[STS-Africa] CfP EASST/4S 2024: Making and Doing AI from Africa: Critical Insights on AI and Data Science

[Jia Hui Lee]

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· Submission Instructions: https://www.easst4s2024.net/callforabstracts/

· Deadline for Abstract Submissions: 12 February 2024

· Conference 16 – 19 July 2024





EASST/4S 2024 - Open Panel



Making and Doing AI from Africa: Critical Insights on AI and Data Science



Short Abstract:

This panel explores the questions of what analytical frameworks for the
social study of AI and data might look like when they are shaped by
knowledges and experiences from Africa and how understandings of concepts
such as intelligence, learning, and computing are contested in an African
context.

Long Abstract:

This panel grapples with two interrelated questions: What might analytical
frameworks for the social study of Artificial Intelligence (AI), machine
learning, and data science look like when they are shaped by knowledges and
experiences from Africa? How are understandings of key concepts, such as
intelligence, learning, data, digitality, virtuality, artificiality,
computing, and so forth contested in an African context? Several scholars
in African studies, anthropology, information science, and other allied
fields have argued for analyses of technology that do not take for granted
systems of knowledge based in Europe and the West (Archambault 2017; Hassan
2022; Newell and Pype 2021; Nyabola 2018). Africans and other communities
in the Majority World have been grappling with the social and political
effects of AI and data science. Kenyan employees have reported experiencing
post-traumatic stress disorder as a result of labeling datasets and
moderating AI content for OpenAI and Facebook. Mobile phone companies
continue to collect and use personal information of their African users
while expanding demand for its uses. Several African cities have embarked
on projects of ‘smartness,’ including rolling out digital platforms for
government services, monitoring environmental change with sensors, and
supporting innovation hubs, such as Yabacon Valley and Konza Technopolis.
As some quarters embrace digitization, others have warned of a new
algorithmic (Birhane 2020) or digital colonization. We invite papers that
examine African experiences of AI and data that intervene into discussions
about labor, ethics, environmental impact, governance, practices of data
collection, and innovation. We encourage, but not limited to, presentations
that articulate how African experiences of AI and data might contribute to
analytical frameworks for a critical study of AI and data.

Convenors:

Yousif Hassan (University of Michigan)
Kwame Edwin Otu (Georgetown University)
Kebene Wodajo (University of St.Gallen)
Jia Hui Lee (University of Bayreuth)
Laila Hussein Moustafa (University of Illinois)
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