Aiming for a “more open, inclusive and sustainable AI on an international level”, the initiative FAIR Forward has developed multiple pilot applications “improving the lives of millions”. By making the datasets (that are used to train the algorithms) openly available, the initiative actively encourages local innovators to take up the data, improve it and localize it. Its strategy also includes working with geospatial datasets, ground truth data, and other open data sources to build AI applications aimed at tackling climate change – as well as joint efforts with policymakers in the development of frameworks for “value-based AI”. Having launched a whole variety of pilot applications, the initiative addresses a wide range of SDGs, including SDG3, SDG5, SDG7, SDG9, SDG10, SDG13, and SDG17.
As announced in the previous few articles, the IRCAI Scientific Program Committees and the IRCAI Scientific Journal Editorial Board have completed their review of the Global Top 100 project submissions. 10 solutions were deemed “outstanding projects” based on their centrality of AI, the potential impact on relevant SDG(s), demonstration of potential in completed work (either proof of concept or completed research paper), and ethical design. The aim of this article is to introduce the project to relevant stakeholders and the broader public and to make the voices of the team behind FAIR Forward heard on the world stage.
A project by the German Corporation for International Cooperation (GIZ), FAIR Forward is developing pilot applications built on open AI training data – across six partner countries: India, Ghana, Kenya, Zambia, Uganda and Rwanda. In Rwanda, for example, the initiative developed a voice-assisted COVID-19 information chatbot. Serving as the central information hub of the Rwandan government, the application reached 150,000 users and facilitated more than 2,000,000 interactions within the first ten days of its launch. The open voice technology promises to make basic services available to millions, including illiterate and/or digitally excluded citizens. Striving to improve access to training data and AI technologies for local innovation, FAIR Forward makes the datasets (which the algorithms are trained on) openly available on GitHub, as a way to actively encourage local businesses, governments, and academia to take up the data, improve it and localize it. To strengthen the local technical know-how, the strategy also oversees the facilitation of traineeships, webinars, and open online courses on AI to the local youth.
Besides its conversational AI systems, the initiative also works with geospatial datasets, ground truth data, and other open data sources to build applications addressing a variety of environmental challenges including sustainable agriculture, climate protection, and food security. As such, FAIR Forward collaborated in the development of ML-based datasets aimed at classifying different crop types available in South Africa. Similarly, the underlying data has been made openly and freely available, allowing local innovation ecosystems to use the models for agricultural monitoring.
Finally, FAIR Forward also collaborates with international and local policymakers in the development of frameworks for “value-based AI”, as a way to address the concerns revolving around ethics, data protection, and privacy, that come with the development of AI-based technologies.
This initiative is an effort by GIZ (on behalf of BMZ) and is complemented by the work of partners including Smart Africa, Mozilla Foundation, IDRC, UN Global Pulse & Lacuna Fund.
For more information about the initiative, feel free to look up FairForward’s website and Twitter:
