We are experiencing an explosion in the amount of data being collected about individuals. We leave digital traces as we move through both physical and virtual worlds. We track our moods, activities, and friends through social networking sites, wireless devices, and smartphone apps. Medical, financial, and social diagnostics reveal our pathologies, rank us among our peers, and potentially open up new pathways for health and well-being. Our numerate shadow selves travel through networks and join with others in unexpected and unpredictable ways, illuminating new identities and socialities. In EVOKE, we are investigating our evolving and expanding reliance on algorithms, numeracy, and quantification as tools for understanding who we are.
This interest in the relationship between ourselves and our data takes a number of directions, investigating several interrelated concepts and issues. For example, the increasing amount of personal data challenges our notions of privacy, anonymity, and data ownership. New surveillance technologies track individuals, creating pervasive digital histories in ways that challenge our belief in a boundary between public and private spheres. Data are increasingly mobile, easily traveling beyond the planned sites of use and into places and uses we would not have imagined. In a “big data” world, individuals can be re-identified in anonymous data through relatively simple combinations of publicly available datasets.
Another key issue surrounds the relationship between our data avatars and ourselves. How do these new forms of data support self-analysis, reflection, and personal biography? To the extent that an individual is represented in data, is that representation accurate and complete? What work does our data do on our behalf, and under whose authority? What are the consequences of so much personal data for the development of communities and societies, and does this data lead to new forms of biosociality or technosociality?
We are also concerned about the uneven distribution of access to and representation by data. When data are driving important decisions in government, markets, and society, it is imperative to ask who is being left out of the data landscape. Are those who cannot afford high-speed internet, smartphones or other high-tech devices rendered invisible to policy makers? Are people who do not wear connected activity sensors at a health care disadvantage? And what about those who choose to disconnect – how well are they able to hide their traces and control their online representations if they so choose?
We use a combination of methods to investigate these questions. We interview participants and key stakeholders. We become participants and observe communities as they encounter these issues and manage their interactions with and through data. We conduct surveys and quantitative studies of attitudes and behaviors. We use design as a way to engage with theoretical and conceptual issues. We question the values invoked by and embedded in the technologies of personal data collection. Through these activities, our goal is to build a deeper and more nuanced understanding of these issues while helping designers, policy makers, and individuals frame the debates and craft appropriate responses and decisions.