Artificial Intelligence for Social Impact - Monash Prato Dialogue
Event date: 1 December 2021
The Monash Prato Dialogue is a Distinguished Lecture series on Artificial Intelligence and its impact on society. In the fifth lecture of the series, Professor Milind Tambe outlined five projects that create ground-breaking precedents for the application of AI and data science to specific problems in the areas of public health and wildlife conservation.
Watch the lecture recording below.
During the lecture, Professor Tambe referenced the following resources:
- Raising Awareness about HIV among Homeless Youth (Research paper)
- Fairness in influence maximization (Research paper)
- AI for social good with ARMMAN - India-based non-profit leveraging maternal and neonatal health
- Contingency-Aware Influence Maximization: A Reinforcement Learning Approach (Research Paper)
- Bridging the Gap Between Theory and Practice in Influence Maximization: Raising Awareness about HIV among Homeless Youth (Research Paper)
- Prevention of Tuberculosis via Prediction and Multi-agent Planning (Research Paper)
- Collapsing Bandits and Their Application to Public Health Interventions (Research Paper)
- Test sensitivity is secondary to frequency and turnaround time for COVID-19 surveillance (Research Paper)
- PAWS: Game Theory Based Protection Assistant for Wildlife Security (Research Paper)
ABOUT THE SPEAKER
Professor Milind Tambe is Gordon McKay Professor of Computer Science and Director of Center for Research on Computation and Society at Harvard University; he is also Director "AI for Social Good" at Google Research India.
Prof Tambe is a fellow of AAAI (Association for Advancement of Artificial Intelligence), ACM (Association for Computing Machinery), as well as recipient of the IJCAI John McCarthy Award, AAAI Robert S. Engelmore Memorial Lecture Award, ACM/SIGAI Autonomous Agents Research Award, the Columbus Fellowship Foundation Homeland security award, the INFORMS Wagner prize for excellence in Operations Research practice and others.
With the maturing of AI and multiagent systems research, we have a tremendous opportunity to direct these advances towards addressing complex societal problems. Prof. Tambe focused on the problems of public health and conservation, and addressed one key cross-cutting challenge: how to effectively deploy our limited intervention resources in these problem domains. He presented results from work around the globe in using AI for HIV prevention, maternal and child care interventions, TB prevention and COVID modeling, as well as for wildlife conservation.
Achieving social impact in these domains often requires methodological advances. To that end, he highlights key research advances in multiagent reasoning and learning, in particular, in computational game theory, restless bandits and influence maximization in social networks. In pushing this research agenda, he believes, our ultimate goal is to facilitate local communities and non-profits to directly benefit from advances in AI tools and techniques.
Monash Prato Dialogue - Fostering Global Dialogue & Discovery in AI and Data Science
The Monash Data Futures Institute Prato Dialogue Distinguished Lecture Series aims to explore the evolving impact of data science and AI in society by fostering a global dialogue.
The lecture series takes its name from Monash University's Centre in Prato, Italy. Located in the heart of Tuscany, our Prato Centre represents a European base for international research and education, intellectual and cultural exchanges and brings people together to meet, learn and collaborate with peers and colleagues from around the world.
Please note: this lecture series was virtual in 2021.
Schedule of lectures and links to video recordings:
- Professor Stuart Russell - Provably Beneficial Artificial Intelligence (5 August 2021)
- Professor Huw Price - The Future of Artificial Intelligence: Academia’s Role in Getting it Right (09 September 2021)
- Professor Virginia Dignum - Responsible AI: From Principles to Action (21 October 2021)
- Professor Rayid Ghani - Doing Good with AI: Fairly and Equitably (18 November 2021)