Cited by 0Digitalization, Law, and RegulationEthics and Social Impacts of AIArtificial Intelligence in Law

The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index; 1 of the 33 sources its claims cite were checked for support.

Retrofitters, pragmatists, and activists: public interest litigation for accountable automated decision-making

Open access
Fraser, Henry Leopold, Stardust, Zahra·2026·Law & Society Review

Abstract

This paper examines the role of public interest litigation in promoting accountability for AI and automated decision-making (ADM) in Australia. Since ADM regulation faces political and geopolitical headwinds, effective governance will have to rely on the enforcement of existing laws. Drawing on interviews with Australian public interest litigators, technology policy activists, and technology law scholars, the paper positions public interest litigation as part of a larger ecosystem for transparency, accountability, and justice with respect to ADM. The paper explores the tactics and strategies of what one participant described as “retrofitting” old laws to ADM. These go beyond creative legal argumentation to encompass practices of community-building, collaboration on theories of change, canny selection of clients and causes of action, and careful alignment of the interests of stakeholders in litigation. Naturally, the paper also contends with the limits of these strategies, and of the Australian legal system. Where limits are, however, capable of being overcome, the paper presents findings on urgent needs: the enabling institutional arrangements without which effective litigation and accountability will falter. The paper is relevant to law and technology scholars; individuals and groups harmed by ADM; public interest litigators and technology lawyers; civil society and advocacy organizations; and policymakers.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This qualitative interview study argues that public interest litigation is one pragmatic tool in a broader Australian ecosystem for holding automated decision-making accountable, especially by retrofitting existing laws to new harms. It documents strategies, enablers, and limits, concluding that transparency, funding, and networks are necessary for effective litigation while systemic and collective harms remain hard to remedy.

Key findings

  • Participants saw public interest litigation as part of a larger accountability ecosystem, not a sole solution; it can assert or develop law, prompt law reform, galvanise public opinion, and support advocacy. The Robodebt class action settled with the government agreeing to repay over $751 million and withdraw over $1 billion worth of improperly issued debt notices.
  • Pragmatic tactics included “retrofitting” old causes of action to ADM harms, choosing doctrines with monetary remedies (e.g., negligence, breach of confidence, unjust enrichment), adding “bolt-ons” such as public interest arguments or amicus briefs to private suits, and aligning litigant, funder, and firm incentives.
  • Enablers identified were transparency across the accountability lifecycle, information-aggregating mechanisms such as complaint systems, networks for referrals and theory development, and funding/adverse-costs reform, including possible protective costs orders.
  • Limits included law’s better fit for individualised harms with damages than collective, systemic, or intangible harms; discrimination law’s intent-based model, low damages, and uncertainty; access burdens and adverse costs; and risks of entrenching structural harms or settling away systemic issues.

Methods

  • Applied social research in an action-research spirit, recruiting 20 participants with experience in public interest litigation, advocacy, technology law, and policy, including barristers, solicitors, policy advisors, academics, and consumer advocates from public and private institutions.
  • Recruitment began through authors’ networks and continued via snowball sampling; data came from recorded one-hour semi-structured interviews, with participants able to review and edit transcripts for clarity and confidentiality.
  • Analysis used qualitative thematic analysis (Braun and Clarke) with iterative file notes and memos, coding around challenges, opportunities, barriers, and enablers; ethics approval was obtained from Queensland University of Technology’s faculty low-risk ethics review panel.

Limitations

  • Stated in the paper: interviews took place before the late 2024 Privacy Act reforms and before the proposed “mandatory guardrails” for high-risk AI; the study focuses on Australia; and the authors foreshadow forthcoming work on systemic automated harms and related concerns.
  • Evident from the text: the qualitative sample of 20 participants, recruited through authors’ networks and snowball sampling, is not representative or generalisable, and the paper does not quantitatively measure litigation outcomes.
  • Evident from the text: participant views are time-bound and jurisdiction-specific, and the paper relies on illustrative cases rather than a systematic evaluation of ADM litigation outcomes.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1017/lsr.2026.10124

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

74 Own interpretation · 43 Own result · 27 No basis given · 17 Sources not found · 14 Not checked yet · 4 No full text of the sources · 1 Partly supported · 1 Own method · accuracy not yet measured

Show all 54 claims

  • Probably not a substantial claim. 114
  • It may state two separate claims as one. 34
127 of 127
  • The paper relies on this without support.

    The views and experiences of the twenty interviewed participants are sufficiently representative of the Australian public interest litigation, advocacy, and technology law community to support general conclusions about strategies and enablers for ADM accountability.

    “we recruited and interviewed twenty candidates with experience in public interest litigation, advocacy, technology law and policy.”
  • The paper relies on this without support.

    Participants' accounts of past cases and their outcomes are accurate.

    “She described the outcome in these terms:”
  • The paper relies on this without support.

    Costs are the most well-known barrier to effective public interest litigation.

    “Costs are the most well-known barrier to effective public interest litigation.”
  • The paper relies on this without support.

    Lead plaintiffs in class actions are solely liable for adverse cost orders, whereas any proceeds of the case are shared with the whole class.

    “One serious problem is the fact that lead plaintiffs in class actions are solely liable for adverse cost orders (whereas any proceeds of the case are shared with the whole class).”
  • The paper relies on this without support.

    Public interest litigation is a last resort to address harm that has already occurred.

    “Public interest litigation is a last resort to address harm that has already occurred.”
  • The paper relies on this without support.

    The mandatory guardrails proposal stalled before any Bill reached Parliament.

    “Unfortunately the proposal stalled before any Bill reached Parliament.”
6 of 6

Citations

Cites

Show all 27 references

Research works printed but not linked: 27

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Metadata

Authors
Fraser, H. L., & Stardust, Z.
Affiliations
Queensland University of Technology (AU)
Corresponding author
Fraser, Henry Leopold
Venue
Law & Society Review
Published
2026-10-22
Pages
1-32
ISSN
  • 0023-9216 (ISSN-L)
  • 1540-5893
OpenAlex
W7104289959
Cited by
0
References
27
FWCI
0.00
Type
journal article
Language
en
Open access
Locations
  • Law & Society Review (publishedVersion, cc-by)
  • arXiv (Cornell University) (submittedVersion, cc-by-nc-sa)
  • intR2Dok (Staatsbibliothek zu Berlin) (submittedVersion, cc-by)
  • arXiv (Cornell University)
Funders
  • Deakin University
  • Australian Research Council (CE200100005)
Topics
  • Social Sciences › Law › Digitalization, Law, and Regulation
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
  • Social Sciences › Law › Artificial Intelligence in Law
Keywords
public interest litigation, automated decision-making, algorithmic accountability, AI regulation, transparency, algorithmic justice, civil society advocacy, Australian legal system, law and technology

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Fraser, H. L., & Stardust, Z. (2026). Retrofitters, pragmatists, and activists: public interest litigation for accountable automated decision-making. Law & Society Review. https://doi.org/10.1017/lsr.2026.10124