STS in Africa: Techno

Cite as:

Okune, Angela. 2018. "STS in Africa: Techno." In PhD Orals Document: Querying Science and Technology Studies in Africa, created by Angela Okune. PhD Orals Document. UC Irvine Anthropology. October.


This essay answers the analytic question: “(How) does the analyst account for the data practices and responsibilities of the people and organizations studied?”. The studies explicitly looking at data practices (Tichenor 2017; Biruk 2018; Bezuidenhout 2017) had strong accounting for the data practices of their interlocutors, describing for example, a process of “rough approximations” which involved “filling out” the approximate diagnostic data performed by nurses, physicians, and laboratory technicians to produce a representation of malaria in Senegal (Tichenor 2017) and a misalignment of categories of data leading to desires for generating “our own data” (Tousignant 2018). Scholars had different perspectives on the travels of data noting the importance of location (Crane 2010; Hountondji 1990) but also the difficulty (impossibility?) of dissaggregating co-constructed knowledges (Tilley 2011; Osseo-Asare 2015). Few of the studies explicitly employed a technical analysis of the underlying infrastructures (other than some mention by Tilley 2010 and Foster 2017). Von Schnitzler (2013) argued that technology itself was a political terrain for the negotiation of moral-political questions about limits, entitlements and obligations of citizenship in South Africa.

This essay is part of a broader orals document by Angela Okune querying Science and Technology Studies in Africa. Sub-essays within the orals document can be accessed directly through the following links: Discursive Risk; Deutero; Meta; Macro; Micro; Nano; Techno; Data; Eco.

Angela Okune's Orals Documents in Brief

This essay is part of three orals documents submitted by University of California, Irvine Anthropology doctoral student Angela Okune i n partial fulfillment of her requirements for...Read more

Bibliography for Annotated Set

Bernal, Victoria. 2014. Nation as Network: Diaspora, Cyberspace, and Citizenship . University of Chicago Press.

Bezuidenhout, Louise, Ann H. Kelly, Sabina Leonelli, and Brian Rappert. 2017. “‘$100 Is Not Much To You’: Open Science and Neglected Accessibilities for Scientific...Read more


Given that within the annotated set Tichenor (2017), Biruk (2018) and Bezuidenhout’s research objects are directly related to data practices, they had strong accounting for the data practices of their interlocutors. Tichenor (2017) described a process of “rough approximations” which involved “filling out” the approximate diagnostic data performed by nurses, physicians, and laboratory technicians to produce a representation of malaria in Senegal. Tousignant (2018)’s interlocutors further support this point about misaligned categories of data, articulating a desire to generate their own data because poison as a cause of morbidity was not yet a category in national health statistics (“so poisoning might be recorded but was not always an accurate reflection of the causes of the problem”). Bezuidenhout et al. (2017) found that professional membership organizations, networking initiatives, data sharing sites, and Web 2.0 tools offered scientists important means of communicating with peers, gaining access to data resources, and disseminating their own data outside of traditional publication routes but that such data engagement channels and access to information are still severely curtailed due to micro-economic concerns. Biruk called out demographic surveys as "raising the specter of the exploitation, extractive logics, racism, and ethnocentrism that have underlain science in Africa" with a presumed "right to invade" in the name of knowledge production. Finding that the data produced by the demographers studied needed to be seen as objective, "clean", and reflecting reality, Biruk (2018) compared this to how anthropologists view (quantitative) data as a classificatory exercise that creates reality or "makes up" people. She acknowledged the contradiction inherent because anthropologists are also in the "data making" game and have particular investments in ideas of a particular kind of "good" data.

Other than these works focused explicitly on data, other scholars have accounted for how the data collected (by those they studied) travels (e.g. Crane 2010). Nonetheless, few described in detail the underlying technical infrastructures that facilitated such travel although Tilley (2011) noted factors including the greater organization of scientific congresses; shared nomenclature and methods; professionalization of the biosciences and field sciences; greater circulation of international scientific journals, and the standardization of laws regulating and defining science. Foster (2017) also noted her own use of email and Skype to build and maintain relationships when she was not physically in South Africa.

Crane (2010) noted that the ethics of HIV health research data is unique (as compared to data practices described in for example, Adriana Petryna’s work on clinical trials) because it is not just a unidirectional route from “periphery” (Uganda) to “center” (US). She described how the global health data travels through the Northern institutions that fund the research, but then returns back again to African countries where it is used to create evidence-based interventions for public health problems locally. Crane argued that these twin demands of being “relevant” to the South but answerable to the North made this research ethically fraught. Although not cited in Crane’s description of how HIV health data travels, I noted echoes of Hountondji (1990)’s concept of “impoverished (colonial) science” which he broke into three parts – data collection; theory-building; and practical application—to argue that while the first and last aspects of “science” were conducted in the colonies, because the intermediate step of synthesis and theory-building was taken outside of the African context (for “proper analysis” in Europe), the science was therefore deprived of the intellectual theory-building activity that in fact makes science, science. Here, Green’s point that careful study of how knowledge objects come to be generated brings attention to the ways in which research processes and the actors involved at different points throughout the processes result in the construction of particular realities. This discussion brings up important points about the territorial situatedness of knowledge and its global circulations. As Crane and Hountondji point out, location matters. But as Okeke’s statement and Tilley (2011) and Osseo-Asare (2015) demonstrate, knowledge is made through many different modes and many actors, in conflict/tension with one another and without necessarily following geographic and national boundaries. As Tilley aptly puts it, “knowledge may be situated, it is designed to travel,” (2011:10). This insight importantly points to some of the discursive risks of Bezuidenhout et al. (2017)’s work which studied use of information from online data platforms but focused only on access rather than generation of data by African scholars. This is a point I am keen to take up further in my own work.

Foster described experiencing the ethnographic refusal that Audra Simpson describes (“what you need to know and what I refuse to write in”) (2017: 24). As a group that has been heavily researched and do not feel they have benefited from the work, Foster outlined (and abided by) protocols and guidelines that the San people have put in place to try to ammeliorate/address the lack of benefits from research.

Viewing technology itself as a political terrain for the negotiation of moral-political questions about limits, entitlements and obligations of citizenship in South Africa, von Schnitzler (2013) described how technical expertise was produced in constant conflict with “expertise in the wild” or the ongoing cycle of “electricity poachers” who pull out, bypass, break, or rewire micro pre-pay devices requiring the constant innovation of new “anti-programs.” Geissler and Tousignant (2016) explained that capacity is meant to last, but to do so it must be “remembered, accumulated, repaired and protected,” echoing recent scholarly work looking at the unaccounted for labor that is often made invisible or forgotten (and therefore unplanned for with regards to technology interventions). This is described in the context of digital infrastructures by Crooks (2018) and also Kenner (2014) and is most obvious in different empirical examples like the failure of the Kenyan Jubilee government roll out of laptops for primary school children in Kenya.

To address perceived bureaucratic incapacity on the African continent, Breckenridge (2014) focused on how technologies of biometric registration came to be seen as the most promising remedy and a distinct break from older forms of written identification. Breckenridge also raised the point that Africa has been characterized as not having data. This narrative about an assumed “lack of data in Africa” is not only part of discussions within STS in Africa, this rhetoric is also encountered and echoed outside of the annotated set in recent blog posts (e.g. Hima 2018). Tilley (2011)’s work highlights that this “Africa has no data” rhetoric has been around since at least the 1884-85 Berlin conference, where the head of the Russian delegation told the conference that “precise data on the climate of Africa are absolutely wanting, whereas the [International] Meteorological Committee has already gathered them in every other part of the world,” (2011: 54).

Mavhunga (2014) noted the social network of people who were key nodes of information sharing (e.g. Javuendava, pg 155 and MaTshangana’s network, pg 180). He also notes some people as being key in shielding the information and protecting it (dying instead of sharing the info, pg 197) while others sold out and shared the information (pg 204). The data sharing infrastructures in this case are not technical but human, evoking Simone AbdouMalique's idea of "people as infrastructure" in an information sharing context.

Osseo-Asare (2014) explained that even in regimes of shared knowledge, such as open-source software development, participants developed ways to track their unique contributions, noting for example that scientists in Madagascar, Cameroon, Ghana, and South Africa inherited such individualistic approaches to knowledge management through their school systems (initiated during the colonial period) as well as the global standards for information sharing that they participated in after independence. She described “cultures of secrecy” both amongst healers and scientists in Africa as well as more general lack of preserved detailed records of their investigations. In contrast to the healers she worked with (who were open with sharing written records and recipes that had been published), the scientists Osseo-Asare engaged with were notably wary of speaking to a historian interested in observing them in their place of work and asking them questions about their personal research narrative. She wrote about shifts over time in how data practices and contributions towards knowledge objects were acknowledged, describing a move from colonial occupation which obfuscated the names of plant medicine experts who advised visiting botanists and chemists to practices in the 1950s by African nationalist scientists who sought to be added to the roster of discoverers, assigning their names to patents, papers, and products, but often continuing to omit the names of traditional healers or family members who had assisted them in their research. The continual shifting of norms and practices (in response to critiques raised over time) is particularly relevant in the current moment of great interest in both open data and its seemingly opposite: data protection.

A sampling of annotations

A few of the notable annotations are included below for quick review. Each can be clicked to view it fully. A full list of all annotations submitted under this analytic question can be found here.

AO. funded by the North with the intent for the data to return back for use by African countries

  • AO: Crane notes that because this HIV health data and research is not just taking a unidirectional route from periphery to center, the global health data travel through the Northern

  • ...Read more