Verktækni - 2018, Qupperneq 23

List of guidelines
“Efforts towards ethical practices need
strong institutional backing to be effective,
and therefore, organizational commitment is
a requirement for addressing ethics in AI.“
1. Create spaces for discussion of the issues
around AI and ethics. These need to be facilitat-
ed and supported by both workplaces and civil
society organizations.
2. Invest into and develop tools that enable
ethical discussions, questions and decision
making throughout the design process and not
only at the beginning and the end.
3. Establish a set of internal standards and
checklists tackling ethical issues in AI devel-
opment such as ensuring meaningful human
control.
4. Support and facilitate internal reporting of
risk and violations, establishing rules for clear
action in response.
5. Establish internal training programs for staff
to deepen an understanding of ethics, and to
develop skills for ethical reflection, debate and
recognition of biases.
6. Pay special attention to potential biases
encoded in system development, training data
and model performance, especially those that
may affect the most vulnerable.
7. Develop ways for accepting organizational
responsibility for potential harm, for example,
by establishing ways to address the harm in-
flicted on others by AI systems that the orga-
nization has built.
8. Establish an internal ethical review process
that democratizes company decision-making
by involving more internal actors.
9. Work to increase transparency not only in
the decisions leading to design and develop-
ment of AI systems, but also in organizational
chains of responsibility.
10. In working towards transparency, main-
tain awareness that transparency has its own
ethical pitfalls and limits.
Policy Recommendations
“While engineers and their organizations will need to shoulder much of the growing
responsibilities in the design and implementation of AI systems, the relevant governing
bodies of the Nordic countries and at EU level must aknowledge their own responsibilities
and opportunities for action.“

1. There is a need to anchor discussions on the
political level and to advance the public un-
derstanding on AI. This could be accomplished
through the creation of a platform - a meeting
space that would engage decision makers,
business, academia, civil society and profession-
als including engineers to come up with stable
and transparent solutions for AI through joint
discussions.
2. Education for ethical considerations and
guidelines is often insufficient in the technical
disciplines and throughout work-life. This needs
to be addressed through changes in educational
goals and priorities for technical subjects as well
as through provision of relevant opportunities
for lifelong learning.
3. Development of an appeal process with
governmental oversight is crucial. Such a process
must enable individuals and organizations to
address the AI behaviour and decisions that they
find potentially harmful.
4. There is a need for shaping regulation and
legislation to govern issues related to AI that
formalises relevant responsibility and defines
accountabilities.
5. Engineers, policy makers, civil society and
the general public need spaces for sustaining a
living dialogue around issues of AI and ethics.
These need to be facilitated and supported
through funding and other forms of support.