Personality of AI
December 03, 2023 Β· Declared Dead Β· π International Conference on Artificial Intelligence and Soft Computing
"No code URL or promise found in abstract"
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Authors
Byunggu Yu, Junwhan Kim
arXiv ID
2312.02998
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI
Citations
2
Venue
International Conference on Artificial Intelligence and Soft Computing
Last Checked
4 months ago
Abstract
This research paper delves into the evolving landscape of fine-tuning large language models (LLMs) to align with human users, extending beyond basic alignment to propose "personality alignment" for language models in organizational settings. Acknowledging the impact of training methods on the formation of undefined personality traits in AI models, the study draws parallels with human fitting processes using personality tests. Through an original case study, we demonstrate the necessity of personality fine-tuning for AIs and raise intriguing questions about applying human-designed tests to AIs, engineering specialized AI personality tests, and shaping AI personalities to suit organizational roles. The paper serves as a starting point for discussions and developments in the burgeoning field of AI personality alignment, offering a foundational anchor for future exploration in human-machine teaming and co-existence.
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