Asymmetric impacts of artificial intelligence on housing price valuation across education levels

Sihyun An, Yena Song, Hanwool Jang and Kwangwon Ahn ()
Additional contact information
Sihyun An: Hankuk University of Foreign Studies
Yena Song: Chonnam National University
Hanwool Jang: Glasgow Caledonian University
Kwangwon Ahn: Yonsei University

Humanities and Social Sciences Communications, 2025, vol. 12, issue 1, 1-16

Abstract: Abstract This study examines the scenarios under which asymmetric estimations can arise from employing artificial intelligence (AI) models to assess housing prices. Advances in the pricing instrument effectively tackle the inherent nonlinearity issue in relevant datasets, and AI technologies have demonstrated superior predictive power compared with traditional approaches. However, AI models may penalize minority groups against the majority in a social manner. We empirically explore the potential negative externalities, specifically the asymmetric estimations that can arise across social groups when using machine learning technology to assess housing prices. Our findings highlight three notable observations. First, education levels are significantly and positively associated with housing prices. Second, AI models can appraise housing prices more precisely compared with conventional hedonic models. Finally, AI models tend to overestimate the housing prices of well-educated groups and underestimate those of less-educated groups. These results indicate that AI models improve the predictive power of price assessments; however, indiscriminate adoption and application of AI-based predictions may aggravate social inequality. Our findings provide insights into ways to alleviate inequality in urban areas; thus, policymakers can refer to our empirical evidence when designing initiatives to enhance social inclusion and coherence, and when considering strategies to realize balanced urban development.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1057/s41599-025-06153-4 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:palcom:v:12:y:2025:i:1:d:10.1057_s41599-025-06153-4

Ordering information: This journal article can be ordered from
https://www.nature.com/palcomms/about

DOI: 10.1057/s41599-025-06153-4

Access Statistics for this article

More articles in Humanities and Social Sciences Communications from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().