Becoming Good at AI for Good
- URL: http://arxiv.org/abs/2104.11757v2
- Date: Mon, 3 May 2021 16:40:55 GMT
- Title: Becoming Good at AI for Good
- Authors: Meghana Kshirsagar, Caleb Robinson, Siyu Yang, Shahrzad Gholami, Ivan
Klyuzhin, Sumit Mukherjee, Md Nasir, Anthony Ortiz, Felipe Oviedo, Darren
Tanner, Anusua Trivedi, Yixi Xu, Ming Zhong, Bistra Dilkina, Rahul Dodhia,
Juan M. Lavista Ferres
- Abstract summary: We detail the different aspects of this type of collaboration broken down into four high-level categories.
We briefly describe two case studies to illustrate how some of these takeaways were applied in practice.
- Score: 21.58081555662445
- License: http://creativecommons.org/licenses/by/4.0/
- 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.
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