As a social scientist working on the intersection of technology and politics, my work is focused on providing evidence that can inform policy processes on information technology. One of the key academic question I keep coming back to is how does the flow of information in a society affect its power relations? Stated otherwise, how do the processes of data access, collection, processing, storage and sharing relate to individual consent, corporate interests and state authority?

This general question has led my research through various projects as explained below.

National Security and Internet Freedom: What laws underpin this relationship in Ethiopia, South Sudan and Kenya?

As countries in Eastern Africa confront both domestic and foreign security threats, and especially terrorism, laws and regulations have been seen as necessary interventions to create the capacity of national security agencies achieve their end-state. These legal instruments have more often than not led to increased information controls in the form of censorship, surveillance, physical arrests and torture of individuals holding or sharing information considered a threat to national security. Internet tools like websites, blogs, messaging platforms among others have been highly targeted owing to their potency to scale information to masses.

My research has been to understand from a comparative perspective the nature of information controls and laws underpinning them, existing oversight structures and what, if any, counter-controls are observed in the three countries.


Internet Access and Freedom of Expression: Applying the Technology Diffusion Model in Four Counties in Kenya.

This study explores the question whether there is differentiated access to the Internet in four counties in Kenya and if so, what factors explain the variance. Further, the study seeks to test whether differentiated access to the Internet affects people’s freedom of expression.

The study adopts the Technology Diffusion Model to look at how technology interacts with geographical from an economic point of view, focusing on the relationship between a country’s historical rate of technology adoption and its per capita income.

In the model of technology diffusion and growth, Comin and Hobijn link the adoption lag of a technology (the length of time between the invention and adoption of a technology) to the level of productivity embodied in the capital associated with the technology. From their analysis of 15 technologies (the Internet included), in 166 countries between 1820 and 2003, two points are worth considering for this study; the longer the lag in technology adoption for any given nation, the lower the per capita income and newer technologies diffuse faster across the globe compared to older ones. If we hold that to current cross-countries comparison, why doesn’t the shrinking gap in technology adoption lags naturally lead to a smaller disparity between per capita incomes? If anything, the per capita incomes are on average widening between the rich and poor countries. The answer, the authors say, lies in the difference between “extensive” and “intensive” margins. Extensive margins are how long a country takes to adopt a technology while intensive margins are the extent to which a technology is adopted by the country as a whole. Stated otherwise, while Kenya may adopt the Internet technology faster than it did the car technology, it’s not necessarily reaching the majority of Kenyans at that same rate.

In further analysis of the intensive margin of technology adoption, the authors make three observations that are relevant to the study a) different technologies have different intra-country adoption levels b) Even as the difference shrinks, the in-country variation has not and c) the in-country variation in adoption has more impact on income per capita compared to cross-country adoption. The model helps us compare quantitatively the spread of technology across the world and guides the study of in-country adoption.

We proceed to test two main hypotheses. One, that digital divide diminishes with increased adoption of non-technical factors affecting ownership and use of the Internet technology. This hypothesis is tested by comparing the levels of adoption and use of the Internet in four counties with varying levels of income, digital skills and urbanization. Two, an increase in access to the Internet increases an individual’s participation in public affairs. This hypothesis is tested by comparing the frequency of participation in governance affairs across different counties over time.


Information Controls and Political Processes: Elections, Information Controls and Counter Controls

Increasing research evidence has demonstrated that political events such as elections, protests, and sensitive anniversaries can influence when and how information controls are enacted and the potential impact of these controls. Good examples in Africa are the 2016 elections in Uganda, Chad and Congo Brazzaville where an increase in information controls were reported.

Using a “mixed methods” in researching forms of information controls, and especially Internet shutdowns, this project is a joint effort with OONI, a technical network measurement organization. This, it is hoped, will develop a deeper understanding of why governments control information around elections and what impact this has on individual rights, economy and national stability.

Leave a Reply

Your email address will not be published. Required fields are marked *