From "AI" to Probabilistic Automation: How Does Anthropomorphization of Technical Systems Descriptions Influence Trust?

TL;DR

The paper investigates whether anthropomorphizing descriptions of probabilistic automation affects trust. Using a randomized survey design with eight product genres and four language-categorization schemes, it finds no overall increase in trust from anthropomorphized descriptions; however, product genre and specific language categories can modulate trust in particular pairs, and age emerges as a demographic correlate. Methodologically, the work defines four anthropomorphization classes via FrameNet-based cues, employs both personal and general trust measures, and analyzes results with Chi-squared tests alongside thematic analysis of open responses. The findings suggest that anthropomorphism in AI descriptions is context-dependent and not a universal driver of trust or over-reliance, motivating more nuanced taxonomies and careful communication in AI discourse. The study contributes to policy and journalistic practices by showing when anthropomorphic language may mislead or misinform and highlights the importance of audience demographics in shaping trust responses.

Abstract

This paper investigates the influence of anthropomorphized descriptions of so-called "AI" (artificial intelligence) systems on people's self-assessment of trust in the system. Building on prior work, we define four categories of anthropomorphization (1. Properties of a cognizer, 2. Agency, 3. Biological metaphors, and 4. Properties of a communicator). We use a survey-based approach (n=954) to investigate whether participants are likely to trust one of two (fictitious) "AI" systems by randomly assigning people to see either an anthropomorphized or a de-anthropomorphized description of the systems. We find that participants are no more likely to trust anthropomorphized over de-anthropmorphized product descriptions overall. The type of product or system in combination with different anthropomorphic categories appears to exert greater influence on trust than anthropomorphizing language alone, and age is the only demographic factor that significantly correlates with people's preference for anthropomorphized or de-anthropomorphized descriptions. When elaborating on their choices, participants highlight factors such as lesser of two evils, lower or higher stakes contexts, and human favoritism as driving motivations when choosing between product A and B, irrespective of whether they saw an anthropomorphized or a de-anthropomorphized description of the product. Our results suggest that "anthropomorphism" in "AI" descriptions is an aggregate concept that may influence different groups differently, and provide nuance to the discussion of whether anthropomorphization leads to higher trust and over-reliance by the general public in systems sold as "AI".

Figures (3)

• Figure 1: A screenshot of one page of the survey as it was presented to participants. Each product pair was presented on a separate page together with the open text option to elaborate.
• Figure 2: Overview of countries of residence of participants. Note, that these numbers do not equal the full amount of participants, since this was an open-text-question, and not all participants provided a (useful) answer.
• Figure 3: Overview of countries of residence of participants. Note, that these numbers do not equal the full amount of participants, since this was an open-text-question, and not all participants provided a (useful) answer.