Thomas Beschorner

This paper contributes to the normative analysis of digital technologies and data-driven practices by broadening the analytical perspective on freedom. Many contemporary discussions of the digital context tend to operate with a relatively narrow conception of freedom, which centers on the absence of interference. While this approach is in line with liberalism’s on-going paradigmatic standing in much of the Western world, we argue that digital theorists have much to gain from opening their discussions to social and positive conceptions of freedom. Drawing on the work of Axel Honneth and John Christman, we show how such a change in perspective gives rise to new considerations for freedom in the digital context, such as collective self-determination, capabilities, and mutual recognition. Building on these ideas, we sketch three demands that follow from such an inclusive conception of freedom: empowering people via new forms of political participation, increasing diversity and collective awareness in the digital industry, as well as using progressive political regulation to unleash digital technology’s social potential.

Health data bear great promises for a healthier and happier life, but they also make us vulnerable. Making use of millions or billions of data points, Machine Learning (ML) and Artificial Intelligence (AI) are now creating new benefits. For sure, harvesting Big Data can have great potentials for the health system, too. It can support accurate diagnoses, better treatments and greater cost effectiveness. However, it can also have undesirable implications, often in the sense of undesired side effects, which may in fact be terrible. Examples for this, as discussed in this article, are discrimination, the mechanisation of death, and genetic, social, behavioural or technological selection, which may imply eugenic effects or social Darwinism. As many unintended effects become visible only after years, we still lack sufficient criteria, long-term experience and advanced methods to reliably exclude that things may go terribly wrong. Handing over decision-making, responsibility or control to machines, could be dangerous and irresponsible. It would also be in serious conflict with human rights and our constitution.

In this intervention, we discuss to what extent the term “decision” serves as an adequate terminology for what algorithms actually do. Although calculations of algorithms might be perceived as or be an important basis for a decision, we argue, that this terminology is not only misleading but also problematic. A calculation is not a decision, we claim, since a decision (implicitly) includes two important aspects: imaginaries about the future and a “fictional surplus” as well as the process of justification. Our proposal can be seen as an invitation to reflect but the role of “humans outside the code” (and not merely “in the loop”).

In this paper, we develop our argument in three steps: Firstly, we elaborate on some theoretical perspectives for industry-specific CSR by referring to cultural business ethics, a theoretical approach which is located between purely business perspectives and purely normative perspectives on CSR. Secondly, we briefly introduce the papers of this special issue, which covers a wide range of theoretical approaches and empirical studies in the field of industry-specific CSR. Thirdly, we draw attention to shortcomings of an industry-specific approach and sketch some theoretical—but also empirically applicable—perspectives for further research that stress cross-sectoral perspectives based on societal needs.