The purpose of this call for EOI is to identify projects to submit full proposals to develop open and accessible datasets for machine learning applications that will enable natural language processing for languages in sub-Saharan Africa. The ability to communicate and be understood in one’s own language is fundamental to digital and societal inclusion.
Natural language processing techniques have enabled critical AI applications that facilitate digital inclusion and improvements in numerous fields, including: education, finance, healthcare, agriculture, communication, and disaster response, among others. Many advances in both fundamental and applied NLP have stemmed from openly licensed and publicly available datasets.
Lacuna Fund aims to:
- Disburse funds to institutions to create, expand, and/or maintain datasets that fill gaps and reduce bias in labeled data used for machine learning.
- Make it possible for underserved populations to take advantage of advances offered by AI.
- Deepen understanding by the machine learning and philanthropy communities of how to most effectively and efficiently fund the development and maintenance of equitably labeled datasets.
The Steering Committee of Lacuna Fund: The Voice on Data has identified the following areas as domains where a lack of labeled training data limits the potential of machine learning or presents the risk of bias or inequity.
- Agriculture: Enabling new and more robust AI applications through remote sensing and other critical datasets.
- Language: Translation, speech recognition, and other datasets to enable the promise of digital communication for all.
- Health: Improving the robustness and availability of AI solutions in healthcare through datasets across the value chain.
Principles of the Fund
The following principles will guide the governance and operations of Lacuna Fund.
- Accessibility – Lacuna Fund is committed to ensuring that the datasets created through its funding are accessible to and benefit underserved communities in service of the goals. Datasets and related intellectual property will utilize appropriate open data licensing to maximize responsible downstream use.
- Equity – Lacuna Fund aims to make AI more equitable by supporting datasets that are created by and responsive to the needs of those with underrepresented identities globally. These datasets should not create or reinforce bias (e.g., they should be gender inclusive and representative of people of color globally), nor should they support systems or technologies that create harm.
- Ethics – Lacuna Fund will fund data collection in a manner consistent with ethical labor standards and require recipients to specify steps they will take to protect privacy and prevent harm in the collection, licensing, and use of datasets created with grant funds.
- Participatory Approach – Lacuna Fund strives to meet the needs of affected stakeholders by encouraging the leadership or strong engagement of local experts, beneficiaries, and end users in the governance of the Fund and in supported projects. The Fund will consider participation in a manner consistent with the principles on equity and ethics.
- Quality – Data generated by Lacuna-funded efforts should be of high quality, enabling beneficial applications in research, communities, and industry.
- Transformational Impact – Lacuna Fund aims to unlock the advances offered by AI for poor and underserved communities by funding datasets that address fundamental gaps in AI.
Lacuna Fund aims to make its funding accessible to as many organizations as possible in the AI for social good space and cultivate capacity and emerging organizations in the field.
To be eligible for funding, organizations must:
- Be either a non-profit entity, research institution, for-profit social enterprise, or a team of such organizations. Individuals must apply through an institutional sponsor. Partnerships are strongly encouraged; however, only the lead applicant will receive funds.
- Have a mission supporting societal good, broadly defined.
- Be headquartered in or have a substantial partnership in sub-Saharan Africa.
- Have all necessary national or other approvals to conduct proposed research, as well as data use agreements or plans to secure them. The approval process may be conducted in parallel with grant application, if necessary. Approval costs, if any, are the responsibility of the applicant.
- Have the technical capacity – or the ability to build this capacity through a partnership described in the EOI – to conduct dataset labeling, creation, aggregation, expansion, and / or maintenance, including the ability to apply best practice and established standards in the specific domain (eg natural language processing) to allow high quality AI / ML analytics to be performed by multiple entities.
For more information, visit https://lacunafund.org/apply/