IEEE Technology and Society Magazine - March 2021 - 21

case of AI. They present a first exploration of the way
forward for AI4Eq and discuss the relevance of multidisciplinary, multilevel, and multifactor alliances
that imply the private sector and civil society.
The rest of the special issue is then divided
(conceptually) into three parts: first, a set of organizational initiative addressing these issues; second,
a set of papers discussing real experience with
SDG-oriented AI applications; and third, a set of
papers describing tools (legislative, methodological, and technical) to support design, development,
and deployment of SDG-oriented AI, reflecting on
their strengths and weaknesses with an emphasis on
reducing inequalities.
In the first part, the reflection on initiatives
addressing the issue of AI4Eq is from three different
organizations: 1) the IEEE; 2) the European Commission; and 3) the Latin America and the Caribbean (LAC) alliance.
In an Opinion piece, Elizabeth D. Gibbons in
" Toward a More Equal World: The Human Rights
Approach to Extending the Benefits of Artificial
Intelligence, " emphasizes the dangers of AI driving
inequality, concentrating wealth, resources, and
decision-making power in the hands of a few countries, companies, or citizens. She stresses the need
for adopting a human rights framework in AI design,
development, and deployment and introduces the
work of the Sustainable Development Committee
of the IEEE's ethically aligned design project [8].
This committee (whose multidisciplinary members included academics, lawyers, robotics engineers, businessmen and women, and international
development experts) was concerned that there is
" equal availability " of access to AI's benefits that
would, to use the SDG's driving principle, " leave no
one behind. "
In " An Inclusive and Sustainable Artificial Intelligence Strategy for Europe Based on Human Rights, "
Fernández et al. summarize the reply that a group
of professionals and experts drafted in response to
the European Commission public consultation process on the " White Paper on Artificial Intelligence:
A European Approach Oriented to Excellence and
Trust " [21]. The authors highlight how the position
expressed in the white paper is technologically
reductionist, in contradiction with the European
commitment to the UN Agenda 2030, which is not
given its due centrality and, indeed, is hardly mentioned. There is an under-representation of the

March 2021

importance of human rights when analyzing AI
impacts, and notions of regulation, self-regulation,
and ethics are used in an imprecise and interchangeable way: proposed policies on AI appear to be
exclusively conceived to improve the competitiveness of European companies in AI.
In " To be fAIr or not to be: Using AI for the Good of
Citizens, " the authors present the fAIr LAC initiative,
which brings together a multidisciplinary group of
Latin American experts from different governments,
academic institutions, private companies, nongovernmental organizations, and innovation centers, as
well as ethics experts and specialists from different
areas of the Inter-American Development Bank. This
initiative seeks to harness the potential of AI to create more efficient, fair, and personalized social services for Latin America and the Caribbean. To this
end, it promotes standards, methodologies, and tools
that guarantee the development of a responsible,
human-centric, and trustworthy AI. The authors also
introduce a local hub of the fAIr initiative implemented in Jalisco, Mexico, and the experience
with a pilot AI-based application for the healthcare
public sector.
In the second part of the Special Issue, concerning the experience with SDG-oriented AI applications, there are three articles in which applications
in the fields of humanitarian emergency, mental
health, and social impact measurement, respectively, are discussed.
In an Opinion piece, " From Artificial Intelligence
Bias to Inequality in the Time of COVID-19, " Luengo
et al. illustrate the potential of AI to make a positive
impact in the fight against the COVID-19 pandemic,
while warning that AI applications, in practice, may
suffer from problems of bias and interpretability
which can result in systems that amplify health, economic, and social inequalities already exacerbated
by the pandemic. The examples of bias that increase
inequality range from systems for diagnosis and treatment trained with data from populations with very
narrow demographics, to epidemiological models
which cannot be adapted to different cultural and
social settings, to AI algorithms driving the spread
of mis- and disinformation targeting the attention of
particularly vulnerable groups.
The article " Persuasive Technology for Mental
Health: One Step Closer to (Mental Health Care)
Equality?, " Kolenik and Gams show how persuasive technology, which tries to influence people's

21
IEEE Technology and Society Magazine - March 2021

Table of Contents for the Digital Edition of IEEE Technology and Society Magazine - March 2021
