As announced by the International Telecommunication Union (ITU), the United Nations specialised agency
for information and communication technology (ICT), its annual AI for Good Global Summit has successfully generated thirty-five
innovative project proposals leveraging the power of artificial intelligence
(AI) for good.
"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 Mr Houlin Zhao.
“This year, we hope to spur action to ensure that artificial intelligence accelerates progress towards the Sustainable Development Goals (SDGs),” Mr Zhao said in his welcoming remarks.
“Already, AI solutions are being developed to help increase crop yields, manage natural disasters, reduce road congestion, or diagnose heart, eye, and blood disorders.”
The summit gathered 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. This
year’s event was organized by ITU in partnership with 32 sister United Nations
agencies, the XPRIZE
Foundation and
the world's largest educational and scientific computing society, the Association for Computing Machinery (ACM).
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 conceptualised 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 community.
The pioneering proposals seek to deliver breakthroughs in:
(1) expanded and improved health care, (2) enhanced monitoring of agriculture
and biodiversity using satellite imagery, (3) smart urban development, and (4) trust
in AI.
(1)
AI-improved healthcare
The
Summit saw the formulation of fifteen AI-project proposals that 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 Organisation
(WHO). This would help gather use cases of AI in healthcare and identify the
data formats and interoperability mechanisms required to amplify the impact of
such use cases.
(2)
Monitoring agriculture and biodiversity
using satellite imagery
In enhancing monitoring of agriculture and biodiversity, three
projects propose the use of 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. Another project
proposal provides enabling infrastructure and common capabilities – through a
'global service platform' – to support new satellite data projects in achieving
immediate scale.
(3)
Smart urban development
In supporting 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.
(4)
Building trust in AI
A total of nine project proposals address three key
dimensions of trust in AI: (1) AI stakeholders' trust in AI developers; (2) trust
across national, cultural and organizational boundaries; and (3) 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.
