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Nostalgia encourages exploration and fosters uncertainty in response to AI technology.

  • Published In: British Journal of Social Psychology, 2025, v. 64, n. 1. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Dang, Jianning; Sedikides, Constantine; Wildschut, Tim; Liu, Li 3 of 3

Abstract

The burgeoning progress of cutting‐edge technology paradoxically evokes nostalgia. How does this emotion influence responses to innovative technology, such as Artificial Intelligence (AI)? We hypothesized that two pathways operate concurrently. First, by enhancing connection with significant others, nostalgia constitutes a psychological resource that supports exploration of technological innovation, thereby promoting positive responses to AI. Second, by reinforcing scepticism toward change, nostalgia heightens uncertainty about innovative technology, thereby fostering negative responses to AI. Three preregistered experiments, testing participants (ΣN = 1397) across cultures (China, UK, USA), supported the two pathways. Nostalgia influenced responses to ChatGPT via two opposing serial pathways (Experiment 1). Further, social connectedness bolstered favourable responses to AI avatars via increased technology exploration (Experiment 2), whereas scepticism about change reduced favourable responses to companion robots via increased technology uncertainty (Experiment 3). This dualistic role of nostalgia can be harnessed to sustain new technology or instill caution for its risks. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:British Journal of Social Psychology. 2025/01, Vol. 64, Issue 1, p1
  • Document Type:Article
  • Subject Area:Technology
  • Publication Date:2025
  • ISSN:0144-6665
  • DOI:10.1111/bjso.12843
  • Accession Number:183985279
  • Copyright Statement:Copyright of British Journal of Social Psychology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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