Analyze

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.

(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.

            This past spring break (2016), on a Monday night while at home, I responded to a motor vehicle accident as a Good Samaritan. The accident happened at approximately 19:00 hours on my street in Blackstone, Massachusetts. My father was on our front porch when he heard a car barreling down our back country road which has a long straight away before taking a sharp turn. Before the impact he knew that the driver would not anticipate the curve fast enough at the speed he was traveling. Sure enough, there was a loud bang and the sound of a car rolling over, which I could hear from inside the house (approximately ¼ mile from crash).

I grabbed both of my personal first aid kits and a flashlight while my father called emergency services. I walked to scene with my father and younger brother. I sped walked and arrived at the crash site first.

The vehicle was a ‘90s sedan that went straight into a telephone pole, which broke like a toothpick, and rebounded backwards and flipped 90 degrees on its left side. Parts of the car, tools, and glass were on ground, airbags deployed. There was a car seat in back, and for a moment I thought a child but it was just clothing. Front right tire was up inside front passenger compartment. Hazards flashing. Driver window was rolled down. No people in the car.

My brother and father directed traffic on either end of the crash site. They almost certainly prevented at another crash by a car who didn’t see the accident but saw my brother flag them down with his light.

I saw man standing 20’ from crash site, talking to people in a gold SUV. When I arrived I start asking medical questions and the people in the SUV leave – they were by standards who pulled up but left after I started taking over. The man in question appeared to be a lower/middle class white/Hispanic, male in his 30s. He was driving an older car with lots of tools in the back which were now all over the road. Our neighborhood is a small country community and I know he was not from our neighborhood. I assumed he was some kind of mechanic, bases on tools in car. He was wearing dirty jeans and stained hoodie. He was definitely a blue-collar worker. He may have been from downtown Blackstone which is largely lower middle class and blue collar, or he may have been from Woonsocket, Rhode Island, which is known as “the Detroit of Rhode Island”.

As I tried to obtain basic medical information from the patient, it was apparent he had an altered mental status, and did not appear to understand fully what was going on. I am not certain if it was alcohol and/or drugs as for safety reasons I did not get close enough to the patient/suspect to tell. He was ambulatory and verbal. The interesting part of our conversation was to the best of my ability as follows:

“Are you sure you’re okay? Umm yeah. Are you hurt anywhere? I’m fine. [I did visual inspection of patient using flashlight which revealed no major injuries other than minor cuts from airbag]. [He starts to edge away from scene]. You should wait for ems to check you out. Wait, you’re right! I might die?! You appear to be okay externally but things like internal bleeding, and a full assessment could reveal other problems. Naaaa [turns and starts to walk away down street]”

I attempted to convince the patient to wait on scene but he was going through several mode swings during my interactions with him from fear, anxiety, agitation, and anger. While I was talking to the patient, the first officer from the neighboring town arrived on a motor cycle. I informed the officer at the scene of the situation about the patient/suspect fleeing the scene. The officer took note of it and continued to work to secure the crash site. Another officer arrive from my town from the west. I informed the same and he stated that he would need me to make a witness statement and proceeded to the crash site. A third and fourth officer arrived together the same time as two ambulances (indicated because of rollover) from the east. One of them told me again that they would need a witness statement.

I met back up with my dad and brother who were no longer needed to control traffic with law enforcement on scene. Neighbors had started coming out to see the commotion. We were all talking near the scene while waiting for officers. Finally one of the officers asked another officer if he should go look for the suspect. He left approximately 20 minutes after my last contact. I never spoke with the arriving EMS as they came from the east and I was on the west of the accident but officers told them that the patient was missing. Eventually multiple officers and cars were out looking for patient/suspect but was not found as far as I am aware. I finally was given the chance to give my testimony which, to the best of my knowledge, mirrors this report. After reading out loud in front of the officer and my father and brother to confirm accuracy, the officer asked me something very strange. First, he asked me to add what the suspect was wearing (which I had forget to include), but then he also asked me to state that I saw the suspect drive into the telephone pole and that I smelled alcohol on the patients breath. Neither of these things were what I told any of the officers and ran counter to my testimony as written. I include the suspect’s clothing description but I did not add the second mention and stated that I had not witnessed those things. After my report I left the scene with my brother and father.

Some of the policies and procedures relevant to this case were: scene safety, dealing with aggressive/combative patients, and HIPPA did not apply to me as a bystander so I gave full testimony including medical status to the officers.

After reflecting on the education I received and didn't receive, there are a few things that would have allowed me to be better prepared for this incident. How do I convince patients to stay on scene? When do you give up? I wish my EMT class was a little better scene on safety training. Being distracted by the emergency at hand, I did not truly take into account the fact that the power lines were live and drooping with half of the telephone poll pulling on them. Only supported by the next and previous poll but not drooping more than 3’ from normal, more than 15’ from ground, and 10’ above vehicle. Reflecting on it, I did not really consider the threat as I should have, and neither did the officers on scene. I don’t understand why it took so long for police to search for the suspect who could have had major medical issues. Should I have followed suspect/patient alone? When is a citizen arrest allowed/appropriate? Should I have asked for the badge number of the officer who asked me to misrepresent the truth on an eye witness testimony? What is the process to do that anyway? If I had the answers to these questions I feel I may have been able to provide better assistance, but then again perhaps not.

Figure 1 was built to serve members of the medical community. It was developed to share unique medical conditions and discuss diseases amongst doctors, nurses, and students.

Healthcare professionals, from all levels, doctors to even students, are invited to share and discuss conditions and diseases. 

The Figure 1 website does not specify how the development of the system was funded. 

Verified members can post pictures of patient's, tests, equipment, or images as long as there is not patient identifying information. All members of figure one are encouraged to comment and discuss the condition or test in the picture. 

Users can access the site from a computer or there is an app available for smart phones. 

This system would be difficult to work with because it publicises patient's  conditions even if it does not directly identify who they are. Some of the diseases or conditions these patients are faced with can be considered humiliating and while the intent of the app is to be educational, a healthcare professionals are faced with the ethical decision as to whether or not post the picture of their patient. A guideline Figure 1 outlines is that before taking and posting a picture the provider should have consent from the patient. Hospitals, clinics, agency, ect. are also faced with whether to allow their members to engage in these activities as patient confidentiality could be called into question. 

Figure 1 was developed as a platform to serve medical professionals and students by providing widespread access to information on medical cases and enable discussion among medical professionals.