These conceptual lenses offer structured ways of thinking about the social and ethical contexts relevant to each stage of the data science lifecycle.
What is a lens?
Conceptual lenses offer structured ways of thinking about the social and ethical contexts relevant to each stage of the data science research process.
Each lens represents a theoretical stance connected to specific ethical problems or questions. Lenses details how, when, and why data is produced, and by whom. They also make visible possible interconnections between infrastructures, institutions, and individuals that impact research question development and the research process.
Four Lenses for Data Science
We have selected four lenses through which to examine the data science research process: Positionality, Sociotechnical Systems, Power, and Narratives. Each lens offers a perspective through which to examine the research and consider its ethical dimensions. Lenses are also interdependent, highlighting the complex nature of interactions between research and society.
Diversity of human experience
A person’s capacity to consider how opportunities and limits of their identity, expertise, or personal situation are shaped by their environments and inform their perspectives and actions.
Technology interacting with society
The reciprocal influences between technical systems and individuals who design, develop, and operationalize them; the hybrid nature of organizations in which individuals and technological actions are constantly interacting with one another.
Asymmetries in agency
A person or technology's asymmetric capacity to structure or alter others' behavior. Scientific and technological powers are always intertwined with political and socioeconomic power.
How we talk about how the world works and what futures are worth pursuing. In science, researchers develop an argument (a claim) supported by pieces of evidence (data) collected in their field world.