Abstract
Values or principles are key elements of human society that influence people to behave and function according to an accepted standard set of social rules to maintain social order. As AI systems are becoming ubiquitous in human society, it is a major concern that they could violate these norms or values and potentially cause harm. Thus, to prevent intentional or unintentional harm, AI systems are expected to take actions that align with these principles. Training systems to exhibit this type of behavior is difficult and often requires a specialized dataset. This work presents a multi-modal dataset illustrating normative and non-normative behavior in real-life situations described through natural language and artistic images. This training set contains curated sets of images that are designed to teach young children about social principles. We argue that this is an ideal dataset to use for training socially normative agents given this fact.
Original language | English |
---|---|
Title of host publication | Proceedings - 2024 International Conference on Machine Learning and Applications, ICMLA 2024 |
Editors | M. Arif Wani, Plamen Angelov, Feng Luo, Mitsunori Ogihara, Xintao Wu, Radu-Emil Precup, Ramin Ramezani, Xiaowei Gu |
Pages | 677-684 |
Number of pages | 8 |
ISBN (Electronic) | 9798350374889 |
DOIs | |
State | Published - 2024 |
Event | 23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024 - Miami, United States Duration: Dec 18 2024 → Dec 20 2024 |
Publication series
Name | Proceedings - 2024 International Conference on Machine Learning and Applications, ICMLA 2024 |
---|
Conference
Conference | 23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024 |
---|---|
Country/Territory | United States |
City | Miami |
Period | 12/18/24 → 12/20/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- Machine Ethics
- Machine Learning
- Natural Language Processing
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Computer Vision and Pattern Recognition
- Modeling and Simulation