“Algorithmic Rural Road Planning in India: Constrained Capacities and Choices in Public Sector” - Harsh Nisar, Government of India

10:45 am - 11:45 am

Join Harsh Nisar, Lead Data Scientist with the Government of India's Ministry of Rural Development for an upcoming talk in the AI for Social Impact Seminar Series. This lecture is free and open to the Penn State community.

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“Algorithmic Rural Road Planning in India: Constrained Capacities and Choices in Public Sector”

In this talk, Harsh Nisar will talk about how the peculiarities of government (within and the setting it operates in) impact algorithmic design, development, and deployment. He'll use his experience developing the resource allocation mechanism for a $10 billion road-maintenance program launched in 2018 to improve rural connectivity to schools, hospitals, and markets.

About the Speaker:

Harsh Nisar is currently the Lead Data Scientist at the Ministry of Rural Development, Government of India. The Ministry of Rural Development operates some of the largest welfare programs in the world targeting rural employment, roads, housing, and so on. At the Ministry, Nisar leads the Data & Insights Unit, which is an interdisciplinary team of HCI, Policy, and Data professionals who try to use data and algorithms to meaningfully improve service delivery for 800 million rural citizens in India. This includes using satellite imagery to find unmapped settlements, biases in resource allocation policies, and algorithmic decision support systems to reduce administrative burdens, among others. He also serves as an advisor to India's apex body for National Highways where he is working on improving emergency incident response times.

About the AI for Social Impact Seminar Series

The AI for Social Impact Seminar Series brings together researchers and thought leaders from a variety of fields to explore the diverse applications of artificial intelligence for a societal benefit. Through the series, the Center for Socially Responsible Artificial Intelligence aims to inspire new ideas and collaborations and to identify novel approaches that can advance discovery in the field at Penn State and beyond.