Tackling the Algorithmic Control Crisis – the Technical, Legal, and Ethical Challenges of Research into Algorithmic Agents

Algorithmic agents permeate every instant of our online existence. Based on our digital profiles built from the massive surveillance of our digital existence, algorithmic agents rank search results, filter our emails, hide and show news items on social networks feeds, try to guess what products we might buy next for ourselves and for others, what movies we want to watch, and when we might be pregnant. Algorithmic agents select, filter, and recommend products, information, and people; they increasingly customize our physical environments, including the temperature and the mood. Increasingly, algorithmic agents don’t just select from the range of human created alternatives, but also they create. Burgeoning algorithmic agents are capable of providing us with content made just for us, and engage with us through one-of-a-kind, personalized interactions. Studying these algorithmic agents presents a host of methodological, ethical, and logistical challenges. The objectives of our paper are two-fold. The first aim is to describe one possible approach to researching the individual and societal effects of algorithmic recommenders, and to share our experiences with the academic community. The second is to contribute to a more fundamental discussion about the ethical and legal issues of “tracking the trackers”, as well as the costs and trade-offs involved. Our paper will contribute to the discussion on the relative merits, costs and benefits of different approaches to ethically and legally sound research on algorithmic governance. We will argue that besides shedding light on how users interact with algorithmic agents, we also need to be able to understand how different methods of monitoring our algorithmically controlled digital environments compare to each other in terms of costs and benefits. We conclude our article with a number of concrete suggestions for how to address the practical, ethical and legal challenges of researching algorithms and their effects on users and society.