The Algorithmic Pandora’s Box: Technologies for Poverty Targeting in Colombia

Description of research project: 

My dissertation ethnographically explores the design and implementation of the algorithmic decision-making system for social program allocation in Colombia - Sisbén. I analyze how this system recreates specific understandings of poverty while(re)producing specific values of society with differentiated effects on the more vulnerable. My analysis of Sisbén reveals how the design and uses of states’ technological tools to classify people/households according to their socioeconomic status translate political debates, cultural understandings, bureaucratic practices, and academic approaches to understanding and defining poverty into the technical terms of datafication. These translations do not eliminate the multiple debates, understandings, practices, and approaches, but commensurate them by showing how social actors appropriate and experience these technologies differently.

Description of work that will be assigned to research assistants: 

During this semester, I plan to work closely with the research assistant in organizing (classifying and coding) and making a preliminary analysis of online data about Sisbén that I have collected from social media since 2018. These consist of Instagram, YouTube, and Twitter posts made both from the official accounts of Sisbén and from citizens. I envision this as an exercise in learning the basic elements of digital ethnography. Since all the data is in Spanish, the research assistant needs to have excellent Spanish reading skills.

Supervising Faculty Member: Luciana de Souza Leao

Graduate Student: Margarita Maria Rodriguez Morales 

Contact Information: mmrodri@umich.edu

Average hours of work per week: 6-8

Range of credit hours students can earn: 2-3

Number of positions available: 1