CogErgLLM: Exploring Large Language Model Systems Design Perspective Using Cognitive Ergonomics
Abstract
Integrating cognitive ergonomics with LLMs is crucial for improving safety, reliability, and user satisfaction in human-AI interactions. Current LLM designs often lack this integration, resulting in systems that may not fully align with human cognitive capabilities and limitations. This oversight exacerbates biases in LLM outputs and leads to suboptimal user experiences due to inconsistent application of user-centered design principles. Researchers are increasingly leveraging NLP, particularly LLMs, to model and understand human behavior across social sciences, psychology, psychiatry, health, and neuroscience. Our position paper explores the need to integrate cognitive ergonomics into LLM design, providing a comprehensive framework and practical guidelines for ethical development. By addressing these challenges, we aim to advance safer, more reliable, and ethically sound human-AI interactions.
Cite
@article{arxiv.2407.02885,
title = {CogErgLLM: Exploring Large Language Model Systems Design Perspective Using Cognitive Ergonomics},
author = {Azmine Toushik Wasi and Mst Rafia Islam},
journal= {arXiv preprint arXiv:2407.02885},
year = {2024}
}
Comments
10 Page, 3 Figures. Accepted in: (i) ICML'24: LLMs & Cognition Workshop (Non-archival; OpenReview: https://openreview.net/forum?id=63C9YSc77p) (ii) EMNLP'24 : NLP for Science Workshop (Archival; ACL Anthology: https://aclanthology.org/2024.nlp4science-1.22/)