The focus of this research is to investigate the algorithms that are commonly found in everyday web environments, such as online tracking, which are often hidden behind user interfaces. To accomplish this, embodied methods and choreography are used to guide interface design and tool-making processes.
Algorithmic systems are often made opaque by design, with users being unaware of how much of their data is being gathered (Pold, 2019) and for what purposes. The impact of algorithmic systems in society has had various reported instances of causing harm and inequality (Klumbyte et al., 2020). One example of these are online tracking algorithms which are present in most web services we access today (Kretschmer, Pennekamp and Wehrle, 2021). From both academia and industry proposals have emerged for making sense of the complexities of such systems.
Central to this research is the understanding of embodiment as physical engagement grounded in and emerging out of everyday experience (Dourish, 2001). Body-centered approaches provide further understanding of the actions we perform and the computational systems we interact with (Klemmer et al., 2006) which can advocate for a system’s transparency. Recent proposals include Experiential AI (Hemment et al., 2019) which uses felt experience to make algorithmic mechanisms more understandable. Graspable AI (Ghajargar et al., 2022) proposes the use of physical artefacts and material manifestations as a relational way for understanding and interpreting algorithmic systems.
The objective of this research is to provide insights for designing and analyzing web interfaces in academic, cultural, and industrial settings, with the goal of empowering users. Its ultimate aim is to question and challenge the opaque algorithmic models prevalent in surveillance capitalism and advocate for algorithmic transparency and legibility.
