Confronting Methodological and Ethical Challenges in the Study of Algorithms and Digital Labour

The biggest problem scholars face when researching algorithms and digital labour is that, at least so far, not only are algorithms black boxes whose workings are unknown to gig workers, journalists, global civil society and researchers but also the entire socio-technical assemblage around algorithms is black-boxed. As Bonini and Gandini (2020) argue, it is the entire field of platform studies research that is black-boxed, because the private companies that produce the gig working apps are extremely repulsive to any attempt by journalists, civil society and academic researchers to access their production and workspaces. The black-boxed nature of the entire research field– not only of the algorithms per se, as strings of computer code– has relevant methodological implications: for instance, it affects the agency of the researcher in getting access to key figures, gatekeepers and research participants in the field (see Alyanak et al., Chapter 39). It is no coincidence, then, that most of the research in this field has taken place outside the private spaces of digital labour companies, such as research papers on food delivery riders and Upwork freelance workers, because it is much easier for researchers to talk to gig workers than to Uber or Deliveroo managers. Moreover, not all research methods, whether qualitative or quantitative, are suitable for investigating this field. Some are more effective than others. In the following sections, we will first analyse the methods most used by researchers in this field and then describe the challenges these researchers face, concluding with a series of proposals for opening up the black box of gig working platforms with a methodological approach that is at once productive, effective and ethical.