If LLMs Have Human-Like Attributes, Then So Does Age of Empires II
Adrian de Wynter
Why It Matters
What makes this one worth your time
This paper encourages a more rigorous and empirical approach to evaluating claims of human-like attributes in AI models, which could lead to more grounded AI research and development.
The paper challenges the uniqueness of anthropomorphic attributes in LLMs by comparing them to other substrates like Age of Empires II.
Summary
The paper critiques the attribution of human-like qualities to large language models by comparing them to entities in other substrates, such as the videogame Age of Empires II, and proposes a 'null' assumption for evaluating these attributes.
Key contributions
- Critique of anthropomorphic attributions in AI research.
- Proposal of a 'null' assumption for AI attribute evaluation.
Notable insights
- The concept of anthropomorphic attributes in AI may not be unique to LLMs and can be observed in other complex systems.
- Proposes a 'null' assumption to avoid circular reasoning in evaluating AI attributes.
Possible limitations
- Not stated in the abstract
Abstract
arXiv:2605.31514v2 Announce Type: replace-cross Abstract: Much research has been carried out on large language models (LLMs) and LLM-powered agentic workflows. However, many works within the field state emergence of, ascribe to, or assume, generalised anthropomorphic attributes to them (e.g., morality or understanding of natural language). Our goal is not to argue in favour or against the existence of these attributes, but to point out that these conclusions could be incorrect. For this we build and train a simple neural network on the videogame Age of Empires II, and note that any entity in a sufficiently-powerful substrate, such as LEGO or the Greater Boston Area, could also present such attributes. Hence, the purported anthropomorphic attributes of LLMs are empirically non-unique: although some properties (e.g., responses to prompts) could remain constant, others, such as the interpretation of their perceived behaviour, might change with the substrate. Thus, any empirically-grounded discussion requires explicit measurement criteria; otherwise the interpretation is left to the representation. We then show that assuming that these attributes exist or not in a system, independent of the substrate and in a generalised way, leads to either circular or uninformative conclusions, regardless of the experimenter's viewpoint on the subject. Finally we propose a 'null' assumption, where one assumes LLM non-uniqueness instead of assuming anthropomorphic attributes to set up an experiment, along with examples of it. We also discuss potential objections to our work, briefly survey the field, and prove that Age of Empires II is functionally- and Turing-complete.