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The myopia of model centrism
AI models seek to intervene in increasingly higher stakes domains, such as cancer detection and microloan allocation. What is the view of the world that guides AI development in high risk areas, and how does this view regard the complexity of the real world? In this talk, I will present results from my multi-year inquiry into how fundamentals of AI systems---data, expertise, and fairness...
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Will algorithms save our planet and will we regret it when they do?
We live in a time of unprecedented global environmental and ecological change: a warming planet, vanishing biodiversity, overfishing and intensifying ecosystem change from fire to draught to invasive species. Not only are these challenges frequently intertwined, all are closely coupled to social, economic, political components which play out in diverse and unequal ways. At the same time, we suddenly have access to ecological and environmental data at a scale we never imagined, thanks to...
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Title: Trustworthy Human-AI Partnerships
Abstract: Recent advances in AI, Machine learning and Robotics have significantly enhanced the capabilities of machines. Machine intelligence is now able to support human decision making, augment human capabilities, and, in some cases, take over control from humans and act fully autonomously. Machines are becoming more tightly embedded into systems alongside humans, interacting and influencing each other in a number of ways. Such human-AI partnerships are a new form of socio-technical system in which the potential...
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Efficient and targeted COVID-19 border testing via reinforcement learning
Throughout the COVID-19 pandemic, countries relied on a variety of ad-hoc border control protocols to allow for non-essential travel while safeguarding public health: from quarantining all travellers to restricting entry from select nations based on population-level epidemiological metrics such as cases, deaths or testing positivity rates....
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Title: How can AI improve the impact of biodiversity conservation
Abstract: Conservation practitioners have to deal with a multitude of different disciplines. These include subjects such as conservation planning which help identify where conservation should be prioritised, to how to most efficiently tackle illegal activities threatening a site, and social aspects such as how to engage local communities in the conservation of a site or to tackle the demand for products. Conservation scientists have to deal with many data inputs which makes it...
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Title: Algorithmic Information Design: Computability, Learnability and Applicability to Societal Challenges
Abstract: The celebrated field of mechanism design studies how a system designer can design agents' incentives, and consequently their actions, in order to steer their joint decisions towards a desirable outcome. This talk also examines the intervention of agents' actions but through a fundamentally different yet equally important "knob" --- i.e., influencing agents' decisions by designing the available information to each agent. This task,...
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Title: Informing Anti-Human Trafficking Efforts with Operations Research Models
Abstract: Human trafficking is a prevalent and malicious global human rights issue, with an estimated 24 million victims exploited worldwide. A major challenge to its disruption is the fact that human trafficking is a complex system interwoven with other illegal and...
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Title: Co-designing Tools to Counter Structural Oppression
Abstract: There has been a recent push in technology design to consider social implications of technology design — both historical, current, and future. In resource-constrained communities, there have been historical policies and practices (e.g., redlining, overpolicing...
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Title: Interdisciplinary intelligence mapping of illicit global environmental change
Abstract: A scientific understanding of human behavior is critical for improving humans’ ability to predict and adapt to global environmental change. The type of behavior that society defines or perceives as driving illicit global...
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Title: F-AI-Rest of Them All
Abstract: While clinical AI and medical risk scores have received much attention for their potential to achieve above-human performance, there are many concerns about their ability to mimic societal bias. In this talk, Dr. Ghassemi explores the difficulty of making state-of-the-art machine learning models behave as we say, not as we do, and how technical choices that seems natural in other settings may not work well in health.
Bio: Dr. Marzyeh Ghassemi is an Assistant Professor at MIT in...
Also read about the 2020 Rising Stars Workshop, where 60 of the brightest rising stars in AI for Social Impact (AISI), their research and activities all mentored by senior AISI faculty and researchers.
