Using Activity Theory to Understand Technology Use and Perception among Rural Users in Uganda

Implementing technologies in developing communities often involves working with people that have a very different context from the researcher in terms of lower literacy and less experience with technology. Having worked with three rural communities in Uganda and introduced an Information and Communication Technology (ICT) intervention for water management, we use activity theory to analyse people's activities in relation to the use and uptake of the community-based ICT tool. To understand the contextual factors that influence the use of the tool, we proceed from our activity theory analysis and we unpack the perceptions and attitudes that rural technology users have towards technology. Our findings provide insights into what motivates and demotivates people in rural communities to use ICTs. We use our findings to substantiate the relevance of the intangible impacts of ICTs such as empowerment, social cohesion and improved self-worth for rural technology users. We recommend that technology designers be open to the unintended uses of the technologies they introduce in rural communities

The perception of technology and data, and its impact on data governance decisions - A study on low literate women farmers in agricultural co-operatives of India.

In this master’s thesis, I study how low-literate women farmers perceive farming technology and data, and how it affects data governance decisions. My focus is on women owned farmer co-operatives in rural India, and my study is motivated by the research gap in understanding how participatory data governance is affected by literacy, socio-cultural norms, and community values within a co-operative structure. The Case study (based on the Megha Mandli co-operative in Gujarat) shows that the women farmers value a sense of pride and status and are open to technology that conforms to these values. They also seek to be empowered to make informed farming decisions independently, and are not only willing to adopt technology that enforces such values, but also contribute to a governance model that governs it. However, I find that there is a huge gradient in technology literacy and access within the community. A few women farmers are well adept to such interventions, while the poorer farmers are dependent on their peers to share the benefits of technology with them. Also, the understanding of data in general is very limited and often not a priority for the farmers. Hence, the level of participation in data governance can vary highly – which is a hinderance to creating an effective bottom-up governance model. The study also finds that socio-cultural values have a big impact on data governance, as is the case currently in Megha Mandli. Data sharing happens mostly upon the values of sisterhood and trust within the community. Women with better access and literacy help bring benefits of technology and data to the rest of the women, purely based on their willingness to do good for the community. Meanwhile, the poorer farmers have absolute trust in their peers as well as the co-operative management that their data will be used for their own benefit. Thus, the current form of cooperative governance is influenced heavily by socio-cultural norms rather than robust legal and formalized frameworks. Although these norms are important to consider in making governance decisions, an overdependence on them leaves room for exploitation. For instance, the process of obtaining ‘informed consent’ is almost redundant given the absolute trust the women farmers have on the co-operative management, leading them to accept most suggestions made to them. As such, this study demonstrates that farmer cooperatives in low-literate settings must employ resources to identify and level the gradient in literacy and accessibility of data and technology. Without such efforts, mechanisms for farmer participation in data governance will fall through. There must also be a balance between the use of Socio-cultural norms and legal formalised frameworks in data governance models, such that the farmers are not left vulnerable to exploitation at the expense of respecting community norms