AI for Good: Breakthrough Tracks
On September 29, 2020, the AI for Good Global Summit held a webinar about their breakthrough tracks and the projects associated with different topics.
The three breakthrough track topics are Gender Equity, Future of Food, and Pandemic Intelligence. Each topic contains one or two groups with projects they have created and submitted with the goal of generating meaningful projects that have short- or medium-term impact on advancing the United Nations sustainable development goals by using artificial intelligence (AI) data ecosystem, community building and collaboration.
The first breakthrough track topic was Pandemic Intelligence presented by the Montreal Artificial Intelligence Ethics Institute and member Allison Cohen. Their presentation was titled 鈥淭urning Pandemics into Gray Rhinos鈥 with the theme of how can we incentivize data collection and sharing to help build solutions that are equitable and fair when it comes to responses to communities affected by pandemics. According to Cohen, the gray rhino serves as an allegory for events that we like to ignore but if the right infrastructure is set up to monitor these types of events and don鈥檛 turn the blind eye that we turn to these sorts of events, we can respond to them much more effectively. The problem they are solving is marginalized communities are being disproportionately affected by COVID-19. The solution that Cohen and her team came up with was shifting the approach to pandemic response to meet the 鈥榞ray rhino鈥 threshold with permanent monitoring of infrastructures that is privacy preserving.
The first breakthrough track topic included another presentation from Intelligent Global Health鈥檚 member Mary-Ann Hartley. Their presentation was titled 鈥淲hat If鈥 Global COVID Policy Simulator鈥 with the question of how we can create predictive models that support informed policy making and mitigation of improper resource allocation during a pandemic. This artificial intelligence data simulator makes predictive models that inform data-driven policy-making and targeted resource allocation. The issue Hartley and her team are trying to address is the lack of evidence and transparency in policy making, which leads to arbitrary decisions, public mistrust, public non-compliance, and then ineffective policies. Their solution is the simulator and data driven personalized predications on how data reacts to changes in policies and the optimal policy tailored to the given situation. According to Hartley, the positive impact of their project is after COVID, nearly anything can be plugged into the policy simulator, as long as the data exists.
The second breakthrough track topic was Gender Equity presented by Outsight International鈥檚 team member Denise Soesilo. Their presentation was titled 鈥淭he Complete Picture Project鈥 with the idea of constructing inclusive and diverse test datasets that show a complete picture of communities for AI bias testing. The problem their team is trying to solve is the ability of not being able to test for bias if people do not show up in the data. According to Soesilo, their solution is simple, build more complete datasets. This provides developers and others concerned with AI bias, a starting point for testing, a complete picture of communities, including the people who are most often excluded or ignored. This matters a lot because in every community in the world, AI is becoming an important tool for making decisions that matter in people鈥檚 lives.
The third and final breakthrough track topic was Future of Food presented by Project Farm鈥檚 team member Marijn Markus. Their presentation was titled the 鈥淔ARM AI platform鈥 with the idea to offer services to smallholder farmers and insight to value chain partners by using mobile phones capable of receiving text messages and combining the smallholder farmer鈥檚 own data with satellite and market information to generate insights. According to Markus, Project Farm aims to solve the problem of using AI to design resilient food systems that can better anticipate, adapt, and/or mitigate system shocks.
To review or find more information on the AI for Good breakthrough tracks check out their website !
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