With the rapid advancements in computational power, the decades-long vision of using and deploying artificial intelligence (AI) has become a reality. The technology’s swift development has allowed it to transform every walk of life, as it is a wide-ranging tool that enables people to rethink how to analyze data, integrate information and use the resulting insights for improved decision making. While AI’s deployment and uptake undoubtedly provide humanity with numerous opportunities to address global challenges, the data used for AI systems can create risks that must be addressed to avoid undesirable outcomes. In order to fully reap the benefits of AI and fulfil commitments to our common future, data and statistics must be generated and leveraged to ensure that everyone has a voice and is visible.
Despite this noble pledge, AI’s contemporary effective deployment is exposing many inequalities by creating data invisible groups. Traditionally underserved and vulnerable populations, such as persons with disabilities, refugees, migrants, and individuals in the LGBT community, make up the strata of data invisible groups. These individuals and communities will most likely remain invisible without creating iWith the rapid advancements in computational power, the decades-long vision of using and deploying artificial intelligence (AI) has become a reality. The technology’s swift development has allowed it to transform every walk of life, as it is a wide-ranging tool that enables people to rethink how to analyze data, integrate information and use the resulting insights for improved decision making. While AI’s deployment and uptake undoubtedly provide humanity with numerous opportunities to address global challenges, the data used for AI systems can create risks that must be addressed to avoid undesirable outcomes. In order to fully reap the benefits of AI and fulfil commitments to our common future, data and statistics must be generated and leveraged to ensure that everyone has a voice and is visible. Despite this noble pledge, AI’s contemporary effective deployment is exposing many inequalities by creating data invisible groups2. Traditionally underserved and vulnerable populations, such as persons with disabilities, refugees, migrants, and individuals in the LGBT community, make up the strata of data invisible groups. These individuals and communities will most likely remain invisible without creating inclusive data systems guided by principles for data minimization and sharing.
This policy brief has been designed to provide UNESCO Member States with a better understanding of the need for greater transparency in data usage by building a case for data sharing and minimization. The insights obtained throughout the paper strive to inform improved decision-making processes and policies and promote capacity building within countries with nascent and/or developing capabilities in AI and the data that underpinnclusive data systems guided by principles for data minimization and sharing. This policy brief has been designed to provide UNESCO Member States with a better understanding of the need for greater transparency in data usage by building a case for data sharing and minimization. The insights obtained throughout the paper strive to inform improved decision-making processes and policies and promote capacity building within countries with nascent and/or developing capabilities in AI and the data that underpin it.
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This policy report was produced by UNESCO in partnership with Tambourine Innovation Ventures.
It was coauthored by Nikola Neftenov, Senior Emerging Tech and IP Research Associate, Dr. Miriam Stankovic, Senior Digital Policy Specialist and Ravi Gupta, CEO, of Tambourine Innovation Ventures, with the assistance of Ms. Ana Ristovska.
TIV is a knowledge-driven development advisory and venture acceleration firm with deep domain expertise in AI and data, Innovation and Intellectual Property, Technology Commercialization, and ICT for Development.
