AI-assisted discovery of quantitative and formal models in social science
Abstract In social science, formal and quantitative models, ranging from ones that describe economic growth to collective action, are used to formulate mechanistic explanations of the observed phenomena, provide predictions, and uncover new research questions. Here, we demonstrate the use of a machi...
Saved in:
Main Authors: | Julia Balla, Sihao Huang, Owen Dugan, Rumen Dangovski, Marin Soljačić |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer Nature
2025-01-01
|
Series: | Humanities & Social Sciences Communications |
Online Access: | https://doi.org/10.1057/s41599-025-04405-x |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
On the role of knowledge graphs in AI-based scientific discovery
by: Mathieu d’Aquin
Published: (2025-01-01) -
Life Sciences discovery and technology highlights
by: Tal Murthy, et al.
Published: (2025-02-01) -
Responsible AI in biotechnology: balancing discovery, innovation and biosecurity risks
by: Nicole E. Wheeler
Published: (2025-02-01) -
Unlocking oral oncology: AI-powered biomarker discovery for early detection
by: S. Karishma, et al.
Published: (2024-06-01) -
AI product cards: a framework for code-bound formal documentation cards in the public administration
by: Albana Celepija, et al.
Published: (2025-01-01)