Improving outcomes from Information and Communication Technology for Development (ICT4D) studies

ABSTRACT: Research in Information and Communication Technologies for Development (ICT4D) is becoming increasingly diverse. The reason being that the last decade has seen, in line with the growth in the availability and use of information and communications technologies (ICTs), a large increase in the number and range of published work on the topic which draw upon a whole range of disciplinary approaches (Walsham, 2017). While drawing upon theories that help understand emerging phenomena, research in ICT4D also requires attention to the contextual challenges facing practitioners in the field. There have been attempts to develop theories that enable these challenges to be understood. Global pressures, socio-economic pressures, disruptive technology, and the emergence of multi-stakeholder networks are some of the forces being studied (Njihia and Merali, 2013). For scholars hoping to draw upon this area, this issue offers a snapshot of papers that illustrate the proliferation of technologies and contexts in which they are implemented. They highlight a glimpse of the key contributions of research in this area while describing the challenges.

Keywords: Mobile money, socio-technical, actor-network theory, Enterprise resource planning, customer relationship management

Why Data Matters for Development? Exploring Data Justice, Micro-Entrepreneurship, Mobile Money and Financial Inclusion

ABSTRACT: With the widespread extraction of very large datasets, artificial intelligence using machine learning hold the promise to address socio-economic problems such as poverty, environmental safety, food production, security and the spread of disease. These applications entail Big Data for Development in which social problems, poverty, food security and responses to climate disasters can be solved in the most efficient and effective manner. This brave new world of solving pressing problems through machine learning has several dark sides. A data divide is being created that leaves the most vulnerable populations out of the solutions being created while discriminating against those whose data is churned by obscure algorithms. Complex mathematical models together with computing algorithms produce scores that are used to evaluate the lives of the masses. These systems have scaled to enormous proportions, changing lives by affecting credit scores, job prospects and access to healthcare. The promise of fairness, transparency, cost-effectiveness and efficiency gives rise to powerful scoring algorithms that have the power to create mass devastation while discriminating against the most vulnerable. Questions arise as to: What injustices (types of injustice) are created by datafication of development? how can the injustices caused by the extraction, analysis and commoditization of data be alleviated? Who has access to and what is being done with private data? And for whose benefit or purpose is personal data being extracted? Such questions are explored through the contributions in on data justice, the use of ICTs by micro-Entrepreneurs, mobile money and financial inclusion offered through papers in this issue.

Keywords: Artificial intelligence, Mobile money, Micro-Entrepreneurs, Big Data for Development