This paper argues against the call to democratize artificial intelligence (AI). Several authors demand to reap purported benefits that rest in direct and broad participation: In the governance of AI, more people should be more involved in more decisions about AI—from development and design to deployment. This paper opposes this call. The paper presents five objections against broadening and deepening public participation in the governance of AI. The paper begins by reviewing the literature and carving out a set of claims (...) that are associated with the call to “democratize AI”. It then argues that such a democratization of AI (1) rests on weak grounds, because it does not answer to a demand of legitimization, (2) is redundant in that it overlaps with existing governance structures, (3) is resource intensive, which leads to injustices, (4) is morally myopic and thereby creates popular oversights and moral problems of its own, and finally, (5) is neither theoretically nor practically the right kind of response to the injustices that animate the call. The paper concludes by suggesting that AI should be democratized not by broadening and deepening participation but by increasing the democratic quality of the administrative and executive elements of collective decision making. In a slogan: The question is not so much whether AI should be democratized but how. (shrink)

Artificial intelligence (AI) is increasingly expected to disrupt the ordinary functioning of society. From how we fight wars or govern society, to how we work and play, and from how we create to how we teach and learn, there is almost no field of human activity which is believed to be entirely immune from the impact of this emerging technology. This poses a multifaceted problem when it comes to designing and understanding regulatory responses to AI. This article aims to: (i) (...) defend the need for a novel conceptual model for understanding the systemic legal disruption caused by new technologies such as AI; (ii) to situate this model in relation to preceding debates about the interaction of regulation with new technologies (particularly the ‘cyberlaw’ and ‘robolaw’ debates); and (iii) to set out a detailed model for understanding the legal disruption precipitated by AI, examining both pathways stemming from new affordances that can give rise to a regulatory ‘disruptive moment’, as well as the Legal Development, Displacement or Destruction that can ensue. The article proposes that this model of legal disruption can be broadly generalisable to understanding the legal effects and challenges of other emerging technologies. (shrink)

In controversies about technology and society, there is no idea more pro vocative than the notion that technical things have political qualities. At issue is the claim that the machines, structures, and systems of modern material culture can be accurately judged not only for their contributions of efficiency and pro-ductivity, not merely for their positive and negative environmental side effects, but also for the ways in which they can embody specific forms of power and authority. Since ideas of this kind (...) have a persistent and troubling presence in discussions about the meaning of technology, they deserve explicit attention... (shrink)

Recent rapid advances in Artificial Intelligence (AI) and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by machines. To (...) achieve this, we can adapt the concept of human-in-the-loop (HITL) from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop (SITL), which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, ‘SITL = HITL + Social Contract.’. (shrink)

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences (...) affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms. (shrink)

The scale and asymmetry of commercial technology firms’ power over people through data, combined with the increasing involvement of the private sector in public governance, means that increasingly, people do not have the ability to opt out of engaging with technology firms. At the same time, those firms are increasingly intervening on the population level in ways that have implications for social and political life. This creates the potential for power relations of domination, and demands that we decide what constitutes (...) the legitimacy to act on the public. Business ethics and private law are not designed to answer these questions, which are primarily political. If people have lost the right to disengage with commercial technologies, we may need to hold the companies that offer them to the same standards to which we hold the public sector. This paper first defines the problem and demonstrates that it is significant and widespread, and then argues for the development of an overarching normative framework for what constitutes non-domination with regard to digital technologies. Such a framework must involve a nuanced idea of political power and accountability that can respond not only to the legality of corporate behaviour, but to its legitimacy. (shrink)

Digital energy platforms play a central role in the transition toward a more sustainable energy system. This research explores the effect of digital energy platforms on public values. We developed and tested a novel public value framework, combining values already embedded in energy and digitalization regulations and emerging values that have become more relevant in recent debates. We analyzed value changes and potential value tensions. We found that sustainability is prioritized, security is broadened to include cybersecurity, and values relevant for (...) digital technologies, such as control over technology, have also become relevant for the energy system. This has resulted in three value tensions: preserving a well-functioning energy system, self-determination, and ensuring a level playing field and public control. A sustainable energy system requires governments to address these value changes, value tensions, and connected societal and political challenges related to the implementation of digital energy platforms. (shrink)

Responsible innovation in artificial intelligence calls for public deliberation: well-informed “deep democratic” debate that involves actors from the public, private, and civil society sectors in joint efforts to critically address the goals and means of AI. Adopting such an approach constitutes a challenge, however, due to the opacity of AI and strong knowledge boundaries between experts and citizens. This undermines trust in AI and undercuts key conditions for deliberation. We approach this challenge as a problem of situating the knowledge of (...) actors from the AI industry within a deliberative system. We develop a new framework of responsibilities for AI innovation as well as a deliberative governance approach for enacting these responsibilities. In elucidating this approach, we show how actors from the AI industry can most effectively engage with experts and nonexperts in different social venues to facilitate well-informed judgments on opaque AI systems and thus effectuate their democratic governance. (shrink)

The increasing availability of digital data reflecting economic and human development, and in particular the availability of data emitted as a by-product of people’s use of technological devices and services, has both political and practical implications for the way people are seen and treated by the state and by the private sector. Yet the data revolution is so far primarily a technical one: the power of data to sort, categorise and intervene has not yet been explicitly connected to a social (...) justice agenda by the agencies and authorities involved. Meanwhile, although data-driven discrimination is advancing at a similar pace to data processing technologies, awareness and mechanisms for combating it are not. This paper posits that just as an idea of justice is needed in order to establish the rule of law, an idea of data justice – fairness in the way people are made visible, represented and treated as a result of their production of digital data – is necessary to determine ethical paths through a datafying world. Bringing together the emerging scholarly perspectives on this topic, I propose three pillars as the basis of a notion of international data justice: visibility, engagement with technology and antidiscrimination. These pillars integrate positive with negative rights and freedoms, and by doing so challenge both the basis of current data protection regulations and the growing assumption that being visible through the data we emit is part of the contemporary social contract. (shrink)

The Critical Theory of the early Frankfurt School promised, in Adorno’s words, a ‘rational critique of reason’. Science and Technology Studies can play a role in the renewal of this approach. STS is based on a critique of the very same technocratic and scientistic assumptions against which Critical Theory argues. Its critique of positivism and determinism has political implications. But at its origins STS took what Wiebe Bijker called the ‘detour into the academy’ in order to institutionalize itself as a (...) social science. It adopted empirical methods, developed case histories, and limited its scope, avoiding politically controversial issues. Its latent political critique has become explicit in recent years as STS has responded to the rise of technical politics by broadening its concerns. Its wide scope converges with the equally encompassing Critical Theory. Together, STS and Critical Theory offer a new concept of politics. (shrink)

As the use of AI systems continues to increase, so do concerns over their lack of fairness, legitimacy and accountability. Such harmful automated decision-making can be guarded against by ensuring AI systems are contestable by design: responsive to human intervention throughout the system lifecycle. Contestable AI by design is a small but growing field of research. However, most available knowledge requires a significant amount of translation to be applicable in practice. A proven way of conveying intermediate-level, generative design knowledge is (...) in the form of frameworks. In this article we use qualitative-interpretative methods and visual mapping techniques to extract from the literature sociotechnical features and practices that contribute to contestable AI, and synthesize these into a design framework. (shrink)