Governments should fully understand the scope and reach of the various Digital Government (DG) institutional functions, described in my previous post, and their proper sequencing before they embark on comprehensive digital transformation processes. The policy units’ actual institutional location leading DG processes should be the result of the analysis of the various functions, not the starting point. Indeed, countries have deployed a wide variety of institutional arrangements while designing and implementing DG. A one size fits all approach is thus out of the question. Similarly, copying and pasting institutional design from DG lead countries or nations within similar development stages will tend to fail. Context is thus essential.
Equally important here is the distinction between policy
Institutions matter, more so for the development and implementation of Digital Government (DG), whose core target is public institutions’ transformation. On the one hand, public institutions should have an array of capacities to ensure public investments in digital technologies are effectively managed from beginning to end. In many low-income countries, such capabilities are exiguous or conspicuously absent. On the other, digital technologies are a means to foster public entities’ responsiveness and effectiveness, thus increasing their overall capacity to deliver established legal mandates. Juggling these two seemingly contradictory propositions in sustained fashion is one of the core challenges governments face when designing and deploying DG, especially in the Global South, where state capacity
Since the early 1980s, Governments have taken a bad rap. Menacing fingerpointing from most quarters ended up on a consensus that loudly declared them personas non-gratas. The 2009 Global Financial Crisis started to turn the tide. At the time, governments once again came to the rescue of capitalism, unveiling gigantic financial packages to prevent critical financial institutions’ failure. Once the recovery started a few years later, Governments took the back seat once more, backed by universal austerity policies that, in hindsight, did more damage than anything else – especially in terms of income and wealth inequality.
The ongoing pandemic has once again demanded the strong intervention of Governments. However, this time around, the crisis is impacting most, if not all, sectors, in addition
Running on the coattails of electronic commerce, Digital Government (DG) first saw the light of day over 20 years. Initially christen as electronic government or e-government, it has since experienced multiple name changes, ranging from e-governance and transformational government to intelligent and smart government. Nowadays, the field seems to be enjoying its run as DG. Regardless of its actual denomination, DG’s indisputable mandate is to transform public institutions via the strategic deployment of digital technologies – the emphasis placed on transformation, not technologies.Such digital transformation must modernize the public sector, thereby leading to increased overall institutional capacity, enhanced provision of public goods, services, and information, and the promotion
Initially touted as revolutionary and progressive in the 1990s, the lightening evolution of digital technologies, running on the coattails of continuous innovation, has been accompanied by the rise of both extreme socio-economic inequalities and loud and widespread populism, nationalism and overt racism. Many countries are undergoing de-democratization processes undergirded by very resilient neoliberalism, while claim-making by conservative political actors has gained considerable ground in the always contentious political arena.
The unexpected and devastating pandemic triggered by the accelerated spread of the SARS-COV-2 virus has put into evidence the real constraints of a now aging and highly monopolistic digital sector. While information and communication tools and platforms are indeed
For the last 30 years, relentless technological innovation has seemingly conquered most, if not all, corners of the world. While in its early stages, the focus was on infrastructure and social networks, the latest phase has set its eyes on core productive and financial processes that will undoubtedly have profound socio-economic and environmental impact across the board. Rapidly adapting to the emerging global context is the clarion call for most countries if they want to remain relevant and competitive at the global level.
Many developing countries find themselves in a unique situation. For starters, most innovations and technologies hold a foreign passport and thus need to first travel and then be adopted and adapted to the national context. Having local capacities –
The current long wave of digital innovation has finally broken the last bastion of socio-economic resistance. While early advances transformed communications infrastructure and enhanced consumer interactions, the resurgence of Artificial Intelligence (AI) and all its relatives, alongside new technologies such as blockchains, have rattled seemingly immovable sectors of the economy thus opening the door for the global disruption of productive and financial processes. Not surprisingly, observers and pundits have quickly agreed on a label for such disruption, the 4th Industrial Revolution (4IR) that could have a profound impact on countries, institutions and people. No stone will remain untouched, such is the warning.
AI in the Global South
Countries in the Global South find themselves in a peculiar
A recent paper published under the auspices of Google Health makes a case for using deep learning algorithms to improve breast cancer detection. The research has been positively received by most and widely publicized as yet another victory of smart machines over weak, dumber humans. Only a few have been critical for good reasons. In this post, I will explore the methodology used in the research to highlight other critical issues. But before I take the dive, let me first set the scene.
Like education or justice, health is an information-rich sector, thus prone to rapid (not just digital) technology innovation and overall digitization. Unlike its peers, most if not all health-related services use a gamut of technologies, from simple thermometers and stethoscopes to noisy, giant
My paper on blockchains for the public sector in developing countries has been published by Frontiers, one of the leading open-access and community-driven academic publishers.
The paper develops an analytical framework that combines sustainable development, state capacity and digital technologies. In principle, the framework can be used to explore the adoption of technologies and innovation in the public sector and is thus not limited to blockchains.
As the central focus of my research was governments, exploring ways to increase state capacity by building strong and resilient democratic institutions and deploying new technologies was on the table. Like Artificial Intelligence and Machine Learning, blockchain is a technology that works best at the application layer. That means that the
As Artificial Intelligence (AI) seemingly continues to permeate all interstices of society, measuring its undaunted progress in the age of data is more than a priority. In a previous post, I share some insights on the Global AI Readiness Index that covered almost all UN member states. The new Global AI Index (GAII), created by Tortoise media with the support of experts from government, academia and the business sector, is geographically less ambitious but aims at a more sophisticated target. It covers 54 countries and its core goal is not readiness but rather capacity. The company informs us that the index is a response to demands from some government on the subject. However, the report is intended not only for governments but also for businesses and communities.
In spite of obvious differences,