Can Data Become Part of a Development Strategy?

By Yasodara Córdova, Padmashree Gehl Sampath, and Lorrayne Porciuncula

That is one of the burning questions for policymakers, regulators and academics today, as we seek to hone in on whether and how the benefits of big data and Artificial Intelligence can be equitably leveraged for developing countries. The current state of deliberations, however, is yet distant from being grounded in a reality that works for all. Although many governance frameworks and data architectures abound, there is not a single one that fits the needs of digital transformation in developing countries. Even when we take into account the fact that developing countries are quite heterogeneous, — following differentiated economic growth and development pathways — some of the underlying issues related to technological monopolies, privacy regulations, data infrastructures, and internet use and architecture are common for all. This calls for establishing common ground.

Tackling this question in the context of the digital economy and breaking this down into a strategy for digital transformation requires the understanding that there are different kinds of typologies and governance frameworks related to big data. One needs to begin by focusing on how the principles of fairness and sustainability can be integrated into these typologies to advance the growth and well-being of all countries and people. There is also the critical need to distinguish between personal and non-personal data, which is often not discussed in issues of design.

The government and civil society have an important role to play in creating new and open data ecosystems that make such data openly available for use by local businesses to build, forecast and innovate. Policy frameworks in developing countries, therefore, should push for data access and the use and re-use of data, avoiding silos and predatory models that facilitate data extraction. In such a digital strategy, data should become an enabler of new models of cooperative growth.

Recognizing the importance of these issues for a balanced debate, we are organizing a second workshop on these issues, hosted by the Digital Initiative at the Harvard Kennedy School, Harvard University on the 23rd of May, 2019. The debate follows the first workshop organized by the initiative in October 2018, called “Big Data, Meager Returns?”.

The meeting will trail around a number of issues that should form part of a developmental strategy for digital transformation, namely: data typologies, the creation of data markets that facilitate the birth of local firms and businesses, guidelines for data regulation and governance frameworks that promote local rights and participation in the data economy at developing countries. The discussions will focus on exploring the particular positive effects of digital transformation in developing countries and the role of public policy in harnessing it.

The Workshop will have five sessions: (a) Data Typologies; b) Collaborative Data Models for Developing Countries; c) Enabling Comprehensive Data Policy for Development, d) Global Agreements, Local Interests, and e) Preserving Developmental Space.

Workshop registration is open. To register, use this link. For background, consult our first workshop proceedings titled ‘Big Data, Meager Returns?’, hosted by the Digital Kennedy School in October 2019, in collaboration with the Berkman Klein Center at Harvard.