Small Data, Big Data and the Ethical Challenges for the Internally Unequal Developing World

The global North observe with attention the advancements and promises related to the use of big volumes of data and their availability for the increasingly refined elements of artificial intelligence. Many agents see with enthusiasm the potential of generating those capabilities in developing countries, as innovation could help to answer old and new problems, give a chance to “catch up”.

Nevertheless, the success of these kind of elements in developing countries needs, before anything else, to deal with clear deficiencies and already existent challenges related to less complex elements (small data). It is imperative to generate public discussion about the current conditions to generate and manage data with a challenging level of volume, velocity and variety (big data) and, more importantly, the priority given to it versus solving more traditional problems.

To be truly successful, that public discussion will need to address topics that evaluate the possibilities and limits of the adoption and promotion of new information practices and technologies in dialogue with preexisting internal inequalities.

Among others, the discussion would need to include topics concerning: 1) how legitimate is to bet on a strategy based on the formation and impulse of an intellectual elite, 2) how the differences in resources available for different agents could generate a difference in how useful the adoption of these technologies will be (will simply the rich get richer?), 3) how the adoption of these technologies could exacerbate inequality between sub-national territories as a consequence of the difference of access and skilled labor availability, etc.

This discussion about these new technological elements will need not only data-aware public managers and authorities, but also awareness about the specific ethical challenges and dilemmas derived of its adoption in developing countries.