IEEE Technology and Society Magazine - March 2021 - 56

AI for a Fair, Just, and Equitable World

devices like Siri and Alexa, we are constantly interacting with AI-based technologies. This disruptive
tendency obliges citizens to adapt themselves to the
prevailing ever-changing technological environment. It
compels citizens, without apparent pressure, to deliver
their data without any control to stay informed.
Governments around the world are devoting significant efforts and resources to support national
research and development to develop AI technological sovereignty. At the same time, governments and
citizens have growing concerns about the misuse
and unintended consequences of AI-based systems
in many aspects of daily life.
Despite the tremendous investment in AI, and the
successful examples of AI-in particular, ML-capabilities, we are not making sufficient progress when it
comes to solving some of our planet's most fundamental challenges or in critical areas for the citizens such as
health, education, or social security. It seems increasingly clear that governments ought to play an essential
role in shaping the future and governance of AI. On the
other hand, the excess of information forces the society
to delegate decision-making to a machine that does so
by analyzing vast amounts of data and our preferences
too, in theory, to immediately satisfy our interests [8].
These decisions are accepted in most cases without
being properly evaluated and without exactly knowing the behavior of the algorithm that produces them.
What is paradoxical is the fact that governments have
a small role in the growth of those tools and are late in
trying to regulate them.

fAIr LAC alliance
The fAIr LAC alliance [9], [10] is made up of a
multidisciplinary group of Latin American experts from
different governments, academic institutions, private
companies, nongovernmental organizations, ethics
experts, innovation centers, and specialists from different areas of the Inter-American Development Bank.
The fAIr LAC team is advancing in the study of use
cases of AI-based systems in critical areas for the citizens such as health, education, or social security. In
those cases, the local or national governments are key
actors and the aim is to extract good practices that can
be exported to other cases in the region.
The fAIr LAC is a regional initiative, but it will have
local hubs. There are three in the list. The first hub will
be implemented with the state of Jalisco in Mexico
and local leaders in AI applications and policy-making (see the " fAIr LAC Jalisco " section). The other two
pilots will be installed in Costa Rica and Uruguay.

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The work of the fAIr LAC initiative will focus on
three axes [9]:
*	 develop standards and tools that guide responsible and reliable use of AI in Latin America and
the Caribbean through certifications, algorithmic
audits, and specific guides.
*	 encourage responsible adoption through pilots
and shaping regional hubs to promote awareness
of the ethical risks of using AI in social services
and ways to mitigate these risks.
*	 lead a dialogue around the responsible use of
this technology-focused on citizens and from the
perspective of diversity and inclusion, through the
promotion of a diverse ecosystem with networks
of experts, discussion tables, and conferences and
the formation of an observatory of use cases.
fAIr aims are contributing to efficient public management, using the opportunities that arise from the
AI-based technologies for the public good, as well
as the linkages between governments and AI companies. Universities are part of all consortia.
fAIr strives to become a regional innovation hub
for responsible use of AI and improving LAC societies' trust in AI.

AI digital transformation in public
services
AI-based technologies using the available data
can solve problems from detecting epidemics to traffic jams and disaster relief, but countries are not yet
using this data to its full potential. As mentioned in
the introduction, public administrations have struggled in this digital transformation process, introducing AI and data analytics to improve their public
services compared to private enterprises. There are
several reasons why this is the case. One significant
factor is a lack of understanding of the best approach
for implementing AI and analytics in administrations,
nor a clear vision of where there are low hanging
fruits on which to base a case for AI public services.
A manifestation of this lack of understanding is the
scarcity of published successful cases to replicate.
Case replication and adaptation are widespread in
local and regional administrations. This is how governments learn from each other and how the implementation of proposals gets improved. The lack of
exemplary cases forces blue sky exploration that
not many administrations are eager to engage with
because of the inherent risks.

IEEE Technology and Society Magazine
IEEE Technology and Society Magazine - March 2021

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