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AI models predict consumer tech ownership using attribute analysis

Researchers have developed a method to predict consumer technology ownership by analyzing perceived attributes of these technologies. They tested this approach using survey data from US adults and ratings from two large language models, Anthropic Claude Opus 4.7 and OpenAI GPT-5.5. The study found that the language models, particularly Claude Opus 4.7, could predict ownership prevalence more effectively than a baseline of years since launch, though the models' ratings might reflect existing knowledge rather than independent reasoning. AI

IMPACT This research could enable more accurate forecasting of new technology adoption by leveraging AI's ability to analyze product attributes.

RANK_REASON Academic paper detailing a new methodology and experimental results. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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AI models predict consumer tech ownership using attribute analysis

COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Irina Vartanova, Niels Selling, Jennifer Viberg Johansson, Pontus Strimling ·

    Predicting consumer-technology ownership without a diffusion history

    arXiv:2608.12344v1 Announce Type: new Abstract: We test whether the perceived attributes of a consumer technology predict how widely it is owned. In a 2022 Prolific survey of US adults (n = 678), respondents rated 65 consumer technologies on six attributes. We then elicited the s…