FFJ-AIR LIQUIDE WORKSHOPInternational Symposiumon Compliance for Algorithmic Law(SCALGO 2022)
01 December 2022 | 13:00 - 19:00 / 02 December 2022 | 9:00 - 13:00 (Paris Time)
Campus Condorcet - Bâtiment de recherche Sud
5 cours des Humanités, 93320 Aubervilliers
Registration for onsite and online: https://forms.gle/3VPQHVEz93e5m9cq7
Contact: events_ffj@ehess.fr
Along with advances of artificial intelligence into society, a situation has emerged in which artificial intelligenceis closely related to the real world and legal and ethical problems caused by artificial intelligence naturally
occur. In particular, AI systems by which governments replace human officials (we call here “algorithmiclaw”) receives a critical concern since these decisions made by the AI system will be legally effective toenforce people. Along with frequent uses of such AI systems, algorithmic law will become a great matter forcivil rights. Therefore, civil control of algorithmic law should be prepared urgently. To solve these problems,
we request governments to expose program source of such AI systems to the public. However, there is aserious technical problem about this check of algorithmic law. Currently, analysis of software code is done
manually. However, according to increasing number of such software, it would be very difficult to find aproblem by human. For this reason, automatic compliance check of legal and ethical norms for algorithmic
law should be investigated. In this symposium, we are discussing how we automate compliance check ofnorms for algorithmic law with interdisciplinary researchers from computer science, AI, standardization,
law and ethics. The topics includes but not limited to:(1) Automatic mechanisms for compliance check of algorithmic law(2) How to extract information related with compliance from program source of algorithmic law(3) How to formalize abstract compliance norms

Programme
December 1st | Room 0.030
13.00 | Opening Remarks
Sébastien Lechevalier (EHESS-FFJ)
Ken Satoh (National Institute of Informatics)
Air Liquide representative (to be confirmed)

13.10 | Session 1
Algorithmic Law and Related Problems
David Restrepo Amariles (HEC)
Compliance Mechanism using AI for Algorithmic Law
Ken Satoh (National Institute of Informatics)
Break

14:45 | Session 2
Can AI Meet Any of the Challenges of Regulatory Compliance?
Randy Goebel (University of Alberta)
Algorithmic Law as Computational Argumentation
Bart Verheij (University of Groningen)Break

16:30 | Session 3
The Compliance Gap in Data Supply Chains: Smart Contracts as aCompliance Technology
Pablo M. Baquero (HEC)Can AI Technical Standards Save Human Rights?
Grégory Lewkowicz (Université libre de Bruxelles)
Break

18:00 | Round Table
chaired by David Restrepo Amariles (HEC)
19:00 | Cocktail

Programme
December 2nd | Room 0.031
09:00 | Session 4
GDPR-120 : an Expert Annotated Dataset for Privacy Policy Compliance
Assessment under the EU GDPR
Raphael Gyory (Université libre de Bruxelles)
Leveraging Knowledge Graphs for GDPR Compliance: Smart Cities andInsurance Use Cases
Anelia Kurteva (University of Delft)Break

10:45 | Session 4
Modelling, Analysing and Enacting Compliance Requirements in Digital
Processes: A Process-Management Perspective
Hugo A. López (Technical University of Denmark)Making Abstract Legal Norms Ready to be Formalised
Georg Borges (Saaland University)
Ethical Ccompliance Principles and Representations
Gauvain Bourgne (Sorbonne University)

13:00 | Closing remarks & Lunch

Participants (alphabetical order)
Pablo Baquero (HEC)
Pablo Marcello Baquero is Assistant Professor at HEC Paris and a Fellow at the
Hi! Paris Center on Data Analytics and Artificial Intelligence for Science, Businessand Society. He is a member of the Smart Law Hub at HEC Paris, is involved indifferent interdisciplinary academic communities focused on law and technology
and collaborates closely with scholars across different disciplines, in projects at
the intersection between law and AI. His research examines how legal institutions
and technologies can support practices of innovation in a socially and economically
inclusive way, contributing to disseminate to most firms the opportunities to
produce in the frontiers of innovation and extending the benefits of advanced
technologies to society at large in a lawful and ethical way. His first book, entitled“Networks of Collaborative Contracts for Innovation”, has been published by Hart. Before becoming an
Assistant Professor, he was a Postdoctoral Research Fellow at HEC Paris. He holds a Ph.D. in Law from the
University of Cambridge, a LL.M. from Harvard Law School and a LL.B. from the Federal University of Rio
Grande do Sul, Brazil.

The Compliance Gap in Data Supply Chains: Smart Contracts as aCompliance Technology
Pablo M. Baquero (HEC Paris), David R. Amariles (HEC Paris), Daniel Amyot (University of Ottawa)
This paper investigates the use of smart contracts as a means to improve compliance with data protection
laws by harnessing the back end of data supply chains. The privacy literature has focused predominantly on
B2C relationships (front end data processing) to assess corporate compliance with data protection laws andexplored the use of technologies primarily as a means to empower data subjects vis-à-vis data processors.
This article shifts the perspective. First, it shows that the effective implementation of data subjects’ rights
hinges upon the capacity of data processors to monitor compliance in back end processing, i.e., the data
supply chain. Second, it spells out the way smart contracts can contribute to bridge the compliance gap in
the data supply chain which currently hinders data controllers from effectively monitoring data documents
and practices across the networks of subcontractors. Indeed, while data is processed in an iterative anddynamic manner through a wide variety of means by actors within and across companies in the supply
chain (e.g. controller, processors and sub-processors), the legal instruments utilized to ensure compliance(framework contracts, data protection addendums, data protection impact assessments, technical andsecurity documents, etc.) are dispersed, static, convoluted and legalistic, ultimately lacking the capacity tooperationalize data protection across different management levels (legal, technical, business, etc.). This
paper offers a concrete case study testing the properties of the ‘Symboleo’ formal contract language in adataset composed of contractual documents used in the data supply chain of a network of IT companies.
The paper concludes with the challenges laying ahead to narrow the compliance gap and highlights the how
smart contracts can evolve to become effective compliance tools in data protection.

Georg Borges (Saaland University)
Georg Borges is a Professor of Civil Law, Legal Informatics, German andInternational Business Law and Legal Theory and the managing director of theInstitute for Legal Informatics at Saarland University, Germany. From 2004 to 2014,
he was Professor of Law at Ruhr-University Bochum. Beside this, he was alsoa Judge at the State Court of Appeals, Hamm Circuit. As an expert on Business
Law with a focus on IT Law and on law and informatics, Prof. Borges authored
several books and numerous articles in the field of IT law. Prof. Borges is involvedin numerous projects in the field of IT and legal informatics. Currently, a focus of his
interest is on formalizing legal norms, in particular with regard to autonomous driving.

Making abstract legal norms ready to be formalised
In this presentation, some challenges and (possible) solutions regarding the formalisation of abstract legal
norms shall be discussed. Such norms often contain broad/vague concepts which can be interpreted invarious ways, allowing for their application in several different scenarios. In each of these scenarios, theconcrete meaning of these broad/vague concepts has to be specified by the agent applying the law.
Because of their semantic complexity and context-dependency, such broad/vague concepts pose a major
challenge for the formalisation of abstract norms. One possible approach to solving this problem is to first
specify the broad/vague concepts contained in them, thus reducing these abstract norms to more concrete
rules entailed by them. These rules would then be used as a basis for the actual formalisation. Thus, insteadof formalising the abstract norms themselves, one would only formalise the concrete rules implied by them.
By analysing selected examples from Road Traffic Law, the paper will demonstrate the method and discuss
the potential advantages and limitations of this approach.

Gauvain Bourgne (Sorbonne University)
Gauvain Bourgne has been an associate professor in artificial intelligence at
Sorbonne Université since 2012. After a PhD on collaborative hypothesis finding
defended in 2008, he worked for 3 years at the National Institute of Informatics
in Tokyo on logic programming, abductive reasoning and distributed knowledge
discovery before joining the ACASA team in LIP6. HIs research domain includes
knowledge representation and reasoning, logic programming and computational
ethics. His current work focuses on modeling the reasoning of cognitive agents, with
an emphasis on collective and ethical aspects.

Ethical compliance principles and representations
This presentation will discuss ethical compliance checking. It will present some of the approaches used
for assessing permissibility of actions and their foundation in normative ethics and introduce some of thechallenges in representation or reasoning raised at different levels, such as the need for establishing actual
causes or to take into account multiple values.

Randy Goebel (University of Alberta)
R.G. (Randy) Goebel is currently professor of Computing Science in the Departmentof Computing Science at the University of Alberta and Fellow and co-founder ofthe Alberta Machine Intelligence Institute (Amii). He received the B.Sc. (Computer
Science), M.Sc. (Computing Science), and Ph.D. (Computer Science) from the
Universities of Regina, Alberta, and British Columbia, respectively.
Professor Goebel's theoretical work on abduction, hypothetical reasoning andbelief revision is internationally well known; his recent research is focused on theformalization of visualization and explainable artificial intelligence (XAI), especiallyin applications in autonomous driving, legal reasoning, and precision health. He has
worked on optimization, algorithm complexity, systems biology, natural language processing, and automatedreasoning.
Randy has previously held faculty appointments at the University of Waterloo, University of Tokyo,
Multimedia University (Kuala Lumpur), Hokkaido University (Sapporo), visiting researcher engagements at
National Institute of Informatics (Tokyo), DFKI (Germany), and NICTA (now Data61, Australia); he is actively
involved in collaborative research projects in Canada, Japan, Germany, France, the UK, and China.

Can AI meet any of the challenges of regulatory compliance?
The current state of AI research requires more attention to principled application of AI to social sciences,including the area of regulatory compliance. Since regulatory compliance has such a broad scope, I will try
and sketch a portion of that scope that can be conveyed to AI researchers, with the hope of encouraging
cross disciplinary teams to multiply the value of those teams to create better value and more precisely
connect to AI research challenges.

Raphael Gyori (Université Libre de Bruxelles)
Raphael Gyory is a PhD candidate at IRIDIA, the Artificial Intelligence researchlaboratory of the Université Libre de Bruxelles. His research focuses on artificial
intelligence in the field of law, and more specifically on the development ofalgorithmic solutions for legal compliance. He practiced as a lawyer before
undertaking his research in engineering.

GDPR-120 : an expert annotated dataset for privacy policy complianceassessment under the EU GDPR

Raphael Gyori (Université Libre de Bruxelles), Sébastien Meeùs (Université de Montréal, Université
Libre de Bruxelles)
In this article, we present our work on GDPR-120, an expert annotated dataset for privacy policy complianceassessment under the EU General Data Protection Regulation, based on our own research on a conceptualmodel of mandatory information and tasks of compliance checking. The dataset consists of 120 policies, 109
possible label categories, and, currently, approximately 91,000 units of crowedsourced label units. We follow
a 3-step methodology already adopted by other authors, where labels are first crowdsourced, then integrated
and finally reviewed by legal experts. We are currently working on the integration stage and estimate that wewill deliver about 15,000 training label units. Our goal is to provide the legal NLP community with a new task
to train deep learning algorithms on an issue that affects the protection of citizens' fundamental rights.

Anelia Kurteva (University of Delft)
Anelia’s doctoral research, at the Semantic Technology Institute (STI) Innsbruck,
Department of Computer Science, University of Innsbruck, Austria, focused on
supporting machines and humans in making sense of informed consent for sensor
data sharing in smart cities, with knowledge graphs. In collaboration with hercolleagues from the smashHit1 Horizon 2020 and CampaNeo2 FFG projects, Anelia
helped bridge the gap between the Semantic Web, Human-Computer Interaction
and Privacy fields by exploring the applications of knowledge graphs for informed
consent solicitation and GDPR compliance. Prior to that, Anelia received an MSc in
Advanced Computer Science from Cardiff University, The United Kingdom, where
she also completed a BSc in Computer Science and Visual Computing.
urrently, Anelia is a postdoctoral researcher at the Faculty of Industrial Design Engineering (IDE), TU Delft,
The Netherlands. Anelia’s research, on the RePlanIT3 project, explores the ways the Semantic Web can help
facilitate trusted, transparent and FAIR ICT data sharing in order to encourage the further implementation of
the Circular Economy.
Anelia is interested in exploring the utilisation of AI and the Semantic Web for Big Data in the privacy andsustainability domains.

Leveraging Knowledge Graphs for GDPR Compliance: Smart Cities andInsurance Use Cases
The General Data Protection Regulation (GDPR) triggered a major technological shift towards greatertransparency and responsibility in data sharing. An emphasis has been put on the rights of individuals,
especially European citizens, regarding their personal data sharing. Despite the fact that data sharing
has been a widely researched topic for years, there is a lack of solutions that enable the transparent
implementation of consent in an easily interpretable manner for both humans and machines in compliancewith GDPR. Further, almost five years after the acceptance of the legislation, organisations still facesignificant challenges such as demonstrating compliance (or audibility) and automated complianceverification due to the complex and dynamic nature of consent, as well as the scale at which complianceverificationmust be performed.
This talk will present a knowledge graph-based approach for consent management in the smart cities andinsurance domains. It will present an overview of how Semantic Web technologies, namely ontologies andknowledge graphs, can be used to semantically represent informed consent through its life-cycle and forautomated GDPR compliance verification and audibility.

Sébastien Lechevalier (Professor at EHESS/President of
the Fondation France-Japon de l'EHESS)
Sébastien Lechevalier is an Economist and a Professor at EHESS (Schoolof Advanced Studies in the Social Sciences, Paris), specialised in Japanese
economy and Asian Capitalisms. He is also founder and president of the Fondation
FranceJapon de l’EHESS (FFJ).Trained as a labor economist, he has extensively
published on various dimensions of the Japanese economy, in comparative
perspective, including: “Lessons from the Japanese experience. Towards
an alternative economic policy?” (ENS Editions, 2016). His book, The Great
Transformation of Japanese Capitalism (Routledge, 2014) was published in threelanguagesand has been cited as one of the most influential ones on the Japanese
economy published during the last decade. Other research interests include innovation (Innovation beyond
technology, Springer, 2019), industrial policies (“Financialization and industrial policies in Japan and Korea:
Evolving complementarities and loss of state capabilities” in Structural Change and Economic Dynamics,
2019, Vol. 48), and inequalities & redistribution (“Decomposing Preference for Redistribution. Beyond theTrans-Atlantic Perspective”, forthcoming). For more than a decade, he is involved in SASE, as a participant
and an organizer.

Gregory Lewkowicz (Université Libre de Bruxelles)
Gregory Lewkowicz is a professor at the Université libre de Bruxelles (ULB) andthe director of the Smart Law Hub at the Perelman Centre of the Faculty of Law. He
is principal investigator at the Artificial Intelligence Institute for the Common Good(FARI) in Brussels and Koyre Senior Research Fellow in Business Law & Artificial
Intelligence at the Université of Nice Sophia Antipolis. He teaches the course “Smart
Law: Indicators, Algorithms and Big Data” at Science Po Paris School of Law. He
teaches also at Paris II Panthéon-Assas and HEC-Paris. He is a member of theexternal advisory board of AI4Belgium, of the “Club des juristes” digital taskforce(Paris) and a founding member of the international platform of French-speaking
experts in law & AI (Geneva).

Can AI Technical Standards Save Human Rights?
During the last 20 years, the evidence has been piling up that digital technology play a role in significant
violations of human rights by public and private actors and that available legal remedies are ill-equipped toaddress the issue. In this context, it comes as no surprise that the two building blocks of digital technologies– data and artificial intelligence – are the targets of new rules and regulations. Several of them impose
new human rights-related compliance obligations for systems using artificial intelligence and for digital
infrastructures. In this regulatory context, this paper claims that technical standards will inevitably become
the spearhead of human rights in the digital society and highlights a set of issues that need to be addressed.

Hugo A. Lopez (Technical University of Denmark)
Hugo A. López is a tenure-track assistant professor at the Technical University ofDenmark (DTU), in the Computer Science Department. His research objectives
involve the maturing of a new generation of process technologies that can adapt tocitizen needs, while still be compliant with regulations and laws. His main research
topics are process-oriented technologies, their theoretical formalisation, theiradoption via software tools (engineering), and their empirical validation. Previously
he have had research positions at Copenhagen University, the IT university(Denmark) and the University of Lisbon (Portugal).

Modelling, Analysing and Enacting Compliance Requirements in Digital
Processes: A process-management perspective
Digitalisation of the public sector is not an optional path: given the amount of work, number of cases andlack of transparency, state organisations decide to invest in different type of digital tools, many of them
involving AI-powered processes. However, not all AI-powered implementations support the knowledgeintensive nature of administrative case work, leading to implementations that are inflexible and opaque in thedecisions recommended, or that replicate undesirable biases. In our talk we will discuss how the combinationof two variants of AI that can support the flexible nature of case work while at the same time being compliant
with regulations. In our research, we explore the use of declarative process models and natural language
processing to 1) generate digital representations of legislations, 2) analyse the compliance of existing caseswith regulations, and 3) generate case-management applications that support the flexible nature of casework. Our talk will discuss the results achieved so far, but, equally importantly, stresses the importance ofan inter-disciplinary and inter-sectorial approach to digitalisation and compliance involving law, design andcomputer science.

David Restrepo Amariles (HEC)
David Restrepo Amariles is Associate Professor of Data Law and Artificial
Intelligence at HEC Paris. He is co-Director of research on SMART Law (Scientific
Mathematical, Algorithmic, Risk and Technology driven law) at the DATA IA Instituteand director of the project Smart Contracts and Regulatory Technologies in theAutonomy through Cyberjustice Technologies Programme.
His work analyses the transformations of law and regulation in the global and digitalsociety with a special focus on the fields of privacy, financial law, international
business transactions and corporate social responsibility. His research combines
approaches from legal theory, computer science and informatics, empirical legal
studies, and science and technology studies. He has conducted several industrial
projects with public partners such as the European Commission and the French Supreme Court, as well aswith private partners such as Atos, Baker McKenzie, Dechert LLP, Natixis, among others.

Ken Satoh (2022 FFJ/Air Liquide fellow, National Institute of Informatics)
Ken Satoh is a full professor of Principles of Informatics Research Division, NII(National Institute of Informatics), and Sokendai (The Graduate University of
Advanced Studies), Japan. He worked with Fujitsu 1981-1995 and then was an
associate professor of Hokkaido University till 2001. He also studied law at thelaw school of University of Tokyo in 2006-2009 and passed Japanese bar exam in2017. His main research interest is logical foundations of Artificial Intelligence (AI)and application of AI to law. He recently proposed juris-informatics which is a newresearch field combining informatics and law.

Bart Verheij (University of Groningen)Bart Verheij's research and teaching focus on the connections between knowledge,
data and reasoning, as a contribution to responsible artificial intelligence. He uses
an argumentation perspective, inspired by the domain of law. Bart Verheij holds thechair of artificial intelligence and argumentation as full professor at the Universityof Groningen. He is head of the department of Artificial Intelligence in the Bernoulli
Institute of Mathematics, Computer Science and Artificial Intelligence, Faculty of
Science and Engineering.

Algorithmic Law as Computational Argumentation
In these days of successes in artificial intelligence, an old question returns: are we close to building acomputer judge? Reading the news the answer seems to be yes. Are we indeed close to a fully algorithmic
perspective on law? In the talk we take the perspective of computational argumentation to analyze
algorithmic law. We discuss historical and current developments. As a conclusion, it is suggested thatalgorithmic law will be hybrid in nature, in two ways. First, algorithmic law necessarily involves various
techniques and skills involving knowledge, reasoning, learning and language, in a hybrid mix. Also highquality algorithmic law will depend on the strengths of both humans and machines in a hybrid collaboration.