Exploring Augmentation and Cognitive Strategies for AI based Synthetic Personae
<|reference_start|>Exploring Augmentation and Cognitive Strategies for AI based Synthetic Personae: Large language models (LLMs) hold potential for innovative HCI research, including the creation of synthetic personae. However, their black-box nature and propensity for hallucinations pose challenges. To address these limitations, this position paper advocates for using LLMs as data augmentation systems rather than zero-shot generators. We further propose the development of robust cognitive and memory frameworks to guide LLM responses. Initial explorations suggest that data enrichment, episodic memory, and self-reflection techniques can improve the reliability of synthetic personae and open up new avenues for HCI research.<|reference_end|>
@article{gonzalez2024exploring,
    title={Exploring Augmentation and Cognitive Strategies for AI based Synthetic
  Personae},
    author={Rafael Arias Gonzalez, Steve DiPaola},
    journal={arXiv preprint arXiv:2404.10890},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.10890},
    primaryClass={cs.AI cs.HC cs.IR}
}