Making Algorithmic Systems More Meaningfully Transparent for Users Through Visualisation

Abstract

Transparency over algorithmic systems is increasingly asked for, though it is unclear how it can be realised in practice. Transparency is largely recognised as helpful-eg. to redress information asymmetries-but not as an end in and of itself. Understanding how transparency can be meaningful to users, as well as the challenges and design methods to improve transparency at the interface level is therefore key to make algorithmic systems more usefully transparent for users. As part of the DIS '22 Doctoral Consortium, I am presenting my PhD research on visualising meaningful transparency for users. We are exploring the role of visualisation as a lever to make system transparency more meaningful to users. We consider transparency from a broad socio-technical and systemic perspective, with HCI and Art History research methods. We focus on user interfaces, as they are the key point of interaction between users and systems. By analysing the status quo and various users' transparency needs, we highlight challenges regarding current practices and transparency guidelines, but also offer practical leads to improve algorithmic system transparency for users.