IEEE Technology and Society Magazine - March 2021 - 37

Figure 1. Establishing the AI4Eq field.

With the present article, we seek to encourage
the academic community to get involved in AI4Eq
educational programs and in inter- and multidisciplinary research in AI4Eq that involves, in particular, civil society. We also argue that an HRBA and
development-oriented approach greatly increases
the chances of having a positive impact on the satisfaction of the SDGs.
In our opinion, establishing the AI4Eq field
should involve the following phases: revising the
state of the art, identifying the issues of particular
relevance for AI4Eq, and finally identifying methodological and technological tools that are of particular interest for AI4Eq as well as disseminating AI4Eq
examples of good practice (see Figure 1). In the next
section, we present the first exploration of this way
forward. Before doing so, in the rest of this section,
we discuss the relevance of multilevel and multiactor cooperation.

AI4Eq through multilevel action and multiactor
alliances
The SDGs are focused on equity, inclusiveness, and sustainability so should intrinsically be
addressed from the perspective of cooperation for
the common good rather than from a perspective
of competitiveness. The SDGs promote multilevel
action and multiactor alliances. The UN Agenda
2030 calls on institutions, governments, public,
and private sectors, NGOs and other civil society

March 2021

organizations, and universities to commit to the
development and viability of the SDGs, that is, to
participate together, in the design and application
of collective solutions to collective problems. This is
made explicit in goal 17, " PARTNERSHIPS: Revitalize
the global partnership for sustainable development. "
The way to AI4EQ should reflect this spirit of universality, of collective transformational effort, avoiding the global north-south dichotomy that has often
characterized cooperation for development projects. Collaboration is enriched by different actors
who provide different skills, sensitivities, experiences, and perspectives but this will require defining
methodologies and instruments that articulate this
collaboration.
Private sector involvement
This issue has been brought into focus by projects involving the use of data science in humanitarian emergencies, see [22]. Much of the valuable
data that is relevant in the development context
is owned by the private sector, for example, digital-cash transaction data and location data owned
by mobile-phone operators. Data such as this and
social media data maybe a useful source for extracting indicators of human well-being. The concept of
" data philanthropy " has been coined to describe the
donation of data for a good cause by private sector
actors [22]. Corporate social responsibility needs to
accompany private sector involvement. On the other

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IEEE Technology and Society Magazine - March 2021

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