The term ‘Indigenous’ is used as connective tissue rather than descriptive skin, to appreciate the hyperdense textures of our points of contact while respecting our rich and productive differences.
The designation ‘v. 1’ is used to denote that this is only a first iteration and that we anticipate that these guidelines will be modified, adapted and updated as they circulate, to reflect the needs of specific Indigenous nations and communities.
The purpose of these guidelines is to assist and guide the development of AI systems towards morally and socially desirable ends. Our focus is on the use and application of AI in Indigenous contexts. Yet we also believe these guidelines will be of use in other contexts, given that every implementation of
an AI system is a product and expression of cultural values. The goal of these guidelines is to promote intergenerational transmission of knowledge, ceremony, and practice, to connect and enhance our communities and to frame our relationships to the land, sea, and skyscapes. They are aimed at any person, group, organization, institute, company, and/or political or governmental representative that wishes to undertake responsible and fair development of AI systems with Indigenous communities. This responsibility includes, amongst other things, contributing to scientific or technological progress, project
Indigenous Protocol and Artificial Intelligence Workshops Position Paper 21 development, rules, regulations, codes and algorithm development, methodological approaches and public opinion.
Although these guidelines are presented as a list, there is no hierarchy in its ordering. The first principle is no less important or weighted higher than the last.

Indigenous knowledge is often rooted in specific territories. It is also useful in considering issues of global importance.

AI systems should be designed in partnership with specific Indigenous communities to ensure the systems are capable of responding to and helping care for that community (e.g., grounded in the local) as well as connecting to global contexts (e.g. connected to the universal).

Indigenous knowledge is often relational knowledge.

AI systems should be designed to understand how humans and non-humans are related to and interdependent on each other. Understanding, supporting and encoding these relationships is a primary design goal.

AI systems are also part of the circle of relationships. Their place and status in that circle will depend on specific communities and their protocols for understanding, acknowledging and incorporating new entities into that circle.

Indigenous people are often concerned primarily with their responsibilities to their communities.

AI systems developed by, with, or for Indigenous communities should be responsible to those communities, provide relevant support, and be accountable to those communities first and foremost.

Protocol is a customary set of rules that govern behaviour.

Protocol is developed out of ontological, epistemological and customary configurations of knowledge grounded in locality, relationality and responsibility.

Indigenous protocol should provide the foundation for developing governance frameworks that guide the use, role and rights of AI entities in society.

There is a need to adapt existing protocols and develop new protocols for designing, building and deploying AI systems. These protocols may be particular to specific communities, or they may be developed with a broader focus that may function across many Indigenous and non-Indigenous communities.

All technical systems are cultural and social systems. Every piece of technology is an expression of cultural and social frameworks for understanding and engaging with the world. AI system designers need to be aware of their own cultural frameworks, socially dominant concepts and normative ideals; be wary of the biases that come with them; and develop strategies for accommodating other cultural and social frameworks. Computation is a cultural material.

Computation is at the heart of our digital technologies, and, as increasing amounts of our communication is mediated by such technologies, it has become a core tool for expressing cultural values. Therefore, it is essential for cultural resilience and continuity for Indigenous communities to develop computational methods that reflect and enact our cultural practices and values.

Culture forms the foundation of the technology development ecosystem, or ‘stack.’ Every component of the AI system hardware and software stack should be considered in the ethical evaluation of the system. This starts with how the materials for building the hardware and for energizing the software are extracted from the earth, and ends with how they return there. The core ethic should be that of do-no-harm.

Indigenous communities must control how their data is solicited, collected, analysed and operationalized. They decide when to protect it and when to share it, where the cultural and intellectual property rights reside and to whom those rights adhere, and how these rights are governed. All AI systems should be designed to respect and support data sovereignty.

Open data principles need to be further developed to respect the rights of Indigenous peoples in all the areas mentioned above, and to strengthen equity of access and clarity of benefits. This should include a fundamental review of the concepts of ‘ownership’ and ‘property,’ which are the product of non-Indigenous legal orders and do not necessarily reflect the ways in which Indigenous communities wish to govern the use of their cultural knowledge.