IEEE Technology and Society Magazine - March 2021 - 48

AI for a Fair, Just, and Equitable World

tools, in general. This research should involve multidisciplinary teams that understand the technical,
human, and social implications of AI algorithms and
platforms [26].
Finally, ensuring that AI benefits society as a
whole requires overcoming ethnocentric and androcentric approaches, opening dialogue mechanisms
among different social actors, involving civil society
in the discussions, and obligating a concomitant
investment in AI education and literacy.
We need to go beyond an AI framework that is
restrictive, reductionist and self-regulated, and work
toward a future in which not only citizens are protected against the risks of AI, but also AI empowers
and makes a decisive contribution to bringing peace,
prosperity, and justice as well as to enhancing social,
material, and spiritual well-being.

Artificial intelligence and the
Agenda 2030
We believe that the position expressed in the
2020 European Commission (EC) White Paper on AI
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 also an under-representation of the importance of human rights when analyzing AI impacts. Public policies on AI appear to be
exclusively designed to improve the competitiveness of European companies in AI when the focus
should be more on how AI helps to improve people's
living conditions, contributes to the SDGs, and to the
fight against climate change and its consequences.
In terms of specific content on the SDGs, the document makes only a timid mention of environmental
sustainability, which did not figure as a significant
issue in the accompanying public consultation
questionnaire either. The potential and compelling
purpose of technology to advance issues of rights,
sustainability of communities, common welfare, and
social and gender equality is ignored. In addition,
the current crisis has highlighted the need to use AI
to improve the health response at national and European levels, monitor progress of the infection, and
mitigate our vulnerability.
The section of the document titled " Focusing
the Efforts of the Research and Innovation Community " fails to mention promoting lines of research
that support the SDGs, including the most pressing
ones for Europe (fair and equitable data, sustainable

48

economic development, risk prevention, and disaster management). This omission occurs in spite of
the fact that the EU has also stated its commitment
to the SDGs in the objectives of Horizon Europe
and in the EU Framework Programme for Research
and Innovation 2021-2027. The UN recognizes that
the so-called digital revolution is a key enabler of
sustainable development. It is also pertinent to
observe that AI research and development in the
field of SDGs is biased toward issues relevant to the
nations where most researchers and practitioners
live. There are very few AI technologies applied in
less-developed countries where there is not a strong
AI research base.
We believe it would advance the commitment
to the 2030 Agenda if AI were developed with the
philosophy of responsible research and innovation
(RRI), which aims for a new model of research governance that reduces the gap between the scientific community and society, encouraging different
stakeholders (educational community, scientific,
business, industry, civil society organizations, and
politics) to work together throughout the process of
research and innovation. The idea is that cooperation between different (relatively autonomous but
highly interdependent) actors will make it possible
to align the research process and its results with society's values, needs, and expectations. Although the
term RRI was coined a decade ago, it has recently
gained prominence due to its inclusion in the Science with and for Society Programme promoted by
the EC within the framework of the Horizon 2020
research strategy.
The RRI is a radical move toward openness and
socialization of technoscientific processes that
are embodied in four principles of governance:
1) anticipation; 2) reflexivity; 3) deliberation; and
4) 
accountability. The public engagement in
research and innovation that RRI entails should lead
to more ethical solutions to difficult problems, facilitating public acceptance and trust.
Another aspect that is missing from the document
concerns the social and ethical impacts of AI. As AI
permeates into more and more areas of society, it
should increasingly be able to measure its own
impact: AI should be self-assessing. Clear metrics are
needed in this regard to avoid bias and undesired
indirect impacts. Social and ethical impact assessment needs dedicated research and common tools
(ethical and technological), without which impact

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

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