Challenge 1

Knowledge-intensive human work in the age of digital transformation

What is the nature and role of work in the digital age? What work remains left to be done by humans? Recent advances in the fields of artificial intelligence, machine learning, and robotics have sparked an intense public debate about the impacts of - particularly digital - technology on labour markets, labour politics, and economic distribution. They have led to the mushrooming of a – sometimes alarmist, sometimes appeasing – literature that tries to assess the bearing of digital technologies and practices on the future of work. The discursive space in which this societal debate is fought out is, by its very nature, political: it is related to contested understandings of what ‘decent work’ means, what policies should be adopted, and what utopias should be strived towards.

Digital practices – from online consumer and communication behaviour to the ‘Internet of Things’ to the digital transformation of economic production and the workplace environment – are central to this debate. Zuboff (1985, 1988) alerted early to the fact that ‘informating’ digital practices in the ‘age of the Smart Machine’ could have both empowering and oppressing consequences and would be associated with new forms and lines of labour conflict, workplace surveillance and automated recruiting and talent acquisition. Recently, new forms of digital practice in the domain of work – the gig economy, platform work, digital outsourcing – have come into sharp focus of social scientists (Stewart and Stanford 2017; Wood et al 2018; 2019; Drahokoupil and Piasna 2017; Newlands et al 2018). Recent research attempts also go beyond a Eurocentric perspective on the future of work, foregrounding the implications and spill-overs of digital practices on global work relations (Graham et al 2017; Heeks 2010; Schlogl and Sumner 2018). Of particular interest for our Research Platform are such digital global work relations in the science and research domains. One example is the online labour market Mechanical Turk (Amazon), which is already widely used for scientific inquiry (e.g. answering psychological surveys), but also heavily criticised for its low wages and exploitative nature. Lately, a “bot panic” has hit researchers, when many reported quality drops in their virtual work fleets. It was indeed not discernable what caused the loss of quality: bots, human-augmented bots, humans tired and randomly clicking buttons, or just poor survey design (see also Cherry 2015).

Doctoral Project 1

Host Department: Science and Technology Studies @ Faculty of Social Sciences

Supervision: Ulrike Felt & Barbara Prainsack

Pre-doc: Rasmus Kvaal Wardemann

One particular focus of our Research Platform is how the digital transformation, paired with calls for more openness and transparency, affects knowledge-intensive work. The increasing use of artificial intelligence, decision support systems, sorting and surveillance tools does not only raise concerns about the nature and quality of knowledge that is created and used, but also about the social and political consequences. For example, how can the use of a proprietary algorithm for the purpose of sorting radiological images or media content, for example, be squared with ethical and political requirements for accountability and transparency? How are such procedures changing workplace culture at research institutions (and beyond) and the responsibilities and duties of knowledge workers? A doctoral student (‘pre-doc’) based in the Department of Science and Technology Studies, who will collaborate with colleagues in all Departments and Faculties involved in the Platform, will pursue a comparative study of digital practices in datafication, data sharing, and automation in academic daily work routines in the life science and in the social sciences.

The methodological tool box for this case study will include elements of digital ethnography (Pink et al. 2016), qualitative interviews and group discussions. The aim will be to analyse how digital knowledge practices intended to increase efficiency and optimise academic work and knowledge transfer encounter diverging and sometimes clashing data governance regimes. Academic research seems a suitable opportunity to study digital practices in knowledge-intensive work, because it offers a level of access and transparency for an empirical study that would not be available in other societal sectors. Immanuel Bomze will contribute his rich experience as a Co-Editor-in-Chief of a globally leading transdiciplinarity-oriented journal in his field Operational Research, and his expertise in Data Science technologies concerned with protecting confidential content, intellectual property rights and privacy, and trust-building methods. The doctoral project can also be seen as a “test bed” for the broader study of social, ethical and legal implications of AI and automation in society (on the latter, the Department of Innovation and Digitalisation in Law will provide support and input).