IEEE Technology and Society Magazine - March 2021 - 34

AI for a Fair, Just, and Equitable World

which all organizations and individuals in our society
must be involved. Moreover, unlike previous UN initiatives which were, in general, aimed at LICs with the
rest of the world being assigned a supporting role, the
approach of the 2030 Agenda to development problems is universal in nature. This is a recognition that
the development paths followed by the HIC cannot
be held up as examples to follow, given the resulting inequality and unsustainability, particularly relevant being their contribution to creating a climate
emergency. This process of transformation necessarily gives a central role to innovation and, therefore,
to technological innovation. AI can play a decisive
role in the technological innovation that will enable
the necessary transformation toward an inclusive
and sustainable future, consistent with the United
Nations Development Programme (UNDP) concept
of " human development " [30], a more equitable concept of development which refers to human freedoms
and capacities, not to increasing GDP.
In the following sections, we catalog the various
reasons for which A/IS may negatively affect the
SDGs related to equity both within countries and
between different countries.

Inappropriateness for the socioeconomic
conditions
The principal socioeconomic reasons that A/IS
may contribute to increasing inequality are the unequal distribution of computational resources, infrastructure, and suitably trained human resources. For
example, in a review of intelligent tutoring systems
focusing on barriers to their use in LMICs, Nye [31]
highlights a widespread lack of adequacy to the
deployment context. He also introduces a note of
skepticism regarding LMICs leapfrogging straight to
the mobile era: though mobile-based applications
are becoming more prevalent in LMICs, in general,
this is mainly in privileged sectors; meanwhile, networks and devices are generally of low quality, and
mobile data and Internet access remain costly.
References [11], [22], and [23] draw attention
to the fact that the use of big data in LMICs suffers
from the classic problems of poor infrastructure and
lack of human capital. Regarding infrastructure, the
first problem is the lack of available or accessible
data. For example, the low number of meteorological stations for climate data collection and a lack of
digitization of the data in question is a hindrance to
using big data technology in agriculture and WRM,

34

and to supporting climate-change response. Regarding human capital, in LMICs there is a shortage of
expertise in the collection, preparation, and analysis
of data.

Imbalance of power in the market
A/IS may give large corporations a competitive
advantage over small producers, for example, as
stated in [21], big data techniques may require powerful energy and computational infrastructure that is
beyond the reach of small producers.
Similarly, as stated in [22], which discusses the
risks involved in using big data in LMICs, the mere
promotion of big data techniques in areas such
as agriculture is likely to favor those with the economic means to put these techniques into practice.
Enhancing information transparency in agriculture
could also favor large-scale enterprises even to the
point of facilitating predatory practices. Finally,
since futures markets are increasingly based on bigdata analysis, as stated in [21], enhancing information transparency facilitates commodity trading and
could therefore also have a negative impact on small
farmers by increasing price volatility or by accentuating price variability (e.g., due to investors taking
short positions).

Adverse effects on employment
It is generally acknowledged that the deployment
of A/IS will lead to lower salaries for unskilled labor
and to difficulty in accessing the labor market for the
most disadvantaged sectors of the population, this
topic is extensively treated in the literature, for example [7]. In a liberalized market, automation is always
to the advantage of capital and to the disadvantage
of labor, this effect being visible, for example, in the
new tech giants having relatively low numbers of
personnel for their size.

Adverse effects on human rights and
democracy
The recently released report to the UN General
Assembly by the special rapporteur on extreme poverty and human rights about the digital welfare state
[32] and different studies found in academic literature such as [32], [9], [18], and [22] focus attention
on the risk of coercive, surveillance, discriminatory
A/IS technologies that not only do not contribute to
reducing inequalities but contribute to perpetuating them. The report warns of the " riskĀ of stumbling

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IEEE Technology and Society Magazine - March 2021

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