IEEE Technology and Society Magazine - June 2021 - 58

Feature
of AI developers and corporations: As mentioned, the
stated objective of building trust among citizens and
consumers appears to be more a corporate objective
than a societal objective. Trust is the consequence from
building good, safe applications that behave correctly,
but should not be an objective itself. The objective
should be ensuring the development of applications
that reinforce the full implementation of human rights.
Some other rights-based principles are proposed
and should be borne in mind when thinking about
AI algorithms.
Responsibility/accountability
Make available externally visible avenues of
redress for adverse individual or societal effects of
an algorithmic decision system and designate an
internal role for the person who is responsible for the
timely remedy of such issues.
Explainability
Ensure that algorithmic decisions as well as any
data driving those decisions can be explained to end
users and other stakeholders in nontechnical terms.
Accuracy
Identify, log, and articulate sources of error and
uncertainty throughout the algorithm and its data
sources so that expected and worst-case implications
can be understood and inform mitigation procedures.
Auditability
Enable interested third parties to probe, understand,
and review the behavior of the algorithm
through disclosure of information that enables monitoring,
checking, or criticism, including through
provision of detailed documentation, technically
suitable application programming interfaces (APIs),
and permissive terms of use. As recently established
by the Consultative Committee of the Convention for
the protection of individuals with regard to automatic
processing of personal data (January 25, 2019), in its
Guidelines on Artificial Intelligence and Data Protection,
" without prejudice to confidentiality safeguarded
by law, public procurement procedures should
impose on AI developers, manufacturers, and service
providers specific duties of transparency, prior assessment
of the impact of data processing on human
rights and fundamental freedoms, and vigilance on
the potential adverse effects and consequences of AI
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applications (algorithm vigilance). " This vigilance is
the adoption of accountability, awareness, and risk
management practices related to potential adverse
effects and consequences throughout the entire life
cycle of these applications.
Fairness
Ensure that algorithmic decisions do not create
discriminatory or unjust impacts when comparing
across different demographics (e.g., race, sex, etc.).
A definition of fairness is used in the Declaration on
Ethics and Data Protection in Artificial Intelligence
(40th International Conference of Data Protection
and Privacy Commissioners, 2018):
* Considering individuals' reasonable expectations
by ensuring that the use of AI systems remains
consistent with their original purposes and that
the data are used in a way that is not incompatible
with the original purpose of their collection.
* Taking into consideration not only the impact that
the use of AI may have on the individual, but also the
collective impact on groups and on society at large.
* Ensuring that AI systems are developed in a way
that facilitates human development and does not
obstruct or endanger it, thus recognizing the need
for delineation and boundaries on certain uses.
Contestability
When an AI system significantly impacts a person,
community, group, or environment, there should be
a timely process to allow people to challenge the use
or output of the AI system.
Privacy
The right to privacy means the right to control
own's personal data and avoid uses that can harm us.
Impact of human experimentation
There are big concerns around that, obviously. Any
experiments concerning human being (e.g., brain experimentation)
should consider the principle of human
dignity, one of the basic notions used for the protection
from the harm caused to humans. Human dignity should
be respected while developing new technologies.
We have left some of the terms above purposefully
underspecified to allow these principles to be broadly
applicable. Applying these principles well should
include understanding them within a specific context.
It is important that these issues be revisited and
IEEE Technology and Society Magazine
IEEE Technology and Society Magazine - June 2021

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