Report No. 29: The Mobility and Integration of People with Disabilities into the Labour Market

Report based on a study conducted for the European Parliament, Bonn 2010 (95 pages)

Slave to the Algorithm? Why a \u27Right to an Explanation\u27 Is Probably Not the Remedy You Are Looking For

Algorithms, particularly machine learning (ML) algorithms, are increasingly important to individuals’ lives, but have caused a range of concerns revolving mainly around unfairness, discrimination and opacity. Transparency in the form of a “right to an explanation” has emerged as a compellingly attractive remedy since it intuitively promises to open the algorithmic “black box” to promote challenge, redress, and hopefully heightened accountability. Amidst the general furore over algorithmic bias we describe, any remedy in a storm has looked attractive. However, we argue that a right to an explanation in the EU General Data Protection Regulation (GDPR) is unlikely to present a complete remedy to algorithmic harms, particularly in some of the core “algorithmic war stories” that have shaped recent attitudes in this domain. Firstly, the law is restrictive, unclear, or even paradoxical concerning when any explanation-related right can be triggered. Secondly, even navigating this, the legal conception of explanations as “meaningful information about the logic of processing” may not be provided by the kind of ML “explanations” computer scientists have developed, partially in response. ML explanations are restricted both by the type of explanation sought, the dimensionality of the domain and the type of user seeking an explanation. However, “subject-centric explanations (SCEs) focussing on particular regions of a model around a query show promise for interactive exploration, as do explanation systems based on learning a model from outside rather than taking it apart (pedagogical versus decompositional explanations) in dodging developers\u27 worries of intellectual property or trade secrets disclosure. Based on our analysis, we fear that the search for a “right to an explanation” in the GDPR may be at best distracting, and at worst nurture a new kind of “transparency fallacy.” But all is not lost. We argue that other parts of the GDPR related (i) to the right to erasure ( right to be forgotten ) and the right to data portability; and (ii) to privacy by design, Data Protection Impact Assessments and certification and privacy seals, may have the seeds we can use to make algorithms more responsible, explicable, and human-centered

Data access problems in the emerging digital agriculture sector:What role for EU competition law enforcement and regulatory intervention?

The proliferation of IoT implementations and the utilization of advanced data analytics technologies in agriculture have initiated a paradigm shift from traditional agricultural decision-making to data-driven ‘smart farming’. By collecting and processing data from farms, agricultural technology providers offer services for farmers to detect issues early, track developments, and take swift action in their operations. This promises higher productivity, reduced input usage, and minimal environmental impact. However, this digital transformation is accompanied by a set of challenges related to data access and control, which hinder competition, innovation, and trust among stakeholders. Effectively addressing the complexities surrounding access to agricultural data is crucial for fostering competition, driving innovation, and building trust in digital technologies in emerging markets for digital agriculture services. In this context, the overall research question of this dissertation is the following: What are the prominent problems deriving from the ambiguities about ag-data access and control from the perspective of facilitating the development of a competitive Digital Agriculture sector, and to what extent are the EU regulatory initiatives and/or traditional EU competition law enforcement able to address these challenges?Accordingly, this dissertation provides a comprehensive legal analysis on the effectiveness of the voluntary rule-making initiatives, the traditional EU competition law enforcement and/or (existing and possible future) EU regulatory initiatives in addressing these challenges. The methodological approach is mainly doctrinal legal research in addition to conceptual analysis, comparative legal research and law and economics considerations. This research identified the prominent data access related problems in the emerging Digital Agriculture sector, and discussed the adequacy of the existing legal frameworks and voluntary rulemaking initiatives in Europe. Existing frameworks are not able to remove the underlying reasons for the sectoral issues although the recent Data Act proposal is a significant step forward. As a result, this research argues that follow-up sector specific regulation is needed, and it offers a set of conceptual and regulatory suggestions. It proposes a nuanced data access regime tailored to the unique characteristics of the Digital Agriculture sector. The study also highlights the potential synergies among various tools, such as ex-ante sectoral rules, a common European agricultural data space (CEADS) as a technical data access infrastructure, and traditional EU competition law enforcement as a safety net for unpredictable developments. In particular, the thesis proposes avoiding the concept of data "ownership" that is widely advocated by the sectoral literature and suggests linking data access rights to "farm units" rather than individual farmers or companies to ensure continuous access to ag-data sets by actual operators of the related farms. Also, unlike exclusive ownership understanding, access rights design does not preclude broader data re-use possibilities. To address broader data access needs in the farm-to-fork chain, the establishment of sectoral authorities with managerial and regulatory powers, running the CEADS and determining data re-use conditions, is recommended. As designing future-proof and tech-neutral legal design might not be possible, it is highlighted that traditional competition law enforcement can play a complementary role in addressing dynamic challenges, but it needs to update its traditional assessment criteria in the age of ‘Big Data’ to more accurately assess the competition concerns and to provide more effective remedies in the digital age.The findings of this research have potential implications for European Union policymakers, legislators, supervisory authorities, and sectoral stakeholders. By shedding light on sector-specific issues, this thesis aims to contribute to the development of a coherent and effective legal framework for holistic agricultural data governance in Europe. Unlocking the potential of Digital Agriculture and promoting sustainable and efficient smart farming practices are critical for the benefit of society as a whole

Data access problems in the emerging digital agriculture sector:What role for EU competition law enforcement and regulatory intervention?

The proliferation of IoT implementations and the utilization of advanced data analytics technologies in agriculture have initiated a paradigm shift from traditional agricultural decision-making to data-driven ‘smart farming’. By collecting and processing data from farms, agricultural technology providers offer services for farmers to detect issues early, track developments, and take swift action in their operations. This promises higher productivity, reduced input usage, and minimal environmental impact. However, this digital transformation is accompanied by a set of challenges related to data access and control, which hinder competition, innovation, and trust among stakeholders. Effectively addressing the complexities surrounding access to agricultural data is crucial for fostering competition, driving innovation, and building trust in digital technologies in emerging markets for digital agriculture services. In this context, the overall research question of this dissertation is the following: What are the prominent problems deriving from the ambiguities about ag-data access and control from the perspective of facilitating the development of a competitive Digital Agriculture sector, and to what extent are the EU regulatory initiatives and/or traditional EU competition law enforcement able to address these challenges?Accordingly, this dissertation provides a comprehensive legal analysis on the effectiveness of the voluntary rule-making initiatives, the traditional EU competition law enforcement and/or (existing and possible future) EU regulatory initiatives in addressing these challenges. The methodological approach is mainly doctrinal legal research in addition to conceptual analysis, comparative legal research and law and economics considerations. This research identified the prominent data access related problems in the emerging Digital Agriculture sector, and discussed the adequacy of the existing legal frameworks and voluntary rulemaking initiatives in Europe. Existing frameworks are not able to remove the underlying reasons for the sectoral issues although the recent Data Act proposal is a significant step forward. As a result, this research argues that follow-up sector specific regulation is needed, and it offers a set of conceptual and regulatory suggestions. It proposes a nuanced data access regime tailored to the unique characteristics of the Digital Agriculture sector. The study also highlights the potential synergies among various tools, such as ex-ante sectoral rules, a common European agricultural data space (CEADS) as a technical data access infrastructure, and traditional EU competition law enforcement as a safety net for unpredictable developments. In particular, the thesis proposes avoiding the concept of data "ownership" that is widely advocated by the sectoral literature and suggests linking data access rights to "farm units" rather than individual farmers or companies to ensure continuous access to ag-data sets by actual operators of the related farms. Also, unlike exclusive ownership understanding, access rights design does not preclude broader data re-use possibilities. To address broader data access needs in the farm-to-fork chain, the establishment of sectoral authorities with managerial and regulatory powers, running the CEADS and determining data re-use conditions, is recommended. As designing future-proof and tech-neutral legal design might not be possible, it is highlighted that traditional competition law enforcement can play a complementary role in addressing dynamic challenges, but it needs to update its traditional assessment criteria in the age of ‘Big Data’ to more accurately assess the competition concerns and to provide more effective remedies in the digital age.The findings of this research have potential implications for European Union policymakers, legislators, supervisory authorities, and sectoral stakeholders. By shedding light on sector-specific issues, this thesis aims to contribute to the development of a coherent and effective legal framework for holistic agricultural data governance in Europe. Unlocking the potential of Digital Agriculture and promoting sustainable and efficient smart farming practices are critical for the benefit of society as a whole

Artificial intelligence: the end of legal protection of personal data and intellectual property? : research on the countering effects of data protection and IPR on the regulation of artificial intelligence systems

Artificial Intelligence systems have gained notoriety for changing (and having a great potential) to further change the way we live. The use of AI impacts the rights and freedoms of natural persons necessitating the revision of various laws relevant to AI. This research considers the intersection of data protection and intellectual property law as it impacts the rights and freedoms of natural persons. This research argues that data protection and intellectual property law interrelate in such a manner that the (non) regulation of one legal field might (negatively) impact the other. This research examines some of these issues, (including data reidentification) and further proposes the redefinition of the concept of personal data as a means of ensuring that the application of data protection and intellectual property law to AI does not limit the development, adoption, and use of AI