Luciano Floridi

The article argues that AI can enhance the measurement and implementation of democratic processes within political parties, known as Intra-Party Democracy (IPD). It identifies the limitations of traditional methods for measuring IPD, which often rely on formal parameters, self-reported data, and tools like surveys. Such limitations lead to the collection of partial data, rare updates, and significant demands on resources. To address these issues, the article suggests that specific data management and Machine Learning (ML) techniques, such as natural language processing and sentiment analysis, can improve the measurement (ML about) and practice (ML for) of IPD. The article concludes by considering some of the principal risks of ML for IPD, including concerns over data privacy, the potential for manipulation, and the dangers of overreliance on technology.

The advent of Generative AI, particularly through Large Language Models (LLMs) like ChatGPT and its successors, marks a paradigm shift in the AI landscape. Advanced LLMs exhibit multimodality, handling diverse data formats, thereby broadening their application scope. However, the complexity and emergent autonomy of these models introduce challenges in predictability and legal compliance. This paper analyses the legal and regulatory implications of Generative AI and LLMs in the European Union context, focusing on liability, privacy, intellectual property, and cybersecurity. It examines the adequacy of the existing and proposed EU legislation, including the Artificial Intelligence Act (AIA), in addressing the challenges posed by Generative AI in general and LLMs in particular. The paper identifies potential gaps and shortcomings in the EU legislative framework and proposes recommendations to ensure the safe and compliant deployment of generative models.

Regulation by design (RBD) is a growing research field that explores, develops, and criticises the regulative function of design. In this article, we provide a qualitative thematic synthesis of the existing literature. The aim is to explore and analyse RBD's core features, practices, limitations, and related governance implications. To fulfil this aim, we examine the extant literature on RBD in the context of digital technologies. We start by identifying and structuring the core features of RBD, namely the goals, regulators, regulatees, methods, and technologies. Building on that structure, we distinguish between three types of RBD practices: compliance by design, value creation by design, and optimisation by design. We then explore the challenges and limitations of RBD practices, which stem from risks associated with compliance by design, contextual limitations, or methodological uncertainty. Finally, we examine the governance implications of RBD and outline possible future directions of the research field and its practices.

This book offers an overview of the ethical problems posed by Information Warfare, and of the different approaches and methods used to solve them, in order to provide the reader with a better grasp of the ethical conundrums posed by this new form of warfare. The volume is divided into three parts, each comprising four chapters. The first part focuses on issues pertaining to the concept of Information Warfare and the clarifications that need to be made in order to address its ethical implications. The second part collects contributions focusing on Just War Theory and its application to the case of Information Warfare. The third part adopts alternative approaches to Just War Theory for analysing the ethical implications of this phenomenon. Finally, an afterword by Neelie Kroes - Vice President of the European Commission and European Digital Agenda Commissioner - concludes the volume. Her contribution describes the interests and commitments of the European Digital Agenda with respect to research for the development and deployment of robots in various circumstances, including warfare.

In recent years, policymakers, academics, and practitioners have increasingly called for the development of global governance mechanisms for artificial intelligence (AI). This paper considers the prospects for these calls in light of two other geopolitical trends: digital sovereignty and digital expansionism. While calls for global AI governance promote the surrender of some state sovereignty over AI, digital sovereignty and expansionism seek to secure greater state control over digital technologies. To demystify the tensions between these trends and their potential consequences, we undertake a case analysis of digital sovereignty and digital expansionism in China, the European Union, and the United States. We argue that the extraterritoriality embedded in these three actors’ policies and escalatory competitive narratives, particularly those from the US, will likely undermine substantive global AI governance cooperation. However, nascent areas of alignment or compromise, notably in data governance and technical standards, could prove fruitful starting points for building trust in multilateral fora, such as the G20 or United Nations.

Altruism is a well-studied phenomenon in the social sciences, but online altruism has received relatively little attention. In this article, we examine several cases of online altruism, and analyse the key characteristics of the phenomenon, in particular comparing and contrasting it against models of traditional donor behaviour. We suggest a novel definition of online altruism, and provide an in-depth, mixed-method study of a significant case, represented by the r/Assistance subreddit. We argue that online altruism can be characterized by its differing experiences compared to traditional giving, from a giver’s point of view, and unique mechanisms and actions made possible by the internet. These findings explain why people give to anonymous strangers online and provide a new perspective on altruism that is important in building a more altruistic internet and society.

Online controlled experiments, also known as A/B tests, have become ubiquitous. While many practical challenges in running experiments at scale have been thoroughly discussed, the ethical dimension of A/B testing has been neglected. This article fills this gap in the literature by introducing a new, soft ethics and governance framework that explicitly recognizes how the rise of an experimentation culture in industry settings brings not only unprecedented opportunities to businesses but also significant responsibilities. More precisely, the article (a) introduces a set of principles to encourage ethical and responsible experimentation to protect users, customers, and society; (b) argues that ensuring compliance with the proposed principles is a complex challenge unlikely to be addressed by resorting to a one-solution response; (c) discusses the relevance and effectiveness of several mechanisms and policies in educating, governing, and incentivizing companies conducting online controlled experiments; and (d) offers a list of prompting questions specifically designed to help and empower practitioners by stimulating specific ethical deliberations and facilitating coordination among different groups of stakeholders.

This paper considers a host of definitions and labels attached to the concept of smart cities to identify four dimensions that ground a review of ethical concerns emerging from the current debate. These are: (1) network infrastructure, with the corresponding concerns of control, surveillance, and data privacy and ownership; (2) post-political governance, embodied in the tensions between public and private decision-making and cities as post-political entities; (3) social inclusion, expressed in the aspects of citizen participation and inclusion, and inequality and discrimination; and (4) sustainability, with a specific focus on the environment as an element to protect but also as a strategic element for the future. Given the persisting disagreements around the definition of a smart city, the article identifies in these four dimensions a more stable reference framework within which ethical concerns can be clustered and discussed. Identifying these dimensions makes possible a review of the ethical implications of smart cities that is transversal to their different types and resilient towards the unsettled debate over their definition.

The SARS-CoV-2 (COVID-19) pandemic has caused social and economic devastation. As the milestone of two years of ‘living with the virus’ approaches, governments and businesses are attempting to develop means of reopening society whilst still protecting public health. However, developing interventions – particularly technological interventions – that find a safe, socially acceptable, and ethically justifiable balance between these two seemingly opposing demands is extremely challenging. There is no one right solution, but the current most popular ‘solution’ is the so-called ‘COVID-19 Vaccine Passport’ (also known as COVID-19 passes or certificates), the use of which may be supported by both human rights and international public health law if they are designed and implemented appropriately. (We use the term ‘Vaccine Passport’ because it has been adopted by the popular press. Though it has been used in many ways, here we use it generically to refer to a document that certifies that an individual has been vaccinated against COVID-19 and on that basis grants the bearer more liberties than to those who have not been vaccinated. Later, we will discuss why it is necessary to move beyond considering only vaccinations, which informs our preferred term of ‘COVID-19 Status Pass’.) We set out to answer the following questions: how should governments and businesses assess the risks in light of human rights, public health ethics, and digital ethics concerns which emerge from developing and deploying COVID-19 Vaccine Passports? What design decisions should businesses make when developing COVID-19 Vaccine Passports to help ensure they respect human rights, and both public health and digital ethics? Do the implications for human rights, public health, and digital ethics vary depending on where and when COVID-19 Vaccine Passports are used? What are the rights and powers of the individual to object to or seek remedy for the use of COVID-19 Vaccine Passports? How can the risks of inequalities and social division derived from the deployment of COVID-19 Vaccine Passports be avoided or mitigated? We conducted a literature review and documentary analysis, supplementing our findings with news articles where appropriate. The following pages report our results, concluding with a series of actionable recommendations for businesses, national governments, and supranational organisations.

In this short article, I argue that (a) the distinction between what counts as natural and moral evil is not fixed; that (b) science and technology can transform natural evil into moral evil; that (c) two main philosophical anthropologies explain moral evil as due to ignorance (Socrates) or wickedness (Hobbes); and hence that (d) a society that seeks to counter evil should rely on science and technology to transform natural evil into moral evil and then on education (Paideia) and regulations (Nomos) to minimise or even eliminate moral evil.

This chapter provides an overview of six topics related to governance, ethical, legal, and social implications of artificial intelligence (AI) for sustainable development goals (SDGs) initiatives. We identified six common challenges and related opportunities to mitigate such challenges, as referred to by the authors analysing the chapters provided in the book The Ethics of Artificial Intelligence for the Sustainable Development Goals. They are (1) governance and collaboration, (2) private investments and the role of big tech companies, (3) AI and communities, (4) AI and individuals, (5) jobs and skills, and (6) impact assessment.

Artificial intelligence (AI) as a general-purpose technology has great potential for advancing the United Nations Sustainable Development Goals (SDGs). However, the AI×SDGs phenomenon is still in its infancy in terms of diffusion, analysis, and empirical evidence. Moreover, a scalable adoption of AI solutions to advance the achievement of the SDGs requires private and public actors to engage in coordinated actions that have been analysed only partially so far. This volume provides the first overview of the AI×SDGs phenomenon and its related challenges and opportunities. The first part of the book adopts a programmatic approach, discussing AI×SDGs at a theoretical level and from the perspectives of different stakeholders. The second part illustrates existing projects and potential new applications.

This volume provides an extensive overview of the Ethics of Artificial Intelligence for the Sustainable Development Goals. The authors are experts contributing with perspectives from different fields. The comprehensive collection of chapters illustrates the pressing governance problems related to using AI for the SDGs, and case studies describing how AI is advancing and can advance the achievement of the Goals. Students, scholars, and practitioners working on AI for SDGs, the ethical governance of AI, sustainability, and the fourth revolution can find this book a helpful reference.

Following the storming of the US Capitol building, Donald Trump became digitally toxic, and was deplatformed from Facebook, Instagram, Twitter and YouTube—as well as a host of other social media networks. Subsequent debate has centred on the questions of whether these companies did the right thing and the possible ramifications of their actions for the future of digital societies along with their democratic organisation. This article seeks to answer this question through examining complex, and seemingly contradictory notions (legality and the protection of public interest vs issues of democratic legitimacy and digital sovereignty) and argues that reform is needed to determine who, in the future, will control the infosphere—and how.

This article offers an account and defence of constructionism, both as a metaphilosophical approach and as a philosophical methodology, with references to the so-called maker's knowledge tradition. Its main thesis is that Plato's “user's knowledge” tradition should be complemented, if not replaced, by a constructionist approach to philosophical problems in general and to knowledge in particular. Epistemic agents know something when they are able to build (reproduce, simulate, model, construct, etc.) that something and plug the obtained information into the correct network of relations that account for it. Their epistemic expertise increases with the scope and depth of the questions that they are able to ask and answer. Thus, constructionism deprioritises mimetic, passive, and declarative knowledge that something is the case, in favour of poietic, interactive, and practical knowledge of something being the case. Metaphilosophically, constructionism suggests adding conceptual engineering to conceptual analysis as a fundamental method

The EU Artificial Intelligence Act (AIA) defines four risk categories for AI systems: unacceptable, high, limited, and minimal. However, it lacks a clear methodology for the assessment of these risks in concrete situations. Risks are broadly categorized based on the application areas of AI systems and ambiguous risk factors. This paper suggests a methodology for assessing AI risk magnitudes, focusing on the construction of real-world risk scenarios. To this scope, we propose to integrate the AIA with a framework developed by the Intergovernmental Panel on Climate Change (IPCC) reports and related literature. This approach enables a nuanced analysis of AI risk by exploring the interplay between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. We further refine the proposed methodology by applying a proportionality test to balance the competing values involved in AI risk assessment. Finally, we present three uses of this approach under the AIA: to implement the Regulation, to assess the significance of risks, and to develop internal risk management systems for AI deployers.

The EU proposal for the Artificial Intelligence Act (AIA) defines four risk categories: unacceptable, high, limited, and minimal. However, as these categories statically depend on broad fields of application of AI, the risk magnitude may be wrongly estimated, and the AIA may not be enforced effectively. This problem is particularly challenging when it comes to regulating general-purpose AI (GPAI), which has versatile and often unpredictable applications. Recent amendments to the compromise text, though introducing context-specific assessments, remain insufficient. To address this, we propose applying the risk categories to specific AI scenarios, rather than solely to fields of application, using a risk assessment model that integrates the AIA with the risk approach arising from the Intergovernmental Panel on Climate Change (IPCC) and related literature. This model enables the estimation of the magnitude of AI risk by considering the interaction between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. We use large language models (LLMs) as an example.

Wie kann Europa politisch und gesellschaftlich durch die Möglichkeiten der Digitalisierung profitieren und seine Krisen überwinden, von denen es in der letzten Zeit so geplagt wurde? Wie kann es ein „Humanprojekt“ und die Einheit von „grüner“ Ökologie und „blauer“ Informationstechnik realisieren? In diesem Band präsentiert Luciano Floridi eine Zusammenfassung seiner Thesen, wie sich die Digitalisierung ganz konkret auf politische und soziale Phänomene auswirkt, und wie nun weniger die Dinge als ihre Relationen an Bedeutung gewinnen.Mit kritischen Beiträgen von Manfred Broy, Markus Gabriel, Armin Grunwald, Ruth Hagengruber, Alexander Kriebitz, Christoph Lütge, Raphael Max, Catrin Misselhorn und Malte Rehbein.

In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial opportunities that AI offers in this domain: it can help improve and expand current understanding of climate change, and it can contribute to combatting the climate crisis effectively. However, the development of AI also raises two sets of problems when considering climate change: the possible exacerbation of social and ethical challenges already associated with AI, and the contribution to climate change of the greenhouse gases emitted by training data and computation-intensive AI systems. We assess the carbon footprint of AI research, and the factors that influence AI’s greenhouse gas (GHG) emissions in this domain. We find that the carbon footprint of AI research may be significant and highlight the need for more evidence concerning the trade-off between the GHG emissions generated by AI research and the energy and resource efficiency gains that AI can offer. In light of our analysis, we argue that leveraging the opportunities offered by AI for global climate change whilst limiting its risks is a gambit which requires responsive, evidence-based, and effective governance to become a winning strategy. We conclude by identifying the European Union as being especially well-placed to play a leading role in this policy response and provide 13 recommendations that are designed to identify and harness the opportunities of AI for combatting climate change, while reducing its impact on the environment.