Anthropomorphization is the tendency to attribute human-like traits to non-human entities. It is prevalent in many social contexts -- children anthropomorphize toys, adults do so with brands, and it is a literary device. It is also a versatile tool in science, with behavioral psychology and evolutionary biology meticulously documenting its consequences. With widespread adoption of AI systems, and the push from stakeholders to make it human-like through alignment techniques, human voice, and pictorial avatars, the tendency for users to anthropomorphize it increases significantly. We take a dyadic approach to understanding this phenomenon with large language models (LLMs) by studying (1) the objective legal implications, as analyzed through the lens of the recent blueprint of AI bill of rights and the (2) subtle psychological aspects customization and anthropomorphization. We find that anthropomorphized LLMs customized for different user bases violate multiple provisions in the legislative blueprint. In addition, we point out that anthropomorphization of LLMs affects the influence they can have on their users, thus having the potential to fundamentally change the nature of human-AI interaction, with potential for manipulation and negative influence. With LLMs being hyper-personalized for vulnerable groups like children and patients among others, our work is a timely and important contribution. We propose a conservative strategy for the cautious use of anthropomorphization to improve trustworthiness of AI systems.

翻译：人格化是指将人类特征赋予非人类实体的倾向。这种倾向在社会情境中普遍存在——儿童会人格化玩具，成年人会对品牌进行人格化，它也是一种文学手法。在科学领域，人格化同样是重要工具，行为心理学和进化生物学已详细记录其影响后果。随着AI系统的广泛普及，以及利益相关者通过对齐技术、人声和拟人化头像推动其向人类化发展，用户将其人格化的倾向显著增强。我们采用二元视角，通过研究以下两方面来理解大型语言模型（LLMs）中这一现象：（1）从近期《AI权利法案蓝图》视角分析的法律客观影响；（2）定制化与人格化的微妙心理层面。研究发现，针对不同用户群体定制的人格化LLMs违反了该立法蓝图的多个条款。此外，我们指出LLMs的人格化会影响其对用户的影响力，从而可能从根本上改变人机交互的本质，带来操控与负面影响的潜在风险。鉴于LLMs正为儿童、患者等弱势群体提供高度个性化服务，本研究的及时性与重要性不言而喻。我们提出一种保守策略，建议审慎运用人格化以提升AI系统的可信度。