In the ”Studying User Perceptions and Experiences with Algorithms” workshop, there were many interesting questions popping up. Here are some of them:
- Will increased awareness of algorithm functionality change user behavior? How
- How can we build better algorithms to diversify information users are exposed to?
- Do most people care about knowing how Google works?
- What’s the ”count to 10” equivalent for online discussions? How to avoid snap judgments?
- How to defuse revenge seeking in online discussions?
- What are individuals’ affective relationships with algorithms like?
These make for great research questions.
The relationship between users and algorithms is always a mediated one, meaning that there is always a proxy between the algorithm and the user. The proxy can be understood differently based on the particular level we’re interested in. For example, it can be a social media platform (e.g., Facebook, Twitter) where people retrieve their news content (Nielsen & Schrøder, 2014). Or, at a closer level of interaction, it can be understood as user interface (UI). The following picture illustrates this thinking.
Figure 1 Mediated relationship between users and algorithms
In both cases, however, the interaction – and therefore the experience of the user – is mediated by a proxy entity. This is a critical notion when examining the interaction between algorithms and users because such a thing cannot exist in pure form. Essentially, the research of algorithms deal with how algorithms transform into user experience. Through the mediating nature we can build phenomenological bridges to technology adoption, such as TAM2 and UTAUT and models (Venkatesh & Davis, 2000; and Venkatesh et al., 2003, respectively) or generally to experience of technology usage, examined e.g. in human-computer interaction (HCI) literature (see Card et al., 1983; Dix et al., 2003).