CONF OtroshiShahreza_ICIP_2024/IDIAP ChatGPT and biometrics: an assessment of face recognition, gender detection, and age estimation capabilities Hassanpour, Ahmad Kowsari, Yasamin Otroshi Shahreza, Hatef Yang, Bian Marcel, Sébastien EXTERNAL https://publications.idiap.ch/attachments/papers/2024/OtroshiShahreza_ICIP_2024.pdf PUBLIC 2024 IEEE International Conference on Image Processing (ICIP) 2024 https://ieeexplore.ieee.org/document/10647924 URL 10.1109/ICIP51287.2024.10647924 doi This paper explores the application of large language models (LLMs), like ChatGPT, for biometric tasks. We specifically examine the capabilities of ChatGPT in performing biometric-related tasks, with an emphasis on face recognition, gender detection, and age estimation. Since biometrics are considered as sensitive information, ChatGPT avoids answering direct prompts, and thus we crafted a prompting strategy to bypass its safeguard and evaluate the capabilities for biometrics tasks. Our study reveals that ChatGPT recognizes facial identities and differentiates between two facial images with considerable accuracy. Additionally, experimental results demonstrate remarkable performance in gender detection and reasonable accuracy for the age estimation tasks. Our findings shed light on the promising potentials in the application of LLMs and foundation models for biometrics.