IEEE Technology and Society Magazine - March 2021 - 39

UNDP and promoted by the Egyptian Ministry of
Agriculture, were twofold: to develop two ESs aimed
at increasing yield and quality of cucumber and citrus production, and to build the Central Laboratory
for Agricultural Expert Systems [46]. The objective
of the Nile basin decision support system project
[47] was to support regional and transnational decision-making for the management of the Nile basin
resources. Finally, the aim of the project presented
in [48] was to confirm the number, time, and place
of spontaneous refugee returns to the Casamance
region in Senegal using call detail records made
available in the context of Orange Telecom's Data
for Development challenge.
From our review of relevant projects and from
the success factors for AI4Eq-oriented A/IS, and for
ICT4D in general, identified in the literature, in the
following sections, we present, first, the issues and,
secondly, the methodological and technical tools
that we consider of particular relevance for AI4Eq.
In doing so, we also take into account the principles
of HRBA and the general principles of good practice
in development cooperation projects. Our proposal
is a commitment to the essence of the SDGs-recognizing that development and sustainability may
be in opposition and need to be balanced-from
a multidisciplinary and integrative, as opposed to a
technocratic, viewpoint.

Some issues of particular relevance for AI4Eq
Below we discuss issues we consider particularly
relevant for AI4EQ, which dictate the methodological and technical tools needed.
Alignment with the SDGs that are primary in
each case
A/IS should contribute to the fulfillment of
those basic human rights and the satisfaction of
those unmet basic needs that are most affected in
each case.
Use of the HRBA
Ethical AI should be respectful of fundamental human rights and of the particular values of
the culture in which it is deployed, and should
take into account the idiosyncrasy of each context. This requires an inclusive, participatory and
culture-aware approach to project development.
Extensive stakeholder consultation is needed,
paying attention to the representativeness of the

March 2021

participants and, in particular, attempting to ensure
the presence of habitually marginalized communities diverse in gender, economics, culture, and
value. In data science projects, if stakeholders provide not only their data but also their opinion, participating, where possible, in data processing and
interpretation, it would help to avoid inherent bias
in the data and would favor a balance of power.
Stakeholders who feel that their views, values, and
needs are taken into consideration in technological progress are more likely to have a favorable attitude toward A/IS. HRBA also underlines the need
for accountability, in which impact measurement
plays a significant role.
Impact measurement
This should be carried out with a wide but integrative perspective, taking into account multiple
dimensions-sociopolitical, geographical, climatological, environmental, etc.-and paying attention
to social costs, the impact on the workplace, and
consideration of the values of the culture in which
the technology is to be deployed.2 Indicators related
to specific development priorities in LMICs and
associated with compliance with SDGs are of prime
interest. As stated in [8], to date, large-scale impact
assessments of A/IS have not been carried out and,
in fact, no well-established monitoring tools and
assessment methodologies are currently available
for this purpose.
Appropriateness
In addition to worrying about short-term productivity, the following aspects also need to be
addressed: acceptance, continuity, maintainability,
and long-term viability. This will involve knowledge
transfer, the establishment of the necessary infrastructures and could also involve the promotion of
local research.
Promotion of autonomy/empowerment
A/IS should contribute to self-sufficiency and to
the empowerment of small communities and the
small-scale economy. Care needs to be taken, in this
regard, with any use of energy-intensive big-databased solutions.

2
At the same time, being conscious of the limitations of measurement expressed
in phrases such as " teaching to exams " and " anything that can be measured and
rewarded will be gamed " [49].

39
IEEE Technology and Society Magazine - March 2021

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