AI for Social Impact: Learning and Planning in the Data-to-Deployment Pipeline.

摘要: 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 this goal for Social Impact, as researchers must go beyond improvements in computational methodology; it is important step out field demonstrate social impact. To end, focus on problems public safety security, wildlife conservation, health low-resource communities, present research address one key cross-cutting challenge: how effectively deploy our limited intervention resources problem domains. We case studies from deployments around world well lessons learned that hope are use who interested Impact. pushing agenda, believe can indeed play an role fighting injustice improving society.