Skip to main content

Search

West Africa

Misria
Annotation of

At the height of the West African Ebola epidemic, West African governments and Mobile Network Operators (MNOs) were barraged with requests from international humanitarian and Western data analytics agencies to provide Call Detail Record data. This data could furnish the large-scale ambitions of data modelling to track and predict contagion. Despite its utility in tracking mobility and, as such, disease, CDR’s use raises many privacy concerns. In addition, embedded within a turn towards datafication, CDR technologies for surveillance embed specific ontologies of the data-focused society they emerge from. There is a false equivalence embedded in the relationship between humans and technology. The predominantly Western idea that one phone equals one person underlines the claim that CDR data accurately tracks distinct user movements, encoding a Western “phone self-subjectivity” (Erikson 2018). However, the refusal by some African actors to hand over sensitive mobile data to international agencies was met with forceful rhetoric of Africa’s moral obligation to comply—to forgo privacy rights in the name of ‘safety.’ The Ebola context reflects an emergent digitization of emergencies in the Global South, which is reshaping the way societies understand and manage emergencies, risk, data, and technology. The big data frenzy has seen a rising demand to test novel methods of epidemic/pandemic surveillance, prediction, and containment in some of the most vulnerable communities. These communities lack the regulatory and infrastructural capacity to mitigate harmful ramifications. With this emergence is a pivot towards 'humanitarian innovation,' where technological advancements and corporate industry collaboration are foregrounded as means to enhance aid delivery. In many ways, these narratives of innovation and scale replicate the language of Silicon Valley’s start-up culture. Surveillance of the poor and disempowered is carried out under the guise and rhetoric of care. In this scenario, market ideals and data technologies (re)construe social good as dependent on the “imposition of certain unfreedoms” as the cost of protection (Magalhaes and Couldry 2021). As big data technologies, they foreground a convergence of market logistics and global networks with existing and already problematic international humanitarian infrastructures (Madianou 2019). These convergences create new power arrangements that further perpetuate an unequal and complex dependency of developing countries on foreign organizations and corporations. Pushback against these data demands showcases competing notions of where risk truly lies. While resistance to data demands was at the state level, community responses to imposed epidemic regulations ranged from non-compliance to riots. These resistances demonstrated how the questions of ‘who and what is a threat?’ or ‘who and what is risky?’ and ‘to whom?’ experience shifting definitions in relation to these technologies as global, national, and community imaginaries are reinforced and reproduced as cultural, political, as well as biological units. 

Source

Akinwumi, Adjua. 2023. "Technological care vs Fugitive care: Exploring Power, Risk, and Resistance in AI and Big Data During the Ebola Epidemic." In 4S Paraconference X EiJ: Building a Global Record, curated by Misria Shaik Ali, Kim Fortun, Phillip Baum and Prerna Srigyan. Annual Meeting of the Society of Social Studies of Science.

West Africa

Misria
Annotation of

(MNOs) were barraged with requests from international humanitarian and Western data analytics agencies to provide Call Detail Record data. This data could furnish the large-scale ambitions of data modelling to track and predict contagion. Despite its utility in tracking mobility and, as such, disease, CDR’s use raises many privacy concerns. In addition, embedded within a turn towards datafication, CDR technologies for surveillance embed specific ontologies of the data-focused society they emerge from. There is a false equivalence embedded in the relationship between humans and technology. The predominantly Western idea that one phone equals one person underlines the claim that CDR data accurately tracks distinct user movements, encoding a Western “phone self-subjectivity” (Erikson 2018). However, the refusal by some African actors to hand over sensitive mobile data to international agencies was met with forceful rhetoric of Africa’s moral obligation to comply—to forgo privacy rights in the name of ‘safety.’ The Ebola context reflects an emergent digitization of emergencies in the Global South, which is reshaping the way societies understand and manage emergencies, risk, data, and technology. The big data frenzy has seen a rising demand to test novel methods of epidemic/pandemic surveillance, prediction, and containment in some of the most vulnerable communities. These communities lack the regulatory and infrastructural capacity to mitigate harmful ramifications. With this emergence is a pivot towards 'humanitarian innovation,' where technological advancements and corporate industry collaboration are foregrounded as means to enhance aid delivery. In many ways, these narratives of innovation and scale replicate the language of Silicon Valley’s start-up culture. Surveillance of the poor and disempowered is carried out under the guise and rhetoric of care. In this scenario, market ideals and data technologies (re)construe social good as dependent on the “imposition of certain unfreedoms” as the cost of protection (Magalhaes and Couldry 2021). As big data technologies, they foreground a convergence of market logistics and global networks with existing and already problematic international humanitarian infrastructures (Madianou 2019). These convergences create new power arrangements that further perpetuate an unequal and complex dependency of developing countries on foreign organizations and corporations. Pushback against these data demands showcases competing notions of where risk truly lies. While resistance to data demands was at the state level, community responses to imposed epidemic regulations ranged from non-compliance to riots. These resistances demonstrated how the questions of ‘who and what is a threat?’ or ‘who and what is risky?’ and ‘to whom?’ experience shifting definitions in relation to these technologies as global, national, and community imaginaries are reinforced and reproduced as cultural, political, as well as biological units. 

Akinwumi, Adjua. 2023. "Technological care vs Fugitive care: Exploring Power, Risk, and Resistance in AI and Big Data During the Ebola Epidemic." In 4S Paraconference X EiJ: Building a Global Record, curated by Misria Shaik Ali, Kim Fortun, Phillip Baum and Prerna Srigyan. Annual Meeting of the Society of Social Studies of Science. Honolulu, Hawai'i, Nov 8-11.

pece_annotation_1476039783

xiaox
Annotation of

FEMA has involved in fire grants, preparedness, mitigation and individual assistance in different emergency response. FEMA aim to recover after disaster in short term, and also rebuild and finance support for local government in long term.

However, from some research shows that FEMA seems is not good to approach disaster or emergency response. For the Hurricane Katrina in 2005, FEMA received negative criticism because of the slow response, un-effective assistance. Besides, FEMA also has intense criticism in others disaster, such as Buffalo snowstorm (2006) and California wildfires (2007).

pece_annotation_1476039950

xiaox
Annotation of

The law has signed for emergency triggers financial and physical assistance through the FEMA. It is also funding for training as agency’s preparedness effort. It shapes the way of prepare for hazards, and make a better intergovernmental coordination.

 

pece_annotation_1476039969

xiaox
Annotation of

There is an interactive tool which can search some grant data by location and disaster. They apply diagram to show the data and easy to analyse. For example, Summary of Disaster Declarations and Grants which can see the Federal declared disaster occurred in each state, and also summary of FEMA’s support for fire, preparedness, mitigation, and assistance. There are also other graphics show different data of disaster and FEMA assistance.