6. AI systems should be developed in a diverse team that includes individuals capable of assessing the ethical and socioeconomic implications of the system;

Principle: Seven principles on the use of AI systems in government, Jun 28, 2018 (unconfirmed)

Published by The Treasury Board Secretariat of Canada (TBS)

Related Principles

Human, social and environmental wellbeing

Throughout their lifecycle, AI systems should benefit individuals, society and the environment. This principle aims to clearly indicate from the outset that AI systems should be used for beneficial outcomes for individuals, society and the environment. AI system objectives should be clearly identified and justified. AI systems that help address areas of global concern should be encouraged, like the United Nation’s Sustainable Development Goals. Ideally, AI systems should be used to benefit all human beings, including future generations. AI systems designed for legitimate internal business purposes, like increasing efficiency, can have broader impacts on individual, social and environmental wellbeing. Those impacts, both positive and negative, should be accounted for throughout the AI system's lifecycle, including impacts outside the organisation.

Published by Department of Industry, Innovation and Science, Australian Government in AI Ethics Principles, Nov 7, 2019

Accountability

Those responsible for the different phases of the AI system lifecycle should be identifiable and accountable for the outcomes of the AI systems, and human oversight of AI systems should be enabled. This principle aims to acknowledge the relevant organisations' and individuals’ responsibility for the outcomes of the AI systems that they design, develop, deploy and operate. The application of legal principles regarding accountability for AI systems is still developing. Mechanisms should be put in place to ensure responsibility and accountability for AI systems and their outcomes. This includes both before and after their design, development, deployment and operation. The organisation and individual accountable for the decision should be identifiable as necessary. They must consider the appropriate level of human control or oversight for the particular AI system or use case. AI systems that have a significant impact on an individual's rights should be accountable to external review, this includes providing timely, accurate, and complete information for the purposes of independent oversight bodies.

Published by Department of Industry, Innovation and Science, Australian Government in AI Ethics Principles, Nov 7, 2019

V. Diversity, non discrimination and fairness

Data sets used by AI systems (both for training and operation) may suffer from the inclusion of inadvertent historic bias, incompleteness and bad governance models. The continuation of such biases could lead to (in)direct discrimination. Harm can also result from the intentional exploitation of (consumer) biases or by engaging in unfair competition. Moreover, the way in which AI systems are developed (e.g. the way in which the programming code of an algorithm is written) may also suffer from bias. Such concerns should be tackled from the beginning of the system’ development. Establishing diverse design teams and setting up mechanisms ensuring participation, in particular of citizens, in AI development can also help to address these concerns. It is advisable to consult stakeholders who may directly or indirectly be affected by the system throughout its life cycle. AI systems should consider the whole range of human abilities, skills and requirements, and ensure accessibility through a universal design approach to strive to achieve equal access for persons with disabilities.

Published by European Commission in Key requirements for trustworthy AI, Apr 8, 2019

4. As part of an overall “ethics by design” approach, artificial intelligence systems should be designed and developed responsibly, by applying the principles of privacy by default and privacy by design, in particular by:

a. implementing technical and organizational measures and procedures – proportional to the type of system that is developed – to ensure that data subjects’ privacy and personal data are respected, both when determining the means of the processing and at the moment of data processing, b. assessing and documenting the expected impacts on individuals and society at the beginning of an artificial intelligence project and for relevant developments during its entire life cycle, and c. identifying specific requirements for ethical and fair use of the systems and for respecting human rights as part of the development and operations of any artificial intelligence system,

Published by 40th International Conference of Data Protection and Privacy Commissioners (ICDPPC) in Declaration On Ethics And Data Protection In Artifical Intelligence, Oct 23, 2018

· We will make AI systems accountable

1. Accountability for the outcomes of an AI system lies not with the system itself but is apportioned between those who design, develop and deploy it 2. Developers should make efforts to mitigate the risks inherent in the systems they design 3. AI systems should have built in appeals procedures whereby users can challenge significant decisions 4. AI systems should be developed by diverse teams which include experts in the area in which the system will be deployed

Published by Smart Dubai in Dubai's AI Principles, Jan 08, 2019