Realizing AI for Impact: Towards Participatory Human-AI Collaboration for Water Conservation and Reproductive Health
Abstract
AI has immense potential for positive social impact, including in domains ranging from conservation to health. However, it can be challenging to account for human collaborations and real-world uncertainties when deploying such systems, which can lead to critical errors. Therefore, my research focuses on developing new methods in multi-agent systems and machine learning, including methods for participatory design of AI, human-AI collaboration, and uncertainty quantification, to develop safe, impactful AI systems, particularly in the domains of water conservation and reproductive health.
Cite
Text
Bondi-Kelly. "Realizing AI for Impact: Towards Participatory Human-AI Collaboration for Water Conservation and Reproductive Health." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I27.35097Markdown
[Bondi-Kelly. "Realizing AI for Impact: Towards Participatory Human-AI Collaboration for Water Conservation and Reproductive Health." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/bondikelly2025aaai-realizing/) doi:10.1609/AAAI.V39I27.35097BibTeX
@inproceedings{bondikelly2025aaai-realizing,
title = {{Realizing AI for Impact: Towards Participatory Human-AI Collaboration for Water Conservation and Reproductive Health}},
author = {Bondi-Kelly, Elizabeth},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2025},
pages = {28701},
doi = {10.1609/AAAI.V39I27.35097},
url = {https://mlanthology.org/aaai/2025/bondikelly2025aaai-realizing/}
}