Towards Algorithmic Experience

Algorithms currently have direct implications in our democracies and societies, but they also define mostly all our daily activities as users, defining our decisions and promoting different behaviors. In this context, it is necessary to define and think about how to design the different implications that these algorithms have from a user centered perspective, particularly in social media platforms that have such relevance in our information sources and flow. Therefore, the current thesis provides an introduction to the concept of algorithmic experience, trying to study how to implement it for social media services in cellphone devices. Using a Research through Design methodology supported by interface analysis, document analysis and user design workshops, the present paper provides results grouped in five different areas: algorithmic profiling transparency, algorithmic profiling management, algorithmic awareness, algorithmic user-control and selective algorithmic remembering. These five areas provide a framework capable of promoting requirements and guide the evaluation of algorithmic experience in social media contexts.

Introduction. We are currently surrounded by algorithms (Willson, 2017). We appreciate how they ease our lives in many ways, deciding which the most efficient way to go is or selecting which are the most important news to follow. We also let them guide us: Diakopoulos express that Facebook‟s News Feed is the main government and politics source for 61% of millennials (2016, p. 56). In the same way, algorithms could be used as propaganda weapons to change peoples ́ believes and tendencies (Anderson & Horvath, 2017). It can be argued that algorithms govern our societies through shaping the interrelation between human and non-human actors. Introna (2015) explains how algorithms are not just sequences of instructions, but create relations and new meanings of the objects they work with in situated contexts (2015, p. 20). The nature of algorithms is part of the socio-material dynamics in our society, they are not only technical entities (2015, p. 23).

Discussion / Conclusion. Algorithmic experience constitutes a new way to analyze and describe design requirements in systems that possess algorithms in charge of profiling, trending and filtering information for the users, decisions that affect daily life and even societies. The current thesis suggests five areas to take into account for achieving a better user experience in Facebook‟s news feed in mobile devices, but they also could promote a more general solution for social media. First, algorithmic profiling transparency is an important aspect that provides the users the chance of noticing how the system is managing his or her behavior to provide a certain algorithmic results in any social media service. In any social media platform, profiling transparency allows the users to understand what the system knows about them, how it works and how the offered results are related to that profiling.