AI for Social Good: Between My Research and the Real World
Abstract
AI for social good (AI4SG) is a research theme that aims to use and advance AI to improve the well-being of society. My work on AI4SG builds a two-way bridge between the research world and the real world. Using my unique experience in food waste and security, I propose applied AI4SG research that directly addresses real-world challenges which have received little attention from the community. Drawing from my experience in various AI4SG application domains, I propose bandit data-driven optimization, the first iterative prediction-prescription framework and a no-regret algorithm PROOF. I will apply PROOF back to my applied work on AI4SG, thereby closing the loop in a single framework.
Cite
Text
Shi. "AI for Social Good: Between My Research and the Real World." AAAI Conference on Artificial Intelligence, 2021. doi:10.1609/AAAI.V35I18.17863Markdown
[Shi. "AI for Social Good: Between My Research and the Real World." AAAI Conference on Artificial Intelligence, 2021.](https://mlanthology.org/aaai/2021/shi2021aaai-ai/) doi:10.1609/AAAI.V35I18.17863BibTeX
@inproceedings{shi2021aaai-ai,
title = {{AI for Social Good: Between My Research and the Real World}},
author = {Shi, Zheyuan Ryan},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2021},
pages = {15732-15733},
doi = {10.1609/AAAI.V35I18.17863},
url = {https://mlanthology.org/aaai/2021/shi2021aaai-ai/}
}