracy Models and Civic Technologies: Tensions, Trilemmas, and Trade-offs Marta Poblet and Enric Plaza…………………………………………………………..……………………51-62 The Economics of Crypto-democracy Darcy Allen, Chris Berg, Aaron Lane and Jason Potts………………………………...……………63-73 . Promoting Public Deliberation in Low Trust Environments: Australian Use Cases Liam Lander and Nichola Cooper ……………………………………………………………..…….…… 74-85 Intelligent Warning Systems: ‘Nudges’ as a Form of User control for Internet of Things Data Collection and Use Rachelle Bosua, Karin Clark, Megan Richardson and Jeb Webb……………………………… 86-97 Linked Democracy 3.0 – Global Machine Translated Legislation and Compliance in the Age of AI Sean Goltz ………………………………………………………………………………………..……………......98-105 Equal Access to Online Legal Information through Democratisation of Technology: A Myth? Sue Ann Yap ………...……………………………………………………..…………………………………...106-117 Open Rights or Secret Risk Assessments? New Challenges for Public Law in an Age of Artificial Intelligence and the Law Keynote Speech Patrick Keyzer1 1 La Trobe University, Bundoora, VIC 3086, Australia [email protected] 1 The Cautionary Tale of “Robo-Debt” Centrelink, Australia’s welfare agency, recently contacted the Commonwealth Scien- tific and Industrial Research Organisation, Australia’s leading public scientific agen- cy, and asked its “Data61” team to review its electronic data-matching system with the Australian Taxation Office, the “Online Compliance Intervention”. The purpose of the Online Compliance Intervention was to data-match tax records and welfare payment records, work out whether there were any discrepancies, and then correct them (Commonwealth Ombudsman, 2017). It makes sense for governments to ensure that welfare benefits are paid to people who are genuinely in need, and to ensure that benefits are not paid to people who have paid employment. Properly set up and oper- ated, such a system could help ensure that resources are most effectively deployed to prevent poverty and minimise welfare fraud. However this is not how things worked in practice, in a great many cases. Instead, from about midway through last year and well into this year, Centrelink’s data- matching system was conflating annual earnings figures from the Tax Office with fortnightly income profiles used by Centrelink to assess welfare payment needs. It transpires that the “Matching Techniques” Protocol deployed an algorithm to calcu- late totals for a number of financial years, but since Centrelink doesn’t return detailed fortnightly data about a given year’s earnings, the algorithm simply averaged the amounts over the relevant periods. This approach was prone to errors, particularly in circumstances where a beneficiary might have made transitions in and out of work (increasingly common in a casualised labour market). Regrettably, the errors produced by this defective approach were compounded by the administrative approach taken to the recoupment of the debts. Letters were sent out automatically, without any internal, human review of the relevant calculations. These identified debts of hundreds or even thousands of dollars and then required the recipients to contact Centrelink within 21 days to explain the discrepancy, or pay the debt under penalty of enforcement. The letters did not include contact telephone num- bers for the compliance team, so people seeking assistance contacted Centrelink through a general call line that resulted in long waiting times. It transpires that the call line was staffed by people who had little knowledge of the Online Compliance Intervention because they had not been trained. The characterisation of these letters has been a bone of contention. They were de- scribed by the departmental secretary in a subsequent Senate Inquiry as “clarification letters” – as providing opportunities for welfare beneficiaries to “clarify” the discrep- ancy between the identified debt and the beneficiary’s personal records. However to ensure that this “clarification”
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