These projects would be supported by a proposed incubator for multidisciplinary collaboration in the interest of building trust in AI

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Thirty-five innovative project proposals leveraging the power of artificial intelligence (AI) ‘for good’ were generated at the 2nd AI for Good Global Summit, held in Geneva at the headquarters of the International Telecommunication Union ( ITU), the United Nations specialized agency for information and communication technology (ICT).

The pioneering proposals were conceived at the summit by expert ‘breakthrough’ teams to address: expanded and improved health care; enhanced monitoring of agriculture and biodiversity using satellite imagery; ‘smart’ urban development; and trust in AI.  

The summit connected AI innovators with public and private-sector decision-makers, creating collaboration opportunities to execute the ‘AI for Good’ project proposals in the near and medium terms.  

“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,” said ITU Secretary-General Houlin Zhao. “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."

The AI for Good community at the summit discussed the merits of sharing AI tools and resources, datasets, and supporting knowledge and expertise – a vision the summit's participants conceptualized as "AI and Data Commons". This responds to growing recognition among stakeholders that shared resources could spur new AI for Good projects, enable significant scale, and create incentives to return new and improved resources to the AI for Good community.

This year's event was organized by ITU in partnership with 32 sister United Nations agencies, the XPRIZE Foundation and the Association for Computing Machinery (ACM).

Pioneering AI-driven project proposals

Monitoring agriculture and biodiversity using satellite imagery
Three project proposals use AI-powered satellite imagery analysis 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.

AI-improved healthcare
Fifteen project proposals aim to improve and expand healthcare in fields spanning primary care and service delivery, the detection of impending vision loss and osteoarthritis, the integration and analysis of medical data, the consideration afforded to AI by healthcare policy, and responses to outbreaks of disease and other medical emergencies.

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.

Smart urban development
Seven project proposals aim to support linguistic diversity within cities, combat 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.

Trust in AI
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.