Adopting robot lawyer? The extending artificial intelligence robot lawyer technology acceptance model for legal industry by an exploratory study
Ni Xu and
Kung-Jeng Wang
Journal of Management & Organization, 2021, vol. 27, issue 5, 867-885
Abstract:
The development of artificial intelligence has created new opportunities and challenges in industries. The competition between robots and humans has elicited extensive attention among legal researchers. In this exploratory study, we addressed issues regarding the introduction of robots to the practice of legal service through a semistructured interviews with lawyers, judges, artificial intelligence experts, and potential clients. An extended robot lawyer technology acceptance model with five facets and 11 elements is proposed in this study. This model highlights two dimensions: ‘legal use’ and ‘perception of trust.’ In summary, this study provides new specific implications and exhibits three characteristics, namely, derivative, macroscopic, and instructive, in the legal services with artificial intelligence. In addition, artificial intelligence robot lawyers are being developed with some of the abilities necessary to substitute for human beings. Nevertheless, working with human lawyers is imperative to produce benefits from this type of reciprocity.
Date: 2021
References: Add references at CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
https://www.cambridge.org/core/product/identifier/ ... type/journal_article link to article abstract page (text/html)
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:cup:jomorg:v:27:y:2021:i:5:p:867-885_4
Access Statistics for this article
More articles in Journal of Management & Organization from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Kirk Stebbing ().