• Computer Science > Artificial Intelligence [Submitted on 25 Feb 2026] Title:Language Models Exhibit Inconsistent Biases Towards Algorithmic Agents and Human Experts View PDF HTML (experimental)Abstract:Large language models are increasingly used in decision-making tasks that require them to process information from a variety of sources, including both human experts and other algorithmic agents • How do LLMs weigh the information provided by these different sources • We consider the well-studied phenomenon of algorithm aversion, in which human decision-makers exhibit bias against predictions from algorithms • Drawing upon experimental paradigms from behavioural economics, we evaluate how eightdifferent LLMs delegate decision-making tasks when the delegatee is framed as a human expert or an algorithmic agent • To be inclusive of different evaluation formats, we conduct our study with two task presentations: stated preferences, modeled through direct queries about trust towards either agent, and revealed preferences, modeled through providing in-context examples of the performance of both agents • When prompted to rate the trustworthiness of human experts and algorithms across diverse task

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  • Computer Science > Artificial Intelligence [Submitted on 25 Feb 2026] Title:Language Models Exhibit Inconsistent Biases Towards Algorithmic Agents and Human Experts View PDF HTML (experimental)Abstract:Large language models are increasingly used in decision-making tasks that require them to process information from a variety of sources, including both human experts and other algorithmic agents. How do LLMs weigh the information provided by these different sources? We consider the well-studied phenomenon of algorithm aversion, in which human decision-makers exhibit bias against predictions from

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