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Digital Ethics Lab Yearbook Jakob Mökander Marta Ziosi Editors The 2021 Yearbook of the Digital Ethics Lab Digital Ethics Lab Yearbook Series Editors Luciano Floridi, Oxford Internet Institute, Digital Ethics Lab, University of Oxford, Oxford, UK Department of Legal Studies, University of Bologna, Bologna, Italy Mariarosaria Taddeo, Oxford Internet Institute, Digital Ethics Lab, University of Oxford, Oxford, UK The Alan Turing Institute, London, UK The Digital Ethics Lab Yearbook is an annual publication covering the ethical challenges posed by digital innovation. It provides an overview of the research from the Digital Ethics Lab at the Oxford Internet Institute. Volumes in the series aim to identify the benefits and enhance the positive opportunities of digital innovation as a force for good, and avoid or mitigate its risks and shortcomings. The volumes build on Oxford’s world leading expertise in conceptual design, horizon scanning, foresight analysis, and translational research on ethics, governance, and policy making. Jakob Mökander • Marta Ziosi Editors The 2021 Yearbook of the Digital Ethics Lab Editors Jakob Mökander Marta Ziosi Oxford Internet Institute Oxford Internet Institute University of Oxford University of Oxfordo Oxford, UK Oxford, UK Center for Information Technology Policy Princeton University Princeton, NJ, USA ISSN 2524-7719 ISSN 2524-7727 (electronic) Digital Ethics Lab Yearbook ISBN 978-3-031-09845-1 ISBN 978-3-031-09846-8 (eBook) https://doi.org/10.1007/978-3-031-09846-8 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface The field of digital ethics – whether understood as an academic discipline or an area of practice – is maturing. This process has both been propelled and reflected by two long-term trends. First, and most importantly, the focus of the discourse concerning how to design and use digital technologies is increasingly shifting from ‘soft ethics’ to ‘hard governance’. The second trend is an ongoing shift from ‘what’ to ‘how’, whereby abstract or ad-hoc approaches to AI governance are giving way to more concrete and systematic solutions. While these trends are neither new nor surpris- ing, the maturing of the field of digital ethics has, as we shall see, been accelerated by a series of recent events. Consider the shift in focus from soft to hard governance. While the latter is enforced by government institutions, the former relies on mechanisms that allow for some contextual flexibility, such as cultural norms and economic incentives. The plethora of ‘AI ethics’ guidelines or principles produced by regulators and technology providers alike in recent years, including the Ethics Guidelines for Trustworthy (AI HLEG, 2019), the Montreal Declaration for a Responsible Development of AI (University of Montreal, 2018), and the Beijing AI Principles (Beijing Academy of Artificial Intelligence, 2019), constitute soft governance. In contrast, the Artificial Intelligence Act (AIA) published by the European Commission (2021) is an example of hard governance (Mökander et al., 2021). The AIA is a unique milestone insofar as it is the first attempt to elaborate a general legal framework for AI carried out by any major economy. Yet, the AIA did not come as a surprise. Several recent initiatives and publications have foreshad- owed the arrival of hard legislation.1 Moreover, the need to manage the ethical challenges posed by autonomous and self-learning systems has been pressing and clear for a long time, and the fact that soft and hard mechanisms complement and rein- force each other is well established in the governance literature (Erdelyi & Goldsmith, 2018; Floridi, 2018). The AIA can thus be viewed as one example of how the focus in the field of digital ethics is shifting from soft to hard governance (Floridi, 2021). Following the same logic, the eventual imposition of hard 1 For example, the European Commission’s Whitepaper on AI (2020). v vi Preface legislation on the design and use of digital technologies is to be expected outside the EU as well – although the shape such legislation will take is likely to vary between different jurisdictions. A step in that direction was taken with the Algorithmic Accountability Act of 2022 (AAA), which was put before the U.S. Senate by the Office of Senator Ron Wyden (2022). The AAA calls on companies to conduct impact assessments for bias, accuracy, and other issues when designing or deploy- ing automated systems that make critical decisions with little or no human intervention (Mökander et al., 2022). That brings us to the second long-term trend, from theoretical to implemented solutions. While playing an important role in raising awareness of the ethical challenges associated with specific technologies, early works in the field of digital ethics remained largely abstract. Of course, the convergence around a set of high-level ethics principles to guide the design and use of digital technologies was a significant achievement in and of itself. However, researchers quickly established that technology providers lacked both incentives and translational tools to interpret, implement, and demonstrate adherence to abstract ethics principles, namely a link was missing from what to how (Morley et al., 2020; Taddeo & Floridi, 2018). In response to this critical knowledge gap, a rich literature has emerged on how organisations can ensure that the technologies they design or deploy are ethical, legal, and technically robust in practice (see e.g., AIEIG, 2020; Ayling & Chapman, 2021; Mökander & Axente, 2021; Morley et al., 2021). In these attempts to provide more detailed guidance, both policymakers and academic researchers have drawn upon established best practices to provide adequate assurance in adjacent fields, including quality manage- ment in systems engineering, auditing in the financial sector, and pre-market testing and approval procedures in safety-sensitive areas such as food and medical devices. Both trends discussed above are reflected in this volume: the fourth edition of the Digital Ethics Lab Yearbook. The shift from soft ethics to hard governance runs like a red thread through the first half of this volume and binds together seven chapters that otherwise cover a wide range of domains and geographic areas. In ‘The European Legislation on AI: A Brief Analysis of Its Philosophical Approach’, Luciano Floridi highlights some foundational aspects of the AIA and analyses the regulatory approach underpinning it; in ‘Informational Privacy with Chinese Characteristics’, Huw Roberts discusses the emergence of a new privacy protection regime in China; in ‘Lessons Learned from Co-governance Approaches – Developing Effective AI Policy in Europe’, Caitlin Corrigan demonstrates that addressing the ethical challenges posed by AI systems will require close collaboration between state and non-state actors; in ‘State-Firm Coordination in AI Governance’, Noah Schöppl discusses the role of states in digital governance and argues that national governments need to increase and coordinate their regulatory capabilities; in ‘The Impact of Australia’s News Media Bargaining Code on Journalism, Democracy, and the Battle to Regulate Big Tech’, Emmie Hine analyses the new Australian legislation designed to provide financial support to publishers and journalists in terms of its compatibility with the business models of big tech giants; in ‘App Store Governance: The Implications and Limitations of Duopolistic Dominance’, Josh Cowls and Jessica Morley discuss the challenges and tensions inherent to app store Preface vii governance; and in ‘A Legal Principles-Based Framework for AI Liability Regulation’, Massimo Durante and Luciano Floridi review the work of the European Commission’s Expert Group on Liability and New Technologies (2019) to show how it has started to lay the basis for a set of legal principles for an AI liability regime. Similarly, the nine chapters in the latter half of this volume are linked insofar as they concern concrete procedures for implementing digital governance in practice. In ‘The New Morality of Debt’, Nikita Aggarwal argues for the inadequacy of existing regulatory frameworks governing consumer lending in alleviating harms around privacy, autonomy, and dignity; in ‘Site of the Living Dead: Clarifying Our Moral Obligations Towards Digital Remains’, Mira Pijselman assesses the absence of a unified roadmap for how digital remains ought to be managed; in ‘The Statistics of Interpretable Machine Learning’, David Watson provides an in-depth survey of the affordances and constraints in the plethora of existing interpretable machine learning approaches; in ‘Formalising Trade-Offs Beyond Algorithmic Fairness: Lessons from Ethical Philosophy and Welfare Economics’, Michelle Lee and colleagues introduce the use of Key Ethics Indicators (KEIs) as a way towards understanding whether or not an algorithmic system is aligned to a decision-maker’s ethical val- ues; in ‘Ethics Auditing Framework for Trustworthy AI: Lessons from the IT Audit Literature’, Nathaniel Zinda explores how the emerging field of ‘AI auditing’ can learn from and build on traditional IT audits; in ‘Ethics Auditing: Lessons from Business Ethics for Ethics Auditing of AI’, Noah Schöppl and colleagues conduct a similar review of the business ethics literature to establish best practices for how auditing – as a governance mechanism – can help organisations (a) design AI systems in ways that are ethical and (b) make verifiable claims about those systems; in ‘AI Ethics and Policies: Why European Journalism Needs More of Both’, Guido Romeo and Emanuela Griglié argue that policymakers can help newsrooms manage the ethical issues raised by the use of AI in journalism by supporting the development of tools like checklists and guidance on how to use such tools; in ‘Towards Equitable Health Outcomes Using Group Data Rights’, Gal Wachtel proposes a framework for practically implementing group data rights in a healthcare setting; and, finally, in ‘Ethical Principles for Artificial Intelligence in National Defence’, Mariarosaria Taddeo and colleagues propose a framework consisting of five principles and issue-related recommendations to foster ethically sound uses of AI for national defence purposes. From its very start in 2018, the main purpose of the Digital Ethics Lab Yearbook has been to give a non-exhaustive snapshot of the diverse and cutting-edge research agendas being pursued within our research group at the Oxford Internet Institute. However, the 2020/21 Yearbook marks the maturation not only of the field of digital ethics but also of the Digital Ethics Lab itself. As the discipline develops in terms of thematic focus and methodological rigour, so do our ways of working. The Digital Ethics Lab has served its purpose of identifying the opportunities and enhancing the benefits of digital innovation whilst showing how to avoid or mitigate the associated risks. To reflect the shifting focus – from soft to hard governance and from abstract to more concrete solutions – our future efforts will be directed towards supporting viii Preface the newly formed Centre for Digital Ethics and Governance at the University of Bologna and the Digital Governance Research Group at Exeter College, Oxford. Oxford, UK Jakob Mökander Princeton, NJ, USA Oxford, UK Marta Ziosi References AI HLEG. (2019). European Commission’s ethics guidelines for trustworthy Artificial Intelligence (Issue May). https://ec.europa.eu/futurium/en/ai-alliance-consultation/guidelines/1 AIEIG. (2020). From principles to practice – An interdisciplinary framework to operationalise AI ethics (pp. 1–56). AI Ethics Impact Group, VDE Association for Electrical Electronic & Information Technologies e.V., Bertelsmann Stiftung. https://doi.org/10.11586/2020013 Ayling, J., & Chapman, A. (2021). Putting AI ethics to work: Are the tools fit for purpose? AI and Ethics, 0123456789. https://doi.org/10.1007/s43681-021-00084-x Beijing Academy of Artificial Intelligence. (2019). The Beijing AI principles. Erdelyi, O. J., & Goldsmith, J. (2018). Regulating Artificial intelligence proposal for a global solution. In AAAI/ACM conference on artificial intelligence, ethics and society. http://www. aies-conference.com/wp-content/papers/main/AIES_2018_paper_13.pdf European Commission. (2020). White Paper on Artificial Intelligence – A European approach to excellence and trust. 27. European Commission. (2021). Proposal for regulation of the European parliament and of the council – Laying down harmonised rules on artificial intelligence (artificial intelligence act) and amending certain Union legislative acts. Floridi, L. (2018). Soft ethics and the governance of the digital. Philosophy and Technology, 31(1). https://doi.org/10.1007/s13347-018-0303-9 Floridi, L. (2021). The end of an Era: From self-regulation to hard law for the digital industry. Philosophy and Technology, 34(4), 619–622. https://doi.org/10.1007/s13347-021-00493-0 Mökander, J., & Axente, M. (2021). Ethics-based auditing of automated decision-making systems: Intervention points and policy implications. AI & SOCIETY, 0123456789. https://doi. org/10.1007/s00146-021-01286-x Mökander, J., Axente, M., Casolari, F., & Floridi, L. (2021). Conformity assessments and post- market monitoring: A guide to the role of auditing in the proposed European AI regulation. Minds and Machines, 0123456789, 1–27. https://doi.org/10.1007/s11023-021-09577-4 Mökander, J., Juneja, P., Watson, D.S. et al. (2022). The US Algorithmic Accountability Act of 2022 vs. The EU Artificial Intelligence Act: what can they learn from each other?. Minds and Machines. https://doi.org/10.1007/s11023-022-09612-y Morley, J., Floridi, L., Kinsey, L., & Elhalal, A. (2020). From what to how: An initial review of publicly available AI ethics tools, methods and research to translate principles into practices [Article]. Science and Engineering Ethics, 26(4), 2141. https://doi.org/10.1007/ s11948-019-00165-5 Morley, J., Elhalal, A., Garcia, F., Kinsey, L., Mökander, J., & Floridi, L. (2021). Ethics as a service: A pragmatic operationalisation of AI ethics. Minds and Machines, 31(2), 239–256. https://doi.org/10.1007/s11023-021-09563-w Office of U.S. Senator Ron Wyden. (2022). Algorithmic accountability act of 2022. 117th Congress 2D Session. https://doi.org/10.1016/S0140-6736(02)37657-8 Taddeo, M., & Floridi, L. (2018). How AI can be a force for good. Science, 361(6404), 751–752. https://doi.org/10.1126/science.aat5991 The European Commission’s Expert Group on Liability and New Technologies-New Technologies Formation. (2019). Liability for Artificial Intelligence and other emerging digital technologies. https://doi.org/10.2838/25362 University of Montreal. (2018). Montréal Declaration responsible AI. https://www.montrealdecla- ration-responsibleai.com/the-declaration Contents The European Legislation on AI: A Brief Analysis of Its Philosophical Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Luciano Floridi Informational Privacy with Chinese Characteristics. . . . . . . . . . . . . . . . . . 9 Huw Roberts Lessons Learned from Co-governance Approaches – Developing Effective AI Policy in Europe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Caitlin C. Corrigan State-Firm Coordination in AI Governance . . . . . . . . . . . . . . . . . . . . . . . . . 47 Noah Schöppl The Impact of Australia’s News Media Bargaining Code on Journalism, Democracy, and the Battle to Regulate Big Tech . . . . . . . . 63 Emmie Hine App Store Governance: The Implications and Limitations of Duopolistic Dominance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Josh Cowls and Jessica Morley A Legal Principles-Based Framework for AI Liability Regulation . . . . . . 93 Massimo Durante and Luciano Floridi The New Morality of Debt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Nikita Aggarwal Site of the Living Dead: Clarifying Our Moral Obligations Towards Digital Remains . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Mira Pijselman The Statistics of Interpretable Machine Learning . . . . . . . . . . . . . . . . . . . . 133 David S. Watson ix