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- Convenors:
-
Dominique Somda
(HUMA-UCT)
Azza Mustafa Ahmed (HUMA - Institute for Humanities in Africa, UCT)
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- Format:
- Panel
- Sessions:
- Monday 6 June, -
Time zone: Europe/London
Short Abstract:
This panel focuses on AI in healthcare in the context of the Global South. We want to invite contributors to explore data collections by and for AI powered machines in hospitals and beyond, and the expected and unforeseen consequences of their extraction.
Long Abstract:
This panel focuses on AI in healthcare in the context of the Global South. We want to invite contributors to explore data collections by and for AI powered machines in hospitals and beyond. We aim to examine the nature of the data involved (including their social and scientific constructions as data), and the expected and unforeseen consequences of their extraction.
Middle- and low-income countries are not only more subjected to inequalities and less likely to benefit from AI, tailored to their specific local needs - they are also less likely to benefit from data protection laws and regulations. Risks of data mining and data looting in the Global South are not dissimilar to those weighing on economically and politically disenfranchised populations in the Global North. We will comparatively explore the geopolitics of data exploitation.
We wish to critically reflect on the various iterations, understandings, and implementations of the rights included in data ethics discourses and human rights instruments (i.e., the rights to privacy, transparency, ownership, consent, openness). Anthropologists can provide invaluable context to unveil the various constraints that individuals and stakeholders face - some of which undermine the processes designed to protect rights to data protection in healthcare systems.
Finally, we will consider the coloniality of data and the hegemony of representation and quantification of populations in global health.The technological innovations and capitalist ventures we are exploring in the panel exist in continuity with the structures and practices that preceded them, as legacies of the missionary and colonial healthcare systems.
Accepted papers:
Session 1 Monday 6 June, 2022, -Paper short abstract:
Personalized learning digital adherence tools make use of data from individuals taking medication. The question is, how do individuals feel about use of data and how is security of data in the global south. We would like to develop a theoretical framework to understand acceptability of such DATs.
Paper long abstract:
Adherence to treatment for individuals with chronic or longterm conditions, such as people living with HIV, multi-drug resistant tuberculosis patients, diabetes patients and people with cardiovascular diseases, is important. Digital adherence tools have been developed for monitoring adherence and intervening when necessary. Currently, such tools are not designed to intervene in a completely personalized manner. Artificial intelligence could help to intervene when adherence is low through, for example, medication reminders or triggering health care workers to provide extra counseling.
Using machine learning for development and continuous learning through medication intake algorithms, requires continuous use of medication intake data. However, end-users may not accept such interventions as it may lead to the feeling of 'big brother is watching you'. In addition, in the global south, there may be issues related to data security and end-users may also feel threatened by that. We propose to develop a theoretical framework investigating factors that may hamper acceptability of digital adherence tools that make use of machine learning principles among people living with chronic conditions in Tanzania. We will develop an algorithm for learning adherence patterns through existing or proposed studies in Tanzania. Based on existing theoretical frameworks for acceptability of interventions and other factors that play a role in these kind of interventions, we will collect data from end-users to inform development of a new theoretical framework for acceptability of digital adherence tools including artificial intelligence. The framework will, in future, contribute to development of better accepted interventions.
Paper short abstract:
The paper explores the hopes and fears of medical professionals as healthcare centers digitize their processes in compliance with the new regulations on data protection. Interpreting, circulating, and archiving data through digital instruments and platforms create new tensions.
Paper long abstract:
With this presentation, I aim to examine the evolving configurations of secrecy, privacy, and transparency in the e-health era in Africa. What are the data for? In Benin, medical professionals themselves interrogate their changing strategies to protect the data of their patients and intentions behind data collections and interpretations, as digital platforms and instruments are massively adopted in healthcare centers. This presentation analyzes the discourses and practices of doctors, nurses, administrators, and developers who engender new relations to the data they produce.