Social harm in the Australian gig economy: an approach to determine accountability of gig companies and their algorithms for harming gig workers

Author: Elvio Sinopoli

  • Thesis download: available for open access on 23 Oct 2025.

Sinopoli, Elvio, 2023 Social harm in the Australian gig economy: an approach to determine accountability of gig companies and their algorithms for harming gig workers, Flinders University, College of Business, Government and Law

Terms of Use: This electronic version is (or will be) made publicly available by Flinders University in accordance with its open access policy for student theses. Copyright in this thesis remains with the author. You may use this material for uses permitted under the Copyright Act 1968. If you are the owner of any included third party copyright material and/or you believe that any material has been made available without permission of the copyright owner please contact with the details.


The Australian gig economy is causing complex levels of damage to vulnerable workers, who experience harms including underpayment, road accidents and mental distress from their based work. The current labour classification of gig workers as independent contractors shifts all costs and liabilities of the gig work from the gig company to these labourers, who often belong to the most vulnerable categories of workers in Australia. Labour and criminal laws and legal cases are yet to provide a set of protections for gig workers and struggle to find a balance between autonomy and algorithmic control to determine an employment relationship and offer a set of already existing legal protections against these harms. The thesis proposes an alternative to the current insufficient laws and cases using zemiology—a branch of criminology—and two zemiological approaches: principles drawn from ultra-realism and technology harm. Under zemiology, damages in the gig economy are considered forms of ‘social harm’, which are proximate and serious impediments to workers’ autonomy, and systematically affect vulnerable gig workers as a social cohort. There are two categories of social harm in the gig economy that this thesis identifies: gig company harm and algorithmic harm. Gig company harms can be financial, physical, psychological, legal and other forms of harm caused directly by gig companies. Through selected ultra-realist principles used in the thesis, gig companies use their ‘special liberty’ from the independent contracting model and the ‘pseudo-pacification process’, intended as harming without exercising violence through market control, to cause social harm to gig workers. Gig companies generate a relationship of harm by creating a system of unilateral terms and conditions through their Guidelines containing an absence of moral responsibility and contractual stability towards gig workers to accumulate income and at the same time dispossessing working rights to prevent them to exercise their autonomy. Algorithmic harms are unintentional effects of the algorithm, defined as a ‘tool of harm’. Through the ‘technology harm’ approach, and specifically the ‘stratigraphy of harm’, algorithmic harm emerges when the gig workers are forced to use the algorithm to perform work. This triggers ‘unintentional generative utility harms’ (bugs or glitches in the platform), ‘intentional generative utility harms’ (algorithmic changes and preferences) or ‘instrumental technicity harms’, (non-systemic job allocation or unfair account deactivation), which cause a range of financial, physical and psychological harms that gig workers cannot avoid because they lack the autonomy to challenge the algorithm’s decisions. The harmful relationship between the algorithm and the gig worker is determined by the interface of the app, called ‘interface harm’, which is a form of ‘use harm’ where the gig worker is directly but unintentionally harmed by the algorithm when used, which causes either immediate, long-term, physical or psychological harm.

Keywords: gig economy, zemiology, social harm, technology harm, Australia, gig companies, algorithms

Subject: Business thesis

Thesis type: Doctor of Philosophy
Completed: 2023
School: College of Business, Government and Law
Supervisor: Associate Professor Marinella Marmo