Computed compatibility: examining user perceptions of AI and matchmaking algorithms

Aditi Paul and Saifuddin Ahmed

Behaviour and Information Technology, 2024, vol. 43, issue 5, 1002-1015

Abstract: Artificial intelligence (AI) driven matchmaking algorithms are at the core of modern-day dating. Millions of users rely on these algorithms used by online dating platforms for successful matchmaking. However, a scholarly understanding of user perceptions of AI-driven matchmaking algorithms is limited. We explore the factors affecting users’ perceived effectiveness of matchmaking algorithms and analyze how users’ perception of AI’s fairness, social presence, and the threat posed by AI are associated with their perceived effectiveness of matchmaking algorithms. We also investigate if their previous relationship initiation experience through online dating platforms further moderates the studied relationships. An analysis of survey data from Singapore suggests that those who perceive AI to be fair and have higher levels of social presence are more likely to showcase a higher degree of perceived effectiveness of matchmaking algorithms. Moreover, those who have previously been successful in online dating relationship initiation are also more likely to believe in the perceived effectiveness of these algorithms. Further, previous experience of relationship initiation conditionally impacts the relationship between users’ general AI perceptions and perceived effectiveness. We also find that males and younger respondents are more likely to believe in the efficacy of matchmaking algorithms. Practical implications are offered.Highlights Perceived fairness of AI is positively associated with the perceived effectiveness of matchmaking algorithms.Perceived social presence of AI is positively associated with the perceived effectiveness of matchmaking algorithms.Successful relationship initiation through online dating platforms is positively related to the perceived effectiveness of matchmaking algorithms.Relationship initiation conditionally impacts the association between perceptions of AI and the perceived effectiveness of matchmaking algorithms.Contextual transference of AI perceptions and impact of users’ experience on the perceived effectiveness of matchmaking algorithms are discussed.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/0144929X.2023.2196579 (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:taf:tbitxx:v:43:y:2024:i:5:p:1002-1015

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tbit20

DOI: 10.1080/0144929X.2023.2196579

Access Statistics for this article

Behaviour and Information Technology is currently edited by Dr Panos P Markopoulos

More articles in Behaviour and Information Technology from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().