With the maturing of AI and multiagent systems research, we have a tremendous
opportunity to direct these advances towards addressing complex societal
problems. In pursuit of this goal of AI for Social Impact, we as AI researchers
must go beyond improvements in computational methodology; it is important to
step out in the field to demonstrate social impact. To this end, we focus on
the problems of public safety and security, wildlife conservation, and public
health in low-resource communities, and present research advances in multiagent
systems to address one key cross-cutting challenge: how to effectively deploy
our limited intervention resources in these problem domains. We present case
studies from our deployments around the world as well as lessons learned that
we hope are of use to researchers who are interested in AI for Social Impact.
In pushing this research agenda, we believe AI can indeed play an important
role in fighting social injustice and improving society.
Andrew Perrault, Fei Fang, Arunesh Sinha, Milind Tambe