“It would be pretty immoral to choose a random algorithm” Opening up algorithmic interpretability and transparency

In recent years, significant concerns have arisen regarding the increasing pervasiveness of algorithms and the impact of automated decision-making in our lives. Particularly problematic is the lack of transparency surrounding the development of these algorithmic systems and their use. It is often suggested that in order to make algorithms more fair, they should be made more transparent; but exactly how this can be achieved remains unclear. This paper reports on empirical work conducted to open up algorithmic interpretability and transparency. We conducted discussion-based experiments centred around a limited resource allocation scenario which required participants to select their most and least preferred algorithms in a particular context. Our results revealed diversity in participant preferences but consistency in the ways that participants invoked normative concerns and the importance of context when accounting for their selections. These findings demonstrate the value in pursuing algorithmic interpretability and transparency whilst also highlighting the complexities surrounding their accomplishment