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The 2021 Yearbook of the Digital Ethics Lab

Part of the Digital Ethics Lab Yearbook Book Series

Editors: Mökander, Jakob; Ziosi, Marta

DOI: 10.1007/978-3-031-09846-8

ISBN: 978-3-031-09845-1

Publisher: Springer International Publishing - Springer Journals

Nov 8, 2022

1 - 10 of 16 Chapters

LitStream

Chapter 1The European Legislation on AI: A Brief Analysis of Its Philosophical Approach

Floridi, Luciano

Pages: 1 –8

[On 21 April 2021, the European Commission published the proposal of the new EU Artificial Intelligence Act (AIA)—one of the most influential steps taken so far to regulate AI internationally. This chapter highlights some foundational aspects of the Act and analyses the philosophy behind its...
LitStream

Chapter 2Informational Privacy with Chinese Characteristics

Roberts, Huw

Pages: 9 –23

[In recent years there is said to have been a ‘privacy awakening’ in China, with a demand from citizens for improved data protections being met by comprehensive regulatory measures, including legislation passed by the Standing Committee of the National People’s Congress. The measures introduced...
LitStream

Chapter 3Lessons Learned from Co-governance Approaches – Developing Effective AI Policy in Europe

Corrigan, Caitlin C.

Pages: 25 –46

[Advancements in artificial intelligence (AI) are moving faster than the State’s ability to fully govern it, resulting in a need for innovative approaches that also involve non-state actors, or “co-governance” mechanisms. But the question remains as to exactly how co-governance mechanisms can be...
LitStream

Chapter 4State-Firm Coordination in AI Governance

Schöppl, Noah

Pages: 47 –62

[This chapter addresses two questions: What is the role of states and technology firms in AI governance? And how can an AI governance approach that relies on both states and firms succeed? In response to the first question, it is argued that approaches which rely exclusively on either states or...
LitStream

Chapter 5The Impact of Australia’s News Media Bargaining Code on Journalism, Democracy, and the Battle to Regulate Big Tech

Hine, Emmie

Pages: 63 –74

[The Australian News Media and Digital Platforms Mandatory Bargaining Code, legislation requiring large digital platforms to pay news publishers for content that the platforms display, represents the next front in the war to regulate Big Tech. Its ostensible purpose is to provide financial...
LitStream

Chapter 6App Store Governance: The Implications and Limitations of Duopolistic Dominance

Cowls, Josh; Morley, Jessica

Pages: 75 –92

[Much focus of the emerging research front known as platform governance is concerned with content moderation and other ways in which platform companies govern users and activity on their own platforms, as well as with how platforms are themselves governed by states (Gorwa, Inf Commun Soc 22(6):...
LitStream

Chapter 7A Legal Principles-Based Framework for AI Liability Regulation

Durante, Massimo; Floridi, Luciano

Pages: 93 –112

[Europe has recently taken the path of regulating artificial intelligence (AI). This is a complex task, in which it is crucial to understand what the purposes of regulation are. In this perspective, it is not enough to identify and set ethical guidelines and legal norms. It is also important to...
LitStream

Chapter 8The New Morality of Debt

Aggarwal, Nikita

Pages: 113 –118

[This chapter examines the new morality of debt in light of the rise of machine learning and increasing datafication of lending. It argues that existing regulatory frameworks governing consumer lending are inadequate as they fail to sufficiently alleviate the privacy, autonomy and dignity harms...
LitStream

Chapter 9Site of the Living Dead: Clarifying Our Moral Obligations Towards Digital Remains

Pijselman, Mira

Pages: 119 –131

[As internet users, we leave behind both a physical and informational corpse when we die. Practices regarding the disposition of physical remains have been developed over millennia and subjected to considerable ethical scrutiny. However, the same cannot be said for digital remains, for which...
LitStream

Chapter 10The Statistics of Interpretable Machine Learning

Watson, David S.

Pages: 133 –155

[Statisticians, especially those who do applied work in the natural and social sciences, have long been interested in understanding model parameters and predictions. However, the distinct subfield of interpretable machine learning (iML), with its focus on general purpose explanations at varying...

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