The creation of increasingly complex artificial intelligence (AI) systems raises urgent questions about their ethical and social impact on society. Since this impact ultimately depends on political decisions about normative issues, political philosophers can make valuable contributions by addressing such questions. Currently, AI development and application are to a large extent regulated through non-binding ethics guidelines penned by transnational entities. Assuming that the global governance of AI should be at least minimally democratic and fair, this paper sets out three desiderata (...) that an account should satisfy when theorizing about what this means. We argue, first, that an analysis of democratic values, political entities and decision-making should be done in a holistic way; second, that fairness is not only about how AI systems treat individuals, but also about how the benefits and burdens of transformative AI are distributed; and finally, that justice requires that governance mechanisms are not limited to AI technology, but are incorporated into a range of basic institutions. Thus, rather than offering a substantive theory of democratic and fair AI governance, our contribution is metatheoretical: we propose a theoretical framework that sets up certain normative boundary conditions for a satisfactory account. (shrink)

This article makes the case for a specific variety of what we call collective capital institutions (CCIs), by returning to the idea of Wage-Earner Funds – a 1970’s Swedish policy proposal designed gradually to shift ownership and control over parts of the economy over to democratically controlled institutions. We identify two attractive rationales in favour of such a scheme, and argue that both can fruitfully be transposed to the current worldwide economic situation. The egalitarian rationale is that CCIs could help (...) in the pursuit of equality by giving a wider set of people a stake in collectively owned companies and a right to their profits. The democratic rationale is that CCIs redistribute not only these profits, but also the power over economic decisions made within companies. We then contrast such schemes for collective capital ownership with the similar but much more privatised proposals set out in, for instance, John Rawls’s idea of a ‘property-owning democracy’. We argue that CCIs ultimately are more likely to contribute to the development of the ‘sense of justice’ within society that is needed for a stable just society. We conclude that CCIs deserve a great deal more exploration in academic and political discussions of egalitarian economic systems. (shrink)

If there is a duty of justice to contribute to society, which asks individuals to produce a specific amount of goods and services that can be redistributed, we need a decision-procedure to know when we have done our part. This paper analyses and critically assesses the commonly suggested decision-procedure of relying on market prices to measure the value of one’s contribution. It is usually assumed that a high salary indicates that one’s talents are put to good use, but this presupposes (...) both that market prices of labour are correct reflections of supply and demand, and that market prices are correct reflections of social value. I criticise both assumptions and argue that the social value of a contribution cannot simply be a function of its market value, but is also influenced by the principles of justice that support the duty to contribute. Further, the market solution is incapable of valuing contributions that lack market prices, like non-marketised care labour. The market solution thus fails as a decision-procedure under other than special circumstances. This does not mean, however, that we need to give up the idea of a duty to contribute. (shrink)

G. A. Cohen has argued that egalitarian justice proscribes equality-upsetting economic incentives, but that individuals nevertheless are required to make a sufficiently large productive contribution to society. This article argues, however, that Cohen’s claim that justice is insensitive to Pareto concerns and simply is equality, undermines such a duty. In fact, Cohen cannot say that justice prefers a distribution where everyone is equally well off to one where everyone is equally badly off. Individuals hence cannot have a duty of justice (...) to use their talents at a more productive level. This indifference risks removing Cohen’s egalitarianism’s appeal as an alternative to the Rawlsian position it challenges. Several ways of avoiding this problem are proposed and evaluated. Ultimately, it is argued that such a duty to contribute must instead be based on a concern for both equality and human flourishing. The ethos Cohen defends must hence be made pluralist, and encourage a commitment to both principles. (shrink)

The last decade has seen significant improvements in Artificial Intelligence (AI) technologies, including robotics, machine vision, speech recognition and text generation. Increasing automation will undoubtedly affect the future of work, and discussions on how the development of AI in the workplace will impact labor markets often include two scenarios: (1) labor replacement and (2) labor enabling. The former involves replacing workers with machines, while the latter assumes that human-machine cooperation can significantly improve worker productivity. In this context, it is often (...) argued that (1) could lead to mass unemployment and that (2) therefore would be more desirable. We argue, however, that the labor-enabling scenario conflates two distinct possibilities. On the one hand, technology can increase productivity while also promoting “the goods of work,” such as the opportunity to pursue excellence, experience a sense of community and contribute to society (human augmentation). On the other hand, higher productivity can also be achieved in a way that reduces opportunities for the “goods of work” and/or increases “the bads of work,” such as injury, reduced physical and mental health, reduction of autonomy, privacy and human dignity (human stunting). We outline the differences of these outcomes and discuss the implications for the labor market in the context of contemporaneous discussions on the value of work and human wellbeing. (shrink)

Work has always been a significant source of ethical questions, philosophical reflection, and political struggle. Although the future of work in a sense is always at stake, the issue is particularly relevant right now, in light of the advent of advanced AI systems and the collective experience of the COVID-19 pandemic. This has reinvigorated philosophical discussion and interest in the study of the future of work. The purpose of this survey article is to provide an overview of the emerging philosophical (...) field that engages with the future of work, with a special focus on equality and justice, and to outline a research agenda that can help the field to develop further. Section 2 provides some historical context for the current surge in interest in the topic. Then, we discuss what work is and whether there is a philosophy of work (Section 3). The four main sub-debates we then turn to concern the value of work (Section 4), distributive justice and work (Section 5), productive justice (Section 6), and institutional reforms prompted by changes in how work is organized (Section 7). The final section discusses the importance of the distinction between ideal and non-ideal theory in philosophical investigations into the future of work. (shrink)

Although the concept of “AI governance” is frequently used in the debate, it is still rather undertheorized. Often it seems to refer to the mechanisms and structures needed to avoid “bad” outcomes and achieve “good” outcomes with regard to the ethical problems artificial intelligence is thought to actualize. In this article we argue that, although this outcome-focused view captures one important aspect of “good governance,” its emphasis on effects runs the risk of overlooking important procedural aspects of good AI governance. (...) One of the most important properties of good AI governance is political legitimacy. Starting out from the assumptions that AI governance should be seen as global in scope and that political legitimacy requires at least a democratic minimum, this article has a twofold aim: to develop a theoretical framework for theorizing the political legitimacy of global AI governance, and to demonstrate how it can be used as a compass for critially assessing the legitimacy of actual instances of global AI governance. Elaborating on a distinction between “governance by AI” and “governance of AI” in relation to different kinds of authority and different kinds of decision-making leads us to the conclusions that much of the existing global AI governance lacks important properties necessary for political legitimacy, and that political legitimacy would be negatively impacted if we handed over certain forms of decision-making to artificial intelligence systems. (shrink)