@inproceedings{wasi-islam-2024-cogergllm,
    title = "{C}og{E}rg{LLM}: Exploring Large Language Model Systems Design Perspective Using Cognitive Ergonomics",
    author = "Wasi, Azmine Toushik  and
      Islam, Mst Rafia",
    editor = "Peled-Cohen, Lotem  and
      Calderon, Nitay  and
      Lissak, Shir  and
      Reichart, Roi",
    booktitle = "Proceedings of the 1st Workshop on NLP for Science (NLP4Science)",
    month = nov,
    year = "2024",
    address = "Miami, FL, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.nlp4science-1.22/",
    doi = "10.18653/v1/2024.nlp4science-1.22",
    pages = "249--258",
    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."
}