IEEE Technology and Society Magazine - March 2021 - 41

Data science guidelines
In the field of data science, guidelines exist for
taking into account the risks at each stage of the
development cycle (requirements engineering,
design, curing or preprocessing of data, application of learning algorithms, implementation,
testing, deployment, evaluation, monitoring, and
maintenance). The study of these risks should be
an integral part of the data science curricula. The
use of big data for humanitarian purposes presents
particular challenges, mainly concerning privacy,
that have been addressed using different tools.
Thus, Pastor-Escuredo et al. [48], reporting on the
use of big data in humanitarian emergencies, point
to the importance of using protocols involving risk
assessment and mitigation, such as the UNHCRs
data privacy policy or the UNGP-UNDP guide to
data innovation for development, to guarantee
privacy. Technological and methodological tools
were used to carry out aggregation, anonymizing,
and filtering of data to minimize the possibility of
reidentification of individuals.
Explicability tools
The need for A/IS to be able to provide an explanation for their decisions is particularly acute in the
AI4Eq context. However, there are numerous difficulties and challenges in this area, to name a few:
*	 deciding exactly what an explanation is, since
this may be a little obscure in the case of machine
learning;
*	 defining a notion of quality for explanations,
especially to decide when an explanation is considered to be of sufficient quality;
*	 ensuring that explanations are understandable to
their audience, sometimes the general public.
Low-cost A/IS
This refers to solutions such as lightweight mobile
applications or free or open source software (FOSS).
Also relevant in this context is the " Open AI " paradigm (see [50]), which refers not only to FOSS but
also to the application of FOSS principles to algorithms, scientific knowledge, or other A/IS artifacts.
Liberalizing the applications and following free
software principles could contribute to making the
benefits of A/IS more accessible. However, while on
the one hand, the availability of FOSS source code
facilitates checking compliance of developed A/IS

March 2021

software with ethical standards, on the other hand,
the FOSS development and distribution process
makes following ethical guidelines and standards in
the A/IS software development process difficult to
impose and hinders the certification of compliance
of the development process with such guidelines
and standards.
Context aware systems
Not all ethical principles are equally important in
all contexts and cultures. Adaptation to the culture
where systems are deployed (see [51] is an aspect
that should be incorporated in R&D methodologies
as a cross-cutting functional requirement of these
systems. User-centered design methodologies would
benefit from tools for the bidding of social values
and, according to [8], current tools remain at a very
abstract level and are not instantiated in practical
guidelines.
Other paradigms and tools of interest
Finally, other tools and fields of research, such as
value- sensitive design [52], privacy-by-design [53],
and ethics-by design [54], are being developed for
ethical A/IS in general and would be very relevant
to AI4Eq. We believe it would also be of interest to
explore similar approaches such as impact measurement by design, equity-by-design, rule-of-law by
design, democracy-by-design [55], etc.
Technological innovation demands a specific approach to ensure that it contributes to the
SDGs, in particular, avoiding a purely economics-based approach that would convert sustainable and equitable development into an oxymoron.
The ICT4D community has, until recently, shown
insufficient interest in A/IS, while the A/IS research
community has, on the whole, shown a lack of
awareness of any need to integrate development
studies and HRBA perspective. We conclude that
more R&D in the potential of AI to contribute to
the SDGs, particularly for vulnerable and marginalized populations, is urgently needed, via the
consolidation of a field that benefits from the
large body of accumulated knowledge and experience in development studies, and ICT4D, and
takes into account the full range of specificities of
A/IS, including those of an ethical, psychological,
or philosophical nature. A development studies
perspective and the measuring of impact in terms

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IEEE Technology and Society Magazine - March 2021

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