Formal Recognition of Indigenous Data in AI: The Role of the WIPO Treaty on IP, Genetic Resources & Traditional Knowledge

Introduction

Our global outlooks on emerging technologies are crafted through socio-technical interactions.¹ This dictates relational dynamics between various stakeholders that involve “rights and obligations toward self and others.”² Artificial Intelligence (AI) mimics the above, as it finds its roots within values and ideals of the “Western scientific worldview.”³Therefore curating a relational dynamic that emulates the ‘Western experience’. A consequence of this is the undervaluing of non-Western experiences. A key example of this is Indigenous Knowledge (IK) that encompasses “indigenous practices and protocol, customs and ways of interaction with society and the natural world”.⁴ This is further expressed and actualised through information systems such as genetic resources and traditional knowledge that can be labeled as indigenous data.

Undervaluing such data essentially leads to discriminatory practices reminiscent of ‘colonial extraction’, where Western states preserve asymmetrical relations of power by the “repackaging and reselling” of technological solutions utilizing indigenous data without formal recognition and consent.⁵ The development of AI technologies utilizing indigenous data can cause misappropriation that would amplify commercial exploitation of these resources. Bearing this in mind, this blog seeks to explore the WIPO Treaty on Intellectual Property, Genetic Resources and Associated Traditional Knowledge as a legal tool with the potential to regulate the misappropriation of indigenous data in emerging technology. In our previous blog, we discussed the key features of the new WIPO treaty and its implications for the Kenyan legal landscape. This blog’s discussion will focus on analyzing the disclosure obligation within the treaty as a means of formal recognition of indigenous data.

Misappropriation of Indigenous Data in Emerging Technology

Indigenous societies are key stakeholders within the digital economy as they contribute to the development and application of AI as citizens of an “AI permeated world” and as actual subjects of AI applications.⁶ The societies curate traditional knowledge that have a “practical element” that attracts “commercial potential”,⁷ especially within the development of emerging technologies. Specifically, genetic resources, based on traditional knowledge, offer great socio- technological benefits.⁸ However, “when others seek to benefit from the traditional knowledge, especially for industrial or commercial advantage, this can lead to concerns that the knowledge has been misappropriated.”⁹ This allows for Western developers to curate patentable improvements on traditional knowledge that are not “considered to be improvements at all but rather original inventions.”¹⁰

Key illustrations of this include the development of precision agriculture and smart farming technologies in Africa’s agricultural industries. These technologies utilize algorithmic decision-making to assist with improving the profitability and sustainability of agriculture.¹¹ Specifically within the Eastern African context, East African women are held to possess ‘expert knowledge of land, plants and soil through generational small-holder farming practices’.¹² Their traditional knowledge constitutes as indigenous data that has assisted with curating precision agriculture and smart farming applications, as the applications are data-driven systems.¹³ Despite the value of their indigenous data, these women are considered to be “beneficiaries” rather than co-creators of these AI technologies.¹⁴ This stems from the lack of formal recognition of their traditional knowledge as indigenous data that gains value within the digital economy.

Illustrations of these technologies include: Kenyan-based Plant Village’s Nuru AI agricultural application, that utilizes detection technology to identify objects on plant leaves and patterns indicating disease outbreaks, the app utilizing local data is trained using images of healthy and diseased crop leaves.¹⁵ Collection of local data is primarily through the shared knowledge of small-scale farmers such as Kenyan women farmers. Failure to recognize their traditional knowledge devalues their knowledge.¹⁶ This duplicates the colonial practices of extraction, where Western developers utilize traditional knowledge to curate AI applications that do not formally recognize their contributions.¹⁷

Strengthening Legal Frameworks: Protecting Indigenous Data Through Intellectual Property Rights and the WIPO Treaty

Utilizing an Intellectual Property (IP) lens, indigenous data is formally recognized within IPRs as traditional knowledge and genetic resources, which are afforded protection usually within domestic legislation such as the Kenyan Protection of Traditional Knowledge and Cultural Expressions Act 2016. The Act protects and promotes traditional knowledge, cultural expression as well as traditional knowledge that is related to genetic resources. The Act provides for recognition of the knowledge, where there is need for prior consent for third parties before utilizing the traditional knowledge. However, within the international sphere, there is a lack of recognition as the unpatentability of traditional knowledge and genetic resources contributes to the exclusion of indigenous societies claiming proprietorship over the information.¹⁸ Therefore, “without an exclusionary property right”, third parties have leeway to commercialize information for their own benefit.¹⁹To tackle this dilemma, international IP discourse is steered around establishing a mandatory disclosure requirement about the origin and source of the TKs and GRs.²⁰

The treaty is a landmark agreement that aims to protect the Intellectual Property rights (IPRs) of indigenous peoples and local communities in relation to genetic resources and associated traditional knowledge. The treaty is a significant step forward in ensuring that IP systems are more inclusive and responsive to the needs of indigenous societies and local communities. The treaty places a strong emphasis on the protection of traditional knowledge and associated innovations, recognizing the need to adapt the patent system to acknowledge and respect the rights of indigenous peoples and local communities.

This is actualised through article 3 of the treaty that seeks to prevent the misappropriation of genetic resources and traditional knowledge by ensuring transparency and accountability in the use of these resources.²¹ The treaty requires patent applicants to disclose the country of origin or source of genetic resources and the indigenous peoples or local community that provided the traditional knowledge associated with genetic resources.²² This allows for formal recognition which is essentially crucial for preserving cultural heritage, empowering indigenous communities, ensuring inclusive decision-making, and improving data quality.

By requiring patent applicants to disclose the source of genetic resources and traditional knowledge, the treaty helps to address the historical marginalization and exclusion of indigenous peoples from decision-making processes related to their data, especially within the development of AI technologies. Recognition of Indigenous data, specifically within the international sphere is paramount as it provides domestic legislation support to reinforce the proprietary rights of local communities and indigenous societies. In addition, this promotes Indigenous Data Sovereignty as indigenous societies and local communities have the right to “own control and govern their data” and ensure data collected and processed “aligns with their values and interests.”²³

Conclusion

The disclosure requirement outlined in the treaty is the first step towards formally recognizing indigenous data. However, to fully protect traditional knowledge and prevent its exploitation, additional measures such as licensing agreements or compensation for subsequent inventions are essential.²⁴ These mechanisms can empower traditional groups to control the use of their knowledge, negotiate fair terms for its utilization, and receive appropriate compensation for its application in emerging technologies, thus, actualizing moral and economic benefits that arise from their knowledge. By implementing licensing agreements and compensation structures, traditional communities can safeguard their IPRs, ensure equitable benefit-sharing and prevent the misappropriation of their valuable knowledge and resources. This permits valuerecognition within the digital economy, which is key to recognition for these communities.”²⁵

Image is from commons.wikimedia.org

Acknowledgements

This blog draws inspiration from the insightful ideas of Dr. Melissa Omino.