IEEE Technology and Society Magazine - March 2021 - 38

AI for a Fair, Just, and Equitable World

hand, the question of data ownership urgently needs
to be reassessed. The rapid development of big data
and the lack of understanding of its implications
among the general public has led to it being blithely
assumed that citizen-generated data belongs to the
companies that capture it, with little or no thought to
the consequences for the public interest.

practice of curricula competencies in a real context,
emphasizing on multidisciplinary, interpersonal,
civic, ethical, and metacognitive competencies,
fostering critical reflection on social transformation
possibilities, and rethinking professional goals from
a wider perspective.

Exploring the way forward for AI4Eq
Citizen science and community-centered
approaches
Citizen science [43], [44] is a governance
mechanism that allows society to capitalize on
the potential of A/IS, while ensuring respect for
human rights. The approach of citizen science
incorporates ethical values such as knowledge
sharing, reproducibility, participation, and representativeness in the development of A/IS. As
already mentioned about data science projects,
bias, both in the data and in the beliefs of the
professionals who manage it, can contribute to
accentuating inequalities. Citizen science is one
way of avoiding such bias. Additionally, citizen
science provides comprehensive training that
includes ethical awareness on how data science
projects affect vulnerable populations and, by so
doing, fosters confidence and motivation in A/IS.
Thus, at the same time as developing key competencies, participants acquire representation in
data science projects, thereby mitigating the risk
of the technology contributing to exacerbating
inequalities.
Education of future professionals through
AI4Eq transversal competencies and service
learning
A/IS education should avoid an overly technocratic and techno-optimistic approach and should
comprehensively address the impact of these technologies on equity and justice, raising awareness of
the ethical risks and sociopolitical implications that
their use entails.
Higher-education students at the undergraduate,
master's, and doctoral levels could act as providers
of A/IS services to disadvantaged communities in the
context of service learning (SL) projects [45]. The
ethical-civic education that is characteristic of the
SL paradigm constitutes an additional angle from
which to contribute to the objective of reversing
inequalities. The SL pedagogical paradigm enables
the application of knowledge and concepts, and

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In the next section, by way of illustration, we
present the first exploration of our view of the way
forward for AI4Eq, based on a small study of SDG-oriented multidisciplinary AI projects.

Brief overview of some A/IS applications in
sectors crucial to the SDGs
First and foremost, we believe it to be of primary importance to study the current panorama of
A/IS applications in sectors crucial to the SDGs.
The goal of this essential step is to document and
disseminate the lessons learned in developing and
deploying the most significant innovative applications, identifying strengths, weaknesses, and success factors.
Attention should be drawn to the idiosyncrasy of
each LMIC or particular context (cultural, climatic,
environmental,
organizational,
infrastructural,
socioeconomic, etc.) and the particular impact
AI4Eq-based innovation can have in each context.
Reflections on ethical problems arising from the use
of the technology, possible acceptance problems
in a specific context, impacts on culture, sustainability, gender digital divide, etc. would also be of
great value, especially if anchored in impact measurement using quantifiable metrics associated with
compliance with the SDGs.
In [20], we illustrated how some of the problems
discussed in the previous section can be addressed.
We performed a brief review of SDG-oriented
A/IS projects and studied three of the reviewed
projects more closely. In order for their impact to
be clear, we chose illustrative examples that are
relatively large-scale, without wishing to imply
that small-scale projects cannot be examples of
good practice. Though one of these projects could
be considered to be somewhat outdated, on the
other hand, this has enabled its impact to be thoroughly assessed.
The objectives of the ESs for improved crop
management project, funded by Food and Agriculture Organization (FAO) of the United Nations and

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IEEE Technology and Society Magazine - March 2021

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