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Daniel Mwesigwa

Publications and source records attributed to Daniel Mwesigwa.

4 recordsLinked to original sources

Exchange, obligation, accountability: Moral orders of technology repair in Kampala, Uganda

This chapter develops the concept of moral orders of repair, defined as the specific norms, rules, values, and expectations that structure and support joint work and exchange in repair worlds and other spheres of collaborative practice. Drawing on ethnographic fieldwork in mobile phone and computing repair markets in Kampala, Uganda, we identify three key dimensions of moral orders: fair exchange, collaboration across hierarchy, and relational accountability. We show how moral orders provide a detailed specification of informal rules gestured as implicit in moral economies, and how these rules inform the practical and ethical work of repair.

cs.CY

To Tango or to Disentangle? Making Ethnography Public in the Digital Age

Ethnography attends to relations among people, practices, and the technologies that mediate them. Central to this method is the duality of roles ethnographers navigate as researchers and participants and as outsiders and insiders. However, the rise of digital platforms has introduced new opportunities as well as practical and ethical challenges that reshape these dualities across hybrid media environments spanning both online and offline contexts. Drawing on two case studies of VRChat and WhatsApp, we examine how ethnographers employ diverse tactics to study both enduring and emerging socio-cultural issues of race and caste, particularly those that form what are often called publics. We propose emergent relationality as a key analytic for understanding the mutual shaping of ethnographers, platforms, and publics. In this work, emergent relationality offers registers for analyzing how positionality and hybrid media environments constitute and condition what can be accessed, articulated, and made public.

cs.CY

Risk, Data, Alignment: Making Credit Scoring Work in Kenya

Credit scoring is an increasingly central and contested domain of data and AI governance, frequently framed as a neutral and objective method of assessing risk across diverse economic and political contexts. Based on a nine-month ethnography of credit scoring practices in Nairobi, Kenya, we examined the sociotechnical and institutional work of data science in digital lending. While established regional telcos and banks are leveraging proprietary data to develop digital loan products, algorithmic credit scoring is being transformed by new actors, techniques, and shifting regulations. Our findings show how practitioners construct alternative data using technical and legal workarounds, formulate risk through multiple interpretations, and negotiate model performance via technical and political means. We argue that algorithmic credit scoring is accomplished through the ongoing work of alignment that stabilizes risk under conditions of persistent uncertainty, taking epistemic, modeling, and contextual forms. Extending work on alignment in HCI, we show how it operates as a two-way translation, where models are made "safe for worlds" while those worlds are reshaped to be "safe for models."

cs.HC

Against 'softmaxing' culture

AI is flattening culture. Evaluations of "culture" are showing the myriad ways in which large AI models are homogenizing language and culture, averaging out rich linguistic differences into generic expressions. I call this phenomenon "softmaxing culture,'' and it is one of the fundamental challenges facing AI evaluations today. Efforts to improve and strengthen evaluations of culture are central to the project of cultural alignment in large AI systems. This position paper argues that machine learning (ML) and human-computer interaction (HCI) approaches to evaluation are limited. I propose two key conceptual shifts. First, instead of asking "what is culture?" at the start of system evaluations, I propose beginning with the question: "when is culture?" Second, while I acknowledge the philosophical claim that cultural universals exist, the challenge is not simply to describe them, but to situate them in relation to their particulars. Taken together, these conceptual shifts invite evaluation approaches that move beyond technical requirements toward perspectives that are more responsive to the complexities of culture.

cs.HC