Cited by 2

The DOI matches its Crossref record.

Employment Discrimination by Algorithm: Can Anyone Be Held Accountable?

Sheard, Natalie·2022·University of New South Wales Law Journal

Abstract

Accountable? Author Natalie Sheard The use by employers of Algorithmic Hiring Systems (‘AHSs’) to automate or assist with recruitment decisions is occurring in Australia without legal oversight. Regulators are yet to undertake an analysis of the legal issues posed by their use. Academic literature on this topic is limited and judicial guidance is yet to be provided. This article examines to what extent, if at all, Australian anti- discrimination laws are able to regulate the use by employers of discriminatory AHSs. First, it examines the re-emergence of blatant discrimination by digital job advertising systems. Second, it considers who, if anyone, is liable for automated discrimination. Third, it examines the law’s ability to regulate ‘proxy’ discrimination. Finally, it explores whether indirect discrimination provisions can provide redress for the disparate impact of an AHS. Australia’s anti-discrimination laws are long overdue for reform. This article concludes that new legislative provisions, as well as non- binding guidelines, specifically tailored to the use by employers of algorithmic decision systems are needed.

Overview

Integrity signals

Registry

Crossref · 10.53637/xtqy4027

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cited by

Metadata

Authors
Sheard, N.
Venue
University of New South Wales Law Journal
Published
2022-07
Volume
45
Issue
2
ISSN
0313-0096
Cited by
2
References
0

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review