Mitisha Gaur at Digital Legal Talks and LawTomation Days

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 Mitisha Gaur, ESR with the LeADS Project, recently presented at which took place on the 15th of September in Utrecth, NL. Mitisha is researching predictive justice applications deployed across courts and government bodies to augment and support decision making practices as well as how such predictive justice systems interact within the legal and regulatory ecosystem. The presentation was titled Predictive Justice and human oversight under the EU’s proposed Artificial Intelligence Act. The presentation was focused on the provisions of the EU’s draft AI Act dealing with human oversight requirements. The presentation delved into an analysis of the human oversight requirements while detailing the material gaps in the human oversight strategy adopted by the draft AI Act. Finally, a specific plan focused on ensuring human oversight across 4 primary stakeholders namely (1) Developers of AI systems; (2) Deployers of AI Systems; (3) Users of the AI System and; (4) the Impact Population on whom the computational results of the AI system are applied was shared.

 

 

Subsequently on the 29th of September, Mitisha also presented her work at the LawTomation Days 2023 Conference organised by the IE Law School. The presentation titled Regulating Algorithmic Justice Applications under the EU’s proposed Artificial Intelligence Act: A Critical Analysis took a panoramic view of the provisions of the draft AI Act which are applicable to the high-risk AI systems (which includes predictive justice systems) as classified under the draft AI Act. The presentation was oriented around discussing the various compliance requirements, specifically for predictive justice application and whether they are adequate to allow for predictive justice systems being developed and deployed for perform or augment functions on behalf of public authorities and judicial bodies. The core discussion revolved around the provisions pertaining to risk management systems, fundamental rights impact assessment, transparency and provision of information, human oversight, accuracy-robustness and cybersecurity and finally the obligations of deployers of high-risk AI systems.

LeADS Working Paper Series Part VI: Data Collaboratives with the Use of Decentralised Learning – an Interdisciplinary Perspective on Data Governance

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Data Collaboratives with the Use of Decentralised Learning – an Interdisciplinary Perspective on Data Governance

Maciej Zuziak (ESR 6), Onntje Hinrichs (ESR 13), and Aizhan Abdrasulova (ESR 12) are the authors of the paper “Data Collaboratives with the Use of Decentralised Learning – an Interdisciplinary Perspective on Data Governance”. The paper constitutes a collaboration across three different  LeADS Crossroads, i. e. Privacy vs Intellectual Property (Onntje) Data ownership (Aizhan) and Empowering Individuals (Maciej) as well as across disciplines: whereas Onntje and Aizhan focused their research on questions related to data ownership and how conflicted interests in data can be resolved, Maciej is examining various methods of distributed learning.

Their different research interests came together in this paper which exemplified that an interdisciplinary perspective from both law and data science is necessary to tackle urgent questions in the data-dependent economy. Finding appropriate Data Governance solutions that are capable of achieving data policy objectives while at the same time being compliant with EU law requires an interdisciplinary understanding of how both disciplines can complement each other. Their Working Paper cooperation thus perfectly exemplifies the LeADS approach. The paper was presented at this year’s ACM Conference on Fairness, Accountability, and Transparency (FAccT) in Chicago.

 

Abstract of the Working Paper

The endeavor to find appropriate data governance frameworks capable of reconciling conflicting interests in data has dramatically gained importance across disciplines and has been discussed among legal scholars, computer scientists as well as policy-makers alike. The predominant part of the current discussion is centered around the challenging task of creating a data governance framework where data is ‘as open as possible and as closed as necessary’. In this article, we elaborate on modern approaches to data governance and their limitations. It analyses how propositions evolved from property rights in data towards the creation of data access and data sharing obligations and how the corresponding debates reflect the difficulty of developing approaches that reconcile seemingly opposite objectives – such as giving individuals and businesses more control over ‘their’ data while at the same time ensuring its availability to different stakeholders. Furthermore, we propose a wider acknowledgement of data collaboratives powered by decentralised learning techniques as a possible remedy to the shortcomings of current data governance schemes. Hence, we propose a mild formalization of the set of existing technological solutions that could inform existing approaches to data governance issues. By adopting an interdisciplinary perspective on data governance, this article highlights how innovative technological solutions can enhance control over data while at the same time ensuring its availability to other stakeholders and thereby contributing to the achievement of the policy goals of the European Strategy for Data.

LeADS Working Paper Series Part V: From Data Governance by Design to Data Governance as a Service

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From Data Governance by Design to Data Governance as a Service

The WoPa titled “From Data Governance by Design to Data Governance as a Service” is a result of collaborative work between three ESRs from the LeADS project, Armend Duzha (ESR10) and Christos Magkos (ESR11) from University of Piraeus Research Centre (UPRC), and Louis Sahi (ESR2) from University of Toulouse III (UT3), under the supervision of Dr Manolis Alexakis from UPRC and Dr Ali Mohamed Kandi from UT3. Hence, it was designed and conceptualized as a multidisciplinary work, spanning from data processing and management to security and privacy-preservation areas. This is directly related to the research topics of the ESR fellows involved, but most importantly the study carried out as part of the Crossroads (ESRs 10 and 11 are part of Crossroad 4 “Empowering Individuals” while ESR 2 is part of Crossroad 2 “Trust”). Specifically, during the second iteration of the Crossroads, a more in-deep analysis of the state of the art and assessment of existing methods were conducted first individually and then shared among the teams.

Abstract of the Working Paper

Nowadays, companies and governments collect data along every phase of a product/service life cycle. The data is acquired and stored in various and continuous ways, contributing to a large and unique data fingerprint for every product/service in use. Thus, establishing policies, processes and procedures (P3) around data and subsequently enacting those to compile and use such data for effective management and decision-making is extremely important. Data governance (DG) plays an essential role in a dynamic environment with multiple entities and actors, complex IT infrastructures, and heterogeneous administrative domains. Indeed, not only is it beneficial for existing products/services/processes, but it can also support appropriate adjustments during the design of new ones. This research provides an overview of the existing literature and current state-of-the-art in the domain of data processing and government aiming to evaluate existing approaches and to investigate their limitations. To this extent, this study introduces a novel approach for data governance as a service (DGaaS), which provides a framework for (private or public) organizations that facilitate alignment with their vision, goals and legal requirements. Finally, it discusses the potential implication of DGaaS in the smart city and healthcare sectors.

LeADS Working Paper Series Part IV: Data Access And Re-Use In The European Legal Framework For Data, From The GDPR To The Proposed Data Act: The Case Of Vehicle Data

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Data Access And Re-Use In The European Legal Framework For Data, From The GDPR To The Proposed Data Act: The Case Of Vehicle Data

In their working paper on “Data Access and Re-Use in the European Legal Framework for Data, from the GDPR to the Proposed Data Act: The Case of Vehicle Data” ESRs Tommaso Crepax, Mitisha Gaur, and Barbara Lazarotto explore the topic of data access and portability of vehicles’ black boxes, which are electronic data recorders that record a vehicle’s speed, breaking, and other information in the event of a crash. The paper centers the analysis on three main stakeholders: consumers, the public sector, and insurance companies, each having a distinct interest in data. It identifies a number of legal enablers and blockers that could affect data access and portability. The topic of this paper is closely related to the individual topics of the ESRs since it covers topics such as data sharing, access, and portability between

different public and private stakeholders, and how this data can be used to feed algorithms that will generate driver’s profiles. Furthermore, it can be considered a case study that explores the topics of Crossroad 1 “Privacy vs Intellectual Property” and of Crossroad 3 “Data Ownership”, analyzing how black box data can be accessed based on privacy regulations and how individuals can take more control of their vehicle data. The tension of Crossroad 1 becomes evident in the case of black box data in the debate over whether individuals have the right to access their own black box data, and whether companies have the right to use that data for commercial purposes. Questions related to data ownership (crossroad 3) are particularly important in the case of black box data because the data can be used to create driver profiles, which could be used for a variety of purposes, such as assessing driver risk and providing personalized safety recommendations.

The paper concludes by providing valuable insights and recommendations for enhancing data access and reuse while improving transparency and accountability in the process. The authors present a methodology for comparing and evaluating the degree of access conferred by various regulations and put it to practical use to assess how much data is currently left out from access by the existing legislation, how much of such data is covered by the Data Act, and ultimately, how much still remains inaccessible for reuse. The proposed framework can deliver on the promises of access and reuse, but there are promising research areas that have not been extensively discussed, including topics such as competition, data governance and markets, and quality of data.

Abstract of the Working Paper

This article delves into the difficulties and opportunities associated with the acquisition, sharing, and re-purposing of vehicle data, particularly information derived from black boxes used by insurance companies and event data recorders installed by manufacturers. While this data is usually utilized by insurers and car makers, the authors contend that consumers, rival firms, and public institutions may also profit from accessing the data for objectives such as data portability between insurance companies, traffic and transportation management, and the development of intelligent mobility solutions. Among other regulations, the authors examine the proposed Data Act as the European chosen champion to address the legal and technical hurdles surrounding the reuse of privately held corporate data, including privacy and intellectual property, competition, and data interoperability issues. The text also offers an overview of the sorts of data obtained through vehicle recording systems and their potential benefits for various stakeholders. The authors present a methodology for comparing and evaluating, in an ordinal fashion, the degree of access conferred by various regulations and put it to practical use to assess how much data is currently left out from access by the existing legislation, how much of such data is covered by the Data Act, and ultimately, how much still remains inaccessible for reuse.