About the Co-Creation Framework

Over the past decade, the international development community, comprising international agencies, donors, innovators, and beneficiaries, has gone through a “data revolution” as it accrues novel datasets and digital assets, adopts new analytic methods, and begins to leverage machine learning (ML) and artificial intelligence (AI) technology to accelerate the impact of its work. While these new techniques present unique opportunities to advance the Sustainable Development Goals, challenges remain in how the benefits of these tools outweigh their unintended risks. As their adoption becomes more widespread, acute issues have emerged related to questions of fairness, accountability, and transparency.

In order to effectively account for the broadest array of ethical considerations, while simultaneously ensuring the design of a project leads to maximum benefit, the International Development Innovation Alliance (“IDIA”) Emerging Technology Working Group (“ETWG”) seeks to build upon the concept of participatory design in machine learning as a pathway to promote more equitable and inclusive adoption of AI tools for development outcomes. Motivated by the Whistler Principle of facilitating collaboration and co-creation across public, private and civil society sectors, IDIA provides a platform to foster participatory design. IDIA’s membership spans bilateral donors to leading development agencies, and by drawing on the broader networks of these organizations through consultation and collaboration, IDIA can bring together a wide diversity of perspectives and insights to the topic. 

This co-creation framework was developed by the ETWG through a consultative process with NGOs, academia, and research institutes including (insert names). It is meant as a framework that seeks to build a shared understanding and provide resources for international development actors engaged in AI and emerging technology programming, so as to help envision and implement inclusive co-creation in development and deployment of AI/ML solutions. It is meant as a dynamic guide, with updates and additions encouraged as more users leverage the tool.

Disclaimer:

This framework presents approaches and insights that have been collected through a multi-disciplinary and collaborative process led by the IDIA Emerging Technologies Working Group. This framework does not represent the official policies, approaches or opinions of any single contributing agency or IDIA member, nor reflect their institutional endorsement or implementation of the approaches contained herein.