The second AI for Good Global Summit has generated 35 new projects which aim to utilise AI in development roles.
The competition brought together teams from the public and private sector to develop AI-based solutions in healthcare, agriculture and biodiversity, urban development, and to increase trust in AI.
The event was organised by the International Telecommunication Union (ITU) in partnership with 32 sister United Nations agencies, the XPRIZE Foundation and the Association for Computing Machinery (ACM),and held at ITU headquarters in Geneva last week
Houlin Zhao, ITU Secretary-General, commented: "Leveraging the power of ICTs, including artificial intelligence, is imperative if we are to improve the livelihoods of all people, everywhere, through achievement of the United Nations Sustainable Development Goals.
"This call to action by stakeholders was loud and clear at the first AI for Good Global Summit held one year ago. Now here at the 2nd annual summit, a powerful 'AI for Good' community movement has emerged. With its pioneering proposals and rich diversity of expertise, it is unstoppable."
Among the projects developed for the summit were three projects to use AI satellite image analysis to to predict and prevent deforestation, track livestock with great accuracy, and provide data analytics for micro-insurance to small-hold farmers. A fourth project proposal provides enabling infrastructure and common capabilities - through a 'global service platform' - to support new satellite data projects in achieving immediate scale.
Fifteen proposals were in healthcare, with ideas covering primary care, disease outbreaks and data analysis. Participants also discussed the creation of a new study platform that would be open to all interested stakeholders, and supported by ITU and the World Health Organization. This would collect use cases of AI in healthcare and identify the data formats and interoperability mechanisms required to amplify the impact of such use cases.
Seven project proposals focused on urban issues including support for linguistic diversity within cities, combating gender violence, and provide virtual testbeds for the simulation of smart city projects. These projects included the targeted establishment of an 'Internet of Cities', a global network able to share the data, knowledge and expertise required to replicate successful smart city projects elsewhere in the world.
Nine project proposals address three key dimensions of trust in AI: AI stakeholders' trust in AI developers; trust across national, cultural and organizational boundaries; and trust in AI systems themselves.
Other projects proposals seek to build trust in AI's contribution to agriculture and mental health. They investigate strategies for developing countries to maintain social stability as AI-driven automation influences labour markets. They also explore how the concept of trust varies across cultures, and they study how policymakers could encourage the development of trustworthy AI systems and datasets free of bias.
These projects would be supported by a proposed incubator for multidisciplinary collaboration in the interest of building trust in AI, trustfactory.ai.