IEEE Technology and Society Magazine - March 2021 - 27

individual or community harm results, a mechanism
exists to sanction those responsible and provide a remedy to the persons affected [8]. At present, accountability in ethical guidelines for AI is too often limited to
transparency: documenting the development process
or publishing independent audits. While transparency
is necessary, it is not sufficient to ensure accountable
AI; HRBA demands accountability for outcomes that
prove harmful and requires a mechanism for remedy
to population that may have been negatively affected,
including the harm that denies them equitable access
to AI benefits.3
While the human rights framework should be
applied in its entirety to AI-DDD, this commentary
continues with a focus on practical application of
the principle of equality and nondiscrimination,
such that populations the world over can enjoy
equal benefit to the AI systems' innovations and
equal protection from their potential harms.

Promoting AI4Eq: Equal access and
sustainable development
Fulfilling AI's potential for good, by catalyzing a
more equal world, poses particular challenges when
considering the context of AI-DDD for people living
in LMIC. In recognition of these challenges, IEEE's
Ethically Aligned Design (EAD) [10] project (whose
purpose is to provide recommendations leading to
AI development that benefits humanity), established
the Sustainable Development Committee.4 The committee (whose multidisciplinary members included
academics, lawyers, robotics engineers, businessmen and women, and international development
experts) was concerned that there be " equal availability " of access to AI's benefits that would, to use
the SDG's driving principle, " leave no-one behind. " It
recognized that while:
A/IS [autonomous and intelligent systems] are
among the technologies that can play an important role in the solution of the deep social problems plaguing our global civilization, contributing
to the transformation of society away from an
unsustainable, unequal socioeconomic system
toward one that realizes the vision of universal
human dignity, peace, and prosperity [10, p.142],
3
In a forthcoming article (currently under review for publication in Global Policy)
this definition of a human rights framework is applied to a total of 15 AI ethics guidelines produced by industry, government and civil society. " See [9].
4
The author of this Commentary was the Chair of the EAD's Sustainable Development Committee.

March 2021

this social-justice outcome would not happen without a concerted focus on increasing equal access to
AI. As things stand today, the vast majority of AI-DDD
takes place in HIC within a homogenous, educated
subsector of society. A recent article in the MIT
Technology Review lamented " clear lack of regional
diversity in many AI advisory boards, expert panels,
and councils, " which reflected an AI world where
only the " languages, ideas, theories, and challenges
from a handful of regions-primarily North America,
Western Europe, and East Asia (were considered)...
(this lack of diversity is seen in) the current concentration of AI research (pdf): 86% of articles published
at AI conferences in 2018 were attributed to authors
in East Asia, North America, or Europe. And fewer
than 10% of references listed in AI articles published
in these regions are to articles from another region.
Patents are also highly concentrated: 51% of AI
patents published in 2018 were attributed to North
America " [11].
The committee, in acknowledgment of this unequal and undesirable situation, elaborated a series
of issues and recommendations in the EAD's " A/IS
for Sustainable Development " chapter, devoting two
of the chapter's five sections to AI4Eq: " A/IS in Service to Sustainable Development to All " and " Equal
Availability " [10, pp. 140-168]. The paragraphs
which follow are adapted from those sections.
The concentration of AI-DDD in HIC leaves LMIC
behind and undermines AI's potential to provide
them equal benefit, and thus serve as a motor for
reducing global inequality. EAD's Sustainable Development Committee identified several factors [10,
pp. 141, 143, and 148] currently mitigating against
equal benefit:
*

The concentration of AI creator capacity in a few
countries, companies, and citizens (from wealthier, more educated enclaves).
* Lack of the human capital and knowledge
required to adapt HIC-developed technologies
to resolving problems in the LMIC context, or to
develop local technological solutions to these
problems.
* Difficulty retaining A/IS capacity in LMIC due to
globally uncompetitive salaries.
* Inadequate or nonexistent IT infrastructure
needed to support AI.
* Lack of internet access for up to 90% of the population in certain countries.

https://hai.stanford.edu/sites/default/files/ai_index_2019_report.pdf

IEEE Technology and Society Magazine - March 2021

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