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 facilitated 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 development 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 inflicted 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 development of AI systems, but also in organizational chains of responsibility. 10. In working towards transparency, maintain awareness that transparency has its own ethical pitfalls and limits.
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Nordic engineers’ stand on Artificial Intelligence and Ethics Policy recommendations and guidelines