Becoming Good at AI for Good
Abstract
AI for good (AI4G) projects involve developing and applying artificial intelligence (AI) based solutions to further goals in areas such as sustainability, health, humanitarian aid, and social justice. Developing and deploying such solutions must be done in collaboration with partners who are experts in the domain in question and who already have experience in making progress towards such goals. Based on our experiences, we detail the different aspects of this type of collaboration broken down into four high-level categories: communication, data, modeling, and impact, and distill eleven takeaways to guide such projects in the future. We briefly describe two case studies to illustrate how some of these takeaways were applied in practice during our past collaborations.
Cite
@article{arxiv.2104.11757,
title = {Becoming Good at AI for Good},
author = {Meghana Kshirsagar and Caleb Robinson and Siyu Yang and Shahrzad Gholami and Ivan Klyuzhin and Sumit Mukherjee and Md Nasir and Anthony Ortiz and Felipe Oviedo and Darren Tanner and Anusua Trivedi and Yixi Xu and Ming Zhong and Bistra Dilkina and Rahul Dodhia and Juan M. Lavista Ferres},
journal= {arXiv preprint arXiv:2104.11757},
year = {2021}
}
Comments
Accepted to AIES-2021