Human-AI Co-Creation Approach to Find Forever Chemicals Replacements
Abstract
Generative models are a powerful tool in AI for material discovery. We are designing a software framework that supports a human-AI co-creation process to accelerate finding replacements for the ``forever chemicals''-- chemicals that enable our modern lives, but are harmful to the environment and the human health. Our approach combines AI capabilities with the domain-specific tacit knowledge of subject matter experts to accelerate the material discovery. Our co-creation process starts with the interaction between the subject matter experts and a generative model that can generate new molecule designs. In this position paper, we discuss our hypothesis that these subject matter experts can benefit from a more iterative interaction with the generative model, asking for smaller samples and ``guiding'' the exploration of the discovery space with their knowledge.
Cite
@article{arxiv.2304.05389,
title = {Human-AI Co-Creation Approach to Find Forever Chemicals Replacements},
author = {Juliana Jansen Ferreira and Vinícius Segura and Joana G. R. Souza and Gabriel D. J. Barbosa and João Gallas and Renato Cerqueira and Dmitry Zubarev},
journal= {arXiv preprint arXiv:2304.05389},
year = {2023}
}
Comments
5 pages, Generative AI and HCI (GenAICHI) Workshop at CHI 23 (ACM CHI Conference on Human Factors in Computing Systems)