EconPapers    
Economics at your fingertips  
 

Artificial intelligence and access to justice at the ‘shop front’: the potential and limitations of meeting legal need through technology

Catherine Hastings, Art Cotterell and Farzana Bruce

No p59yh_v1, SocArXiv from Center for Open Science

Abstract: In Australia, governments fund Community Legal Centres (CLCs) as part of the legal assistance sector (LAS) to meet the ‘legal needs’ of people experiencing disadvantage who cannot afford private legal services. Persistent unmet demand for CLCs is well-documented. To increase access to justice, the sector has been a long-time adopter of once-revolutionary innovations, like video conferencing. As artificial intelligence (AI) is increasingly used in private legal practice to increase productivity and profits, some parts of the LAS are also exploring AI use cases. This article asks: What do we know about CLC clients and how services are currently delivered to meet their needs? What must we consider about client capabilities to ensure AI technologies are appropriate in the context of CLC service delivery? The research includes a review of policy documents, peer-reviewed research and grey literature, and secondary analysis of empirical data on how client capabilities contribute to the legal needs of CLC clients. We show in the article that the three-dimensional nature of legal need, a client’s capability and ability to self-assist, structural inequalities and current CLC service delivery models are vital considerations when developing AI tools to increase access to justice.

Date: 2026-02-21
New Economics Papers: this item is included in nep-ict and nep-law
References: Add references at CitEc
Citations:

Downloads: (external link)
https://osf.io/download/699914eb759d4a6b6c259ff8/

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:osf:socarx:p59yh_v1

DOI: 10.31219/osf.io/p59yh_v1

Access Statistics for this paper

More papers in SocArXiv from Center for Open Science
Bibliographic data for series maintained by OSF ().

 
Page updated 2026-03-20
Handle: RePEc:osf:socarx:p59yh_v1