Automated informality: generative frictions in ADM systems

PROJECT SUMMARY

A seller stands next to his electronic devices outside in front of graffiti art on wall.

Automated informality: generative frictions in ADM systems

Focus Areas: News & Media
Research Program: People, Data, Machines & Institutions
Status: Active

Informality, especially in economic practice, poses a recurrent problem in development literature. Economic informality is broadly associated with weaker economic outcomes: countries with larger informal sectors have lower per capita incomes, greater poverty, less financial development, and weaker growth in output, investment, and productivity. As such regimes across the globe have sought to intervene in, and formalize the informal sector through worker registration drives, technology transfers, and other interventions which attempt to expand the reach of the formal economy bringing swaths of the working population under regimes of taxation, workplace safety, and enhanced productivity.

Recently, such interventions have turned on the possibilities and promises of automation. While industrial robotics systems boost manufacturing productivity, digital platforms make possible immediate and traceable circulation of funds, even as biometric databases enable automated identity verification in commercial and civic contexts.  Here new technologies of automation hold out the potential to formalize economic practices by extending standardized protocols in the form of apps, database architectures, and machinery.

Scholars of informal work have emphasized that informal and formal economic practices have long been intertwined, and they are connected by exchanges of personnel, ideas, content, and capital as highly contingent interactions. Especially in the Global South, the informal is not exceptional but typical with informality characterizing most economic practices. In India, for example, the rise of formal IT outsourcing firms has been matched by the growth of temporary and unregulated service workers who clean the offices, fix the meals, and provide transportation to professional employees.

In Brazil, wageless trash collectors sort recyclable items from Rio de Janeiro’s municipal waste dumps enabling the operation of this public infrastructure while extracting a livelihood from reselling this waste. Far from eliminating informal economies contemporary regimes of accumulation generate value by weaving formal and informal practices together.

Currently missing from this body of scholarship is a range of contingent and non-standard work that proliferates as a result of the friction that exists within automated systems as complex self-coordinating and self-organising mechanisms. This type of work – which we call small automation – is different from gig work in that it is unregulated, opportunistic, and marginalised; it is largely invisible and opaque, but unlike ghost work, its invisibility is key to its survival.

Small automation is different from both gig work and ghost work in the sense that it encompasses a range of informal enterprises created by informal actors that circumvent, exploit, or co-opt automated systems, rather than being deployed by Silicon Valley to develop new technologies.

This project maps a range of informal automated activities that proliferate within automated systems across various empirical domains, such as click farming, CAPTCHA hacking, phone farming, dropshipping, OTP scams, fraudulent loan apps, and free jacking. The proliferation of automated informality can create unexpected implications for the operation of automated systems and our information environment more generally. Our focus on mapping automated informality works to supplement current research on gig work and ghost work while demonstrating the theoretical and empirical value of examining automated systems in context.

RESEARCHERS

Dang Nguyen

Dr Dang Nguyen

Lead Investigator,
RMIT University

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Danula Hettiachchi

Dr Danula Hettiachchi

Associate Investigator,
RMIT University

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Rakesh Kumar

Rakesh Kumar

PhD Student,
Western Sydney University

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Adam Sargent

Dr Adam Sarget

Affiliate,
Australian National University (ANU)

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Is Pricing Discriminatory: Testing Automated Decision-Making Systems in Online Insurance Markets

PROJECT SUMMARY

man and women working on laptop together

Is Pricing Discriminatory: Testing Automated Decision-Making Systems in Online Insurance Markets

Focus Areas: News & Media, Social Services, Mobilities, Health
Research Program: Data
Status: Active

Advances in data-driven and AI systems are driving significant transformation in the emerging insurance technology (insurtech) sector.

This project investigates the extent to which automated decision-making systems impact the provision of consumer insurance via pricing algorithms which may produce unfair outcomes for particular subsets of society by engaging in proxy and price discrimination.

RESEARCHERS

Kelly Lewis

Dr Kelly Lewis

Lead Investigator,
Monash University

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Mark Andrejevic

Prof Mark Andrejevic

Chief Investigator,
Monash University

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Daniel Angus

Prof Daniel Angus

Chief Investigator,
QUT

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Kim Weatherall

Prof Kim Weatherall

Chief Investigator,
University of Sydney

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Zofia Bednarz

Dr Zofia Bednarz

Associate Investigator,
University of Sydney

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Jathan Sadowski

Dr Jathan Sadowski

Associate Investigator,
Monash University

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ADM+S professional staff Abdul Obeid

Dr Abdul Obeid

Data Engineer,
QUT

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PARTNERS

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Consumer Policy Research Centre

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Automation and Public Space

PROJECT SUMMARY

LiDAR sensing concept

Automation and Public Space

Focus Areas: News and Media, Transport and Mobility, Health, and Social Services
Research Program: Data
Status:
 Active

From delivery drones to digital twins to crowd surveillance, automated decision-making technologies and practices are increasingly impacting public and shared space. This project investigates how automated decision-making systems impact public and shared space via sensors that produce actionable digital simulations, artefacts, and interfaces. Through a mixed methods approach, it will examine current and potential effects of automated decision-making on the form, use, and experience of public space.

Technological development in this area is undergoing rapid change. Delivery via autonomous drone requires sensor-driven navigation systems, but the data and models they produce about public space will likely lead to modulations of that space in response. In urban and environmental governance, ‘digital twins’ are increasingly to monitor environments in real-time, simulate the impact of potential changes, and even implement those changes directly. Technologies such as these are not only increasingly deployed in Australia, but are also invented, designed, and tested here too, often in proximity to defence and defence industries.

Understanding how tools of automated spatiality reconfigure environments and the role of policy and industry in their innovation and uptake will generate new knowledge about a critical point of convergence between public space, technology, defence, and industry with national significance, as well as implications for international jurisdictions facing similar changes and challenges.

Over 3 years commencing in 2022, the project aims to answer the following questions:
• How is space-making automated across different technologies and contexts? What logics, techniques and practices are shared? What are distinct to different contexts?
• How does automated spatiality lead to the reconfiguring of public space?
• How are digital infrastructures, such as unmanned traffic management systems for civilian airspace, imagined, organised, and regulated?
• How do policy settings, industrial demands, and defence priorities shape the development and application of technologies of automated spatiality?

PUBLICATIONS

Andrejevic, M.

Journal article

Biometric Re-bordering: Environmental Control During Pandemic Times, 2022

Andrejevic, M., Volcic, Z.

Journal article

Seeing Like a Border, 2021

Andrejevic, M., Volcic, Z.

Journal article

RESEARCHERS

Michael Richardson

Assoc Prof Michael Richardson

Lead Investigator,
UNSW

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Mark Andrejevic

Prof Mark Andrejevic

Chief Investigator,
Monash University

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Jake Goldenfein

Dr Jake Goldenfein

Chief Investigator,
University of Melbourne

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ADM+S Chief Investigator Anthony McCosker

Prof Anthony McCosker

Chief Investigator,
Swinburne University

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Jathan Sadowski

Dr Jathan Sadowski

Associate Investigator,
Monash University

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Rowan Wilken

Assoc Prof Rowan Wilken

Associate Investigator,
RMIT University

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Zoe Horn

Zoe Horn

Student,
Western Sydney University

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Lauren Kelly

Lauren Kelly

Student,
RMIT University

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Andrew Brooks

Dr Andrew Brooks

Affiliate,
UNSW

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Danielle Hynes

Danielle Hynes

Affiliate,
UNSW

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Kelly Lewis

Dr Kelly Lewis

Affiliate,
Monash University

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Thao Phan

Dr Thao Phan

Affiliate,
ANU

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Christopher O'Neill

Dr Chris O’Neill

Affiliate,
Deakin University

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PARTNERS

OVIC Logo

Office of the Victorian Information Commissioner

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An AI governance framework for garbage truck-mounted machine vision systems

PROJECT SUMMARY

Brimbank City Council garbage truck

An AI governance framework for garbage truck-mounted machine vision systems

Focus Area: Mobilities
Research Program: Data
Status: Completed

This project addresses the ethical and social concerns associated with the use of AI systems in local government municipalities. The use of AI in decision-making offers great potential but also raises important issues such as privacy, transparency, and ethical considerations. To tackle these challenges, we propose an AI governance framework tailored specifically for local government municipalities. The framework prioritises human rights and values while weighing societal risks and benefits. It involves establishing guidelines and practices that align AI technologies with organisational values and objectives, promoting responsible AI development and deployment.

Through a collaborative design approach with Brimbank City Council in Australia, we have developed an AI governance framework. Drawing on insights from ethical and responsible AI research, we identify key AI management pillars, processes, and an action plan to guide responsible and ethical AI practices. This framework will be adaptable to the unique needs and concerns of municipalities, balancing general responsible AI principles with specific local government contexts.

The project makes several contributions. Firstly, it investigates the human, social, and ethical implications of AI usage in the context of local government. Secondly, it proposes an AI governance framework that combines responsible AI principles, management pillars, and an action plan, providing a significant step forward in AI governance. Lastly, it presents a participatory approach that facilitates the development and translation of the AI governance framework, making it a practical resource for policymakers, city planners and related stakeholders.

By adopting this framework, local governments can lead in promoting ethical AI use, building public trust, and transparency. To do so involves context-specific translational work, creating practical pathways for implementing high level ethical principles. Our framework and action plan enables responsible AI deployment across sectors, benefiting both the organisation and the community it serves.

PUBLICATIONS

AI Governance in the Smart City: A case study of garbage truck mounted machine vision for roadside maintenance, 2023

Kang, Y.B., McCosker, A., et al.

Report

RESEARCHERS

ADM+S Chief Investigator Anthony McCosker

Prof Anthony McCosker

Lead Investigator,
Swinburne University

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Yong-Bin Kang

Dr Yong-Bin Kang

Research Fellow,
Swinburne University

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Milovan Savic

Dr Milovan Savic

Research Fellow,
Swinburne University

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Yong-Bin Kang

Thomas Graham

PhD Student,
Swinburne University

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Affiliate,
University of Melbourne

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PARTNERS

Brimbank City Council

Brimbank City Council

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OVIC Logo

Office of the Victorian Information Commissioner (OVIC)

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Assessing Prospective Harms (vs Benefits) associated with ADM

PROJECT SUMMARY

Two people looking at computer screens

Assessing Prospective Harms (vs Benefits) associated with ADM

Focus Areas: News and Media, Transport and Mobility, Health, and Social Services
Research Programs: Data, Machines, Institutions
Status: 
Completed

The project (which is now completed) was set up as a preliminary exercise in assessing prospective harms vs prospective benefits associated with ADM as a first step to amelioration. It took a two-pronged approach: firstly, focusing on individual and social harms/costs that may be associated with automated or semi-automated data processing (including collection, retention, dissemination, and other uses of data) – versus prospective benefits; and secondly, assessing the levels of risk of these harms ranging from nebulous to very significant (and acknowledging there may be
uncertain outcomes and uneven distributions). The overall aim was thus to have a fuller appreciation of harms and risks as a precursor to thinking practically about amelioration/mitigation of costs.

More specifically, the project was geared to questions of elaborating and understanding the range of prospective harms associated with loss of control over data processing for individuals, groups and society, and indeed the entirety of the living world, as a first step to finding solutions such as changes in law, or social practices, or business methods, or technologies (or some combination of these).

The principal activity of the project was to have a series of workshops planned, organised and hosted by the coordinators CI Richardson, AI Roberts and Postdoc Jiménez (with administrator Astari.Kusumawardani providing support). The workshops featured the work of diverse ADM+S CIs, AIs, Researchers and Affiliates and adopted an intense mode of interrogation and discussion along with suggestions. The aim was to assist ADMS personnel with the preparation of reports, books and scholarly articles (as well as share insights and ideas).

Topics and presenters in the workshop series included the following:
•March: Aitor Jiménez (Megan Richardson chair), Crimes of digital capitalism
•March: Ariadna Matamoros- Fernández, Rosalie Gillett, Anjalee de Silva (Aitor Jiménez chair), •Gendered harm
•April: José-Miguel Bello Villarino, Henry Fraser (Megan Richardson chair), Where residual risks reside: a comparative approach to AI risk management under the EU’s AI Act Proposal
•April: Jake Goldenfein (Megan Richardsonchair) How competing constructions of humans legitimize online advertising
•May: Simon Coghlan, Christine Parker (Andy Roberts, chair), A preliminary framework for understanding how ADM/AI technologies can harm non-human animals
•June: Lisa Archbold (Andy Roberts chair), Children’s developmental privacy
•July: Frank Pasquale/Jeannie Paterson (Megan Richardson chair: co-hosted with CAIDE), Automated grace: toward more humane benefits administration via AI
•August: James Meese (Megan Richardson chair), Regulating news recommendation: looking beyond harm
•September: Megan Richardson (Jeannie Paterson chair – co-hosted with CAIDE), Trust norms and data rights
•October: Ariadna Matamoros- Fernández, Louisa Bartolo, Luke Troynar (Aitor Jiménez chair), Addressing harmful humour as an online safety issue
•November: Damian Clifford (Megan Richardson chair), Data protection and (in)accuracy

PUBLICATIONS

Harm to Nonhuman Animals from AI: a Systematic Account and Framework, 2023

Parker, C., Coghlan, S.

Journal article

Humour as an online safety issue: Exploring solutions to help platforms better address this form of expression, 2023

Matamoros-Fernández, A., Bartolo, L., Troynar, L.

Journal article

The Crimes of Digital Capitalism, 2022

Jiménez, A., Oleson, J.C.

Journal article

RESEARCHERS

ADM+S Investigator Christine Parker

Prof Christine Parker

Lead Investigator,
University of Melbourne

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Jake Goldenfein

Dr Jake Goldenfein

Chief Investigator,
University of Melbourne

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Kim Weatherall

Prof Kim Weatherall

Chief Investigator,
University of Sydney

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Zofia Bednarz

Dr Zofia Bednarz

Associate Investigator,
University of Sydney

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Simon Coghlan

Dr Simon Coghlan

Associate Investigator,
University of Melbourne

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ADM+S Chief Investigator Andrew Kenyon

Prof Andrew Kenyon

Associate Investigator,
University of Melbourne

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Ariadna Matamoros Fernandez profile picture

Dr Ariadna Matamoros-Fernández

Associate Investigator,
QUT

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James Meese

Dr James Meese

Associate Investigator,
RMIT University

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Andrew Roberts

Prof Andrew Roberts

Associate Investigator,
University of Melbourne

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ADM+S Investigator Ivana Jurko

Ivana Jurko

Partner Investigator,
Red Cross Australia

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José-Miguel Bello y Villarino

Dr José-Miguel Bello Villarino

Research Fellow,
University of Sydney

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Anjalee de Silva

Dr Anjalee de Silva

Research Fellow,
University of Melbourne

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Henry Fraser

Dr Henry Fraser

Research Fellow,
QUT

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Dr Rosalie Gillett profile picture

Dr Rosalie Gillett

Research Fellow,
QUT

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Damian Clifford

Dr Damian Clifford

Affiliate,
ANU

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ADM+S Investigator Fiona Haines

Prof Fiona Haines

Affiliate,
University of Melbourne

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Aitor Jiménez

Dr Aitor Jiménez

Affiliate,
University of Melbourne

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Kobi Leins

Dr Kobi Leins

Affiliate,
King’s College

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Jeannie Paterson

Prof Jeannie Paterson

Affiliate,
University of Melbourne

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Affiliate,
University of Melbourne

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PARTNERS

OVIC Logo

Office of the Victorian Information Commissioner (OVIC)

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Data for Social Good: Non-profit sector data projects

PROJECT SUMMARY

Diverse group of people using digital devices

Data for Social Good: Non-profit sector data projects

Focus Area: Social Services
Research Program: Data
Status: Completed

It is widely understood that the non-profit sector is at the frontline in addressing issues of social equity and inclusion. While the sector and the communities it serves stands to benefit greatly from the turn to data and analytics, it is often under-equipped.

This project draws on a range of social good data projects with non-profit organisations, including the Building Data Capability and Collaboration project, and provides a foundational methodology for the ADM+S Centre’s goals in reconfiguring data practices for responsible, ethical and inclusive ADM. It centres on a methodology of ‘collaborative data action’ that helps to build capability and improve data governance to produce data insights and innovation.

The open access Data for Social Good: Non-Profit Sector Data Projects book and associated workshops provide non-profit CEOs, managers, practitioners and board members with feasible strategies for getting into data analytics or assessing and building their organisation’s data capability. It also informs researchers as it reflects on where practice-embedded research has arrived and provides thoughts about future research directions.

PUBLIC RESOURCES

A Data Capability Framework for the not-for-profit sector

Target audience: Not-for-profit sector

As the NFP sector undergoes digital transformation it has great opportunity to generate social value from data through its use in analysis, decision making and social innovation. Sector-wide data capability measurement and fostering data communities of practice are essential if the sector is to maximise data for social good and minimise potential harms in the fast-approaching context of a data-driven and automated society.

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Towards Resilient Communities: Data capability and resource mapping for disaster preparedness

Target audience: Disaster management organisations, Communities

Access to quality data is vital for informing decision-making before, during and after emergency events. As more data becomes available, new artificial intelligence (AI) tools such as machine learning and generative AI are extending the possibilities for data-driven disaster resilience. To work toward this outcome, the ADM+S team worked in collaboration with experienced members of Australian Red Cross to better understand the challenges and potential of data-driven decision-making for community disaster resilience.

View Framework

PUBLICATIONS

Data for Social Good - Front Cover

Data for social good: non-profit sector data projects

27 October 2022

Read on APO

RESEARCHERS

ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Lead Investigator,
Swinburne University

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Kath Albury

Prof Kath Albury

Associate Investigator,
Swinburne University

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Jane Farmer

Prof Jane Farmer

Associate Investigator,
Swinburne University

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PARTNERS & COLLABORATING ORGANISATIONS

Australian Red Cross Logo

Australian Red Cross

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Bendigo Bank

Bendigo Bank

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Victorian Government

Department of Premier and Cabinet, Victorian Government

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Entertainment Assist

Entertainment Assist

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Good Cycles

Good Cycles

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Infoxchange

Infoxchange

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Political Economy of Sex Tech

PROJECT SUMMARY

Three hearts displayed on an LED screen

Political Economy of Sex Tech

Focus Area: News & Media
Research Programs: Data, Institutions
Status: Active

Smart sex technologies and networked apps are being used in sex and relationship education, to enhance sexual wellness and to improve sexual and reproductive health. To do so, they collect and process substantial amounts of intimate data. This project examines the political economy of ‘sex tech’ in order to identify how sexual technologies are being governed at scale, how sexual data is being collected, stored, shared and monetised, and how the material benefits of sex tech may be more equitably distributed.

It will provide empirical grounding to enrich scholarship on ethical data governance, predictive profiling and accountability of smart technologies.

PUBLICATIONS

Sex tech in an age of surveillance capitalism: Design, Data and Governance, 2024

Stardust, Z.

Book chapter

Sex tech entrepreneurs: Governing intimate data in start-up culture, 2023

Stardust, Z., Kennedy, J., Albury, K

Journal article

Surveillance does not equal safety: Police, data and consent on dating apps, 2022

Stardust, Z., Gillett, R., Albury, K.

Journal article

Public interest sex tech hackathon: speculative futures and participatory design, 2022

Stardust, Z., Kennedy, J., Albury, K.

Report

RESEARCHERS

Zahra Stardust profile picture

Dr Zahra Stardust

Lead Investigator,
QUT

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ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Chief Investigator,
QUT

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Automating safety: developing better data models to help foster prosocial platforms

PROJECT SUMMARY

Blurred people crossing street

Automating safety: developing better data models to help foster prosocial platforms

Focus Area: News & Media
Research Program: Data
Status: Completed

This project identified and investigated how misunderstandings of harm and safety flow into flawed data logics and ineffective automated digital platform responses. A key output from the project included the journal article “Safety for Whom? Investigating How Platforms Frame and Perform Safety and Harm Interventions” (Gillett, Stardust, and Burgess 2023), which aimed to understand how five major digital platforms frame and define the issues of harm and safety, and identified the interventions they publicly report introducing to address these issues. Findings from this research importantly show that, in the absence of more meaningful measures that may foster safer digital cultures, at the heart of platform commitments is the scaling up of automated tools to moderate the enormous volume of content large digital platforms host.

Another key output included the journal article “Surveillance does not equal safety: Police, data and consent on dating apps” (Stardust, Gillett, and Albury, 2022). The article interrogated how dating apps focus on increasing user surveillance and other mechanisms that are deployed in the name of ‘safety’, rather than addressing the more complex questions about how their users experience and understand harm and safety, and how these understandings might better inform responses that enable users to feel safe. This paper was an extension of the article that the authors wrote for the Conversation (Gillett, Albury, Stardust, 2021).

To better understand the experiences of women online, research led by Gillett and Dr Anjalee de Silva received ADM+S seed funding for a group of the Centre’s ECRs to facilitate a Gendered online Harms Workshop. The workshop brought together a range of civil society actors and academics for whom online safety is a pressing social issue. The workshop enabled the team to better understand online harms based on users who had experienced them. Gillett and de Silva shared key findings from the research at an ADM+S Data Harms workshop. Preliminary findings were also published on the ADM+S website.

PUBLICATIONS

QUT Digital Media Research Centre submission in response to the Online Safety Bill (2021)

Prof Nicholas Suzor, Lucinda Nelson, Dr Rosalie Gillett and Prof Jean Burgess

Submission

QUT Digital Media Research Centre submission in response to the inquiry into serious vilification and hate crimes (2021)

Lucinda Nelson, Prof Nicolas Suzor, Dr Rosalie Gillett and Dr Ariadna Matamoros-Fernández

Submission

‘This is not a nice safe space’: investigating women’s safety work on Tinder (2023)

Dr Rosalie Gillett

Journal article

Safety for Whom? Investigating How Platforms Frame and Perform Safety and Harm Interventions (2022)

Prof Jean Burgess, Dr Rosalie Gillett and Dr Zahra Stardust

Journal article

‘Just a little hack’: Investigating cultures of content moderation circumvention by Facebook users (2023)

Dr Rosalie Gillett, Joanne Gray and Kaye Bondy Valdovinos

Journal article

Self-regulation and discretion (2022)

Prof Nicolas Suzor andDr Rosalie Gillett

Book chapter

Surveillance does not equal safety: Police, data and consent on dating apps (2022)

Dr Rosalie Gillett, Prof Kath Albury and Dr Zahra Stardust

Journal article

Incels on Reddit: A study in social norms and decentralised moderation (2022)

Prof Nicolas Suzor andDr Rosalie Gillett

Journal article

RESEARCHERS

Dr Rosalie Gillett profile picture

Dr Rosalie Gillett

Research Fellow,
QUT

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Lead Investigator,
QUT

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ADM+S Chief Investigator Nic Suzor

Prof Nic Suzor

Chief Investigator,
QUT

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Zahra Stardust profile picture

Dr Zahra Stardust

Research Fellow,
QUT

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Responsible health consumer data analysis and ADM

PROJECT SUMMARY

Lady sitting on coach talking to counsellor

Responsible health consumer data analysis and ADM

Focus Area: Health
Research Program: Data
Status: Completed

Health care service providers are increasingly seeking to use advanced data analytics and automated decision making to improving services and for predictive insights. By better understanding the everyday experiences of people living with mental ill-health, for example, services can improve the allocation of resources and enhance health outcomes. Accessing health consumer voices and experiences directly through social data sets (such as online health forums) can have an important impact on optimising decision making, but also raises ethical issues and data management and analysis challenges.

Drawing on cutting edge practices in text data mining and NLP analysis, this project develops a model for ethical and responsible mental health consumer data analysis. It operationalises data partnerships with the mental health organisations SANE Australia, Beyond Blue and ReachOut to explore and implement data analysis to improve mental health care, with a focus on community mental health support, and ethical, inclusive and participatory practices. The project builds on and extends work undertaken for the ARC Discovery Project (DP200100419), Optimising the roles of online communities in rural resilience, with a particular focus on data practices, analytics and ADM in digital health care services.

PUBLICATIONS

Resilience in Web-Based Mental Health Communities: Building a Resilience Dictionary With Semiautomatic Text Analysis, 2022

McCosker, A., Farmer, J., Kang, Y.B., Kamstra, P.

Research paper

A Novel Mixed Methods Approach for Integrating Not-for-Profit Service Data via Qualitative Geographic Information System to Explore Authentic Experiences of Ill-Health: A Case Study of Rural Mental Health, 2022

Kamstra, P., Farmer, J. et al.

Journal article

Moderating mental health: Addressing the human-machine alignment problem through an adaptive logic of care, 2023

McCosker, A., Farmer, J., Kamstra, P.

Journal article

Moderating Mental Health: Are Automated Systems too Risk Averse? 2023

McCosker, A.

Conference paper

RESEARCHERS

ADM+S Chief Investigator Anthony McCosker

Prof Anthony McCosker

Lead Investigator,
Swinburne University

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Daniel Angus

Prof Daniel Angus

Chief Investigator,
QUT

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Kath Albury

Prof Kath Albury

Associate Investigator,
Swinburne University

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Jane Farmer

Prof Jane Farmer

Associate Investigator,
Swinburne University

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Yong-Bin Kang

Dr Yong-Bin Kang

Research Fellow,
Swinburne University

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PARTNERS

Beyond Blue logo

Beyond Blue

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Infoxchange

Infoxchange

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Reach Out logo

Reach Out

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SANE Australia_1200x600

SANE Australia

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Platform governance of and by bots

PROJECT SUMMARY

Phone with chatbot

Platform governance of and by bots

Focus Area(s): News & Media
Research Program: Data
Status: Completed

This project brings together expertise in digital media, platform studies, and law with data science and machine learning to study the roles and data operations of bots – pre-programmed automated agents – on social media platforms. It aims to map, describe and evaluate the ways that platforms and their users make use of automated agents in governance and community management, and the competing norms and values associated with these practices.

It also examines how platforms and their communities engage in the governance of bots, including through automated moderation and technical limitations. We expect to develop new methods for the public oversight and evaluation of platform governance; as well as to understand why and how bots are understood, valued, and managed in online communities, and to suggest the implications for the benefits of bots for transparent platform governance, including by user communities.

The objectives of this project include:
Undertake a detailed empirical investigation of the role of ‘official’, sanctioned, and user-created bots in governing and managing platform cultures, and the implications of these uses of bots for equality, transparency, and user experience.

Through the data-driven analysis of a particular bot-related controversy, conduct a detailed case study of the norms attached to ‘coordination’ and ‘bot-like’ (or ‘inauthentic’) behaviour on Reddit, and how these norms are enacted and contested through community-led platform governance.
Develop new and updated frameworks for identifying and promoting the pro-social and beneficial uses of bots by platforms and their user communities.

PUBLICATIONS

Dadbot and what ‘He’ reveals about Reddit’s everyday platform culture, 2023

Carlon, D.

Conference paper

RESEARCHERS

ADM+S Investigator Timothy Graham

Dr Timothy Graham

Lead Investigator,
QUT

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Lead Investigator,
QUT

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Daniel Angus

Prof Daniel Angus

Chief Investigator,
QUT

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Axel Bruns

Prof Axel Bruns

Chief Investigator,
QUT

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ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Chief Investigator,
QUT

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Quantifying and Measuring Bias and Engagement

PROJECT SUMMARY

Man working on laptop

Quantifying and Measuring Bias and Engagement

Focus Areas: News & Media, Health
Research Programs: Machines, Data
Status: Active

Automated decision-making systems and machines – including search engines and intelligent assistants – are designed, evaluated, and optimised by defining frameworks that model the users who are going to interact with them. These models are typically a simplified representation of users (e.g., using the relevance of items delivered to the user as a surrogate for system quality) to operationalise the development process of such systems. A grand open challenge is to make these frameworks more complete, by including new aspects such as fairness, that are as important as the traditional definitions of quality, to inform the design, evaluation and optimisation of such systems.

Recent developments in machine learning, information access, and AI communities attempt to define mechanisms to minimise the creation and reinforcement of unintended cognitive biases.

However, there are a number of research questions related to quantifying and measuring bias and engagement that remain unexplored:
– Is it possible to measure bias by observing users interacting with search engines, or intelligent assistants?
– How do users perceive fairness, bias, or trust? How can these perceptions be measured effectively?
– To what extent can sensors in wearable devices and interaction logging (e.g., search queries, app swipes, notification dismissal, etc) inform the measurement of bias and engagement?
– Are the implicit signals captured from sensors and interaction logs correlated with explicit human ratings w.r.t. bias and engagement?

The research aims to address the research questions above by focusing on information access systems that involve automated decision-making components. By partnering with experts in fact-checking, we use misinformation management as the main scenario of study, given that bias and engagement play an important role in three main elements of the automated decision-making processes: the user, the system, and the information that is presented and consumed.

The methodologies considered to address these questions include lab user studies (e.g., observational studies), and the use of crowdsourcing platforms (e.g., Amazon Mechanical Turk). The data collection processes include: logging human-system interactions; sensor data collected using wearable devices; and questionnaires.

PUBLIC RESOURCES

Person working on laptop on wooden desk next to window

Open Source Software: Factchecking – Presentations

Target audience: Researchers, Software Developers
Code type: Python

View on Github

PUBLICATIONS

Report Cover: Quantifying and Measuring Bias and Engagement in Automated Decision-Making

Quantifying and Measuring Bias and Engagement in Automated Decision-Making, 2024

Spina, D., Hettiachchi, D., McCosker, A.

Report

Human-AI Cooperation to Tackle Misinformation and Polarization, 2023

Spina, D., Sanderson, M., et al.

Journal article

Examining the Impact of Uncontrolled Variables on Physiological Signals in User Studies for Information Processing Activities, 2023

Ji, K., Spina, D., et al.

Conference paper

Can Generative LLMs Create Query Variants for Test Collections? 2023

Alaofi, M., Sanderson, M., et al.

Conference paper

Mitigating Negative Transfer with Task Awareness for Sexism, Hate Speech, and Toxic Language Detection, 2023

Spina, D., Rosso, P., Felipe Magnossão de Paula, A.

Conference paper

Do Social Media Users Change Their Beliefs to Reflect those Espoused by Other Users? 2023

Alknjr, H.

Conference paper

How do Human and Contextual Factors Affect the Way People Formulate Queries? 2023

Abu One, N.

Conference paper

Towards Detecting Tonic Information Processing Activities with Physiological Data, 2023

Ji, K., Hettiachchi, D., et al.

Conference paper

Ranking Interruptus: When Truncated Rankings Are Better and How to Measure That, 2022

Spina, D., et al.

Conference paper

Where Do Queries Come From? 2022

Alaofi, M., Spina, D., et al.

Conference paper

User-centered Non-factoid Answer Retrieval, 2022

Alaofi, M.

Conference paper

A Crowdsourcing Methodology to Measure Algorithmic Bias in Black-box Systems: A Case Study with COVID-related Searches, 2022

Scholar, F., Spina, D., Chia, H., Le, B.

Conference paper

AWARDS

2023 Pervasive and Ubiquitous Computing (UbiComp) International Symposium on Wearable Computing (ISWC)
Student Challenge Award
zzzGPT: An Interactive GPT Approach to Enhance Sleep Quality
Yonchanok (Pro) KhaokaewKaixin Ji, Marwah Alaofi, Hiruni Kegalle, Thuc Hanh Nguyen (UNSW) and Prof Flora Salim

2023 Pervasive and Ubiquitous Computing (UbiComp) International Symposium on Wearable Computing (ISWC)
Best Poster Award
Towards Detecting Tonic Information Processing Activities with Physiological Data’
Dr Damiano SpinaKaixin Ji, Prof Falk Scholer, Dr Danula Hettiachchi and Prof Flora Salim

17th Conference on Evaluation of Information Access Technologies (NTCIR-17)
Best Oral Presentation
Sachin Cherumanal Pathiyan

RESEARCHERS

Dr Damiano Spina

Dr Damiano Spina

Lead Investigator,
RMIT University

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ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Chief Investigator,
Swinburne University

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ADM+S Investigator Flora Salim

Prof Flora Salim

Chief Investigator,
UNSW

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ADM+S Chief Investigator Mark Sanderson

Prof Mark Sanderson

Chief Investigator,
RMIT University

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Danula Hettiachchi

Dr Danula Hettiachchi

Associate Investigator,
RMIT University

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ADM+S Associate Investigator Jenny Kennedy

Assoc Prof Jenny Kennedy

Associate Investigator,
RMIT University

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ADM+S Chief Investigator Falk Scholer

Prof Falk Scholer

Associate Investigator,
RMIT University

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ADM+S Member

Nuha Abu Onq

PhD Student,
RMIT University

Marwah Alaofi

Marwah Alaofi

PhD Student,
RMIT University

Learn more

ADM+S Member

Hmdh Alknjr

PhD Student,
RMIT University

Sachin Pathiyan Cherumanal

PhD Student,
RMIT University

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Kaixin Ji

Kaixin Ji

PhD Student,
RMIT University

Learn more

PARTNERS

ABC logo

Australian Broadcasting Corporation

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AlgorithmWatch Logo

Algorithm Watch (Germany)

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Bendigo Health logo

Bendigo Hospital

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Google Logo

Google Australia

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RMIT ABC Fact Check Logo

RMIT ABC Fact Check

Visit website

The Coronavirus Impact

PROJECT SUMMARY

COVID19 Stay safe on mobile device

The Coronavirus Impact

Focus Areas: News and Media, Transport and Mobility, Health, and Social Services
Research Program: Data
Status:
Completed

This project focused on a publication output: a themed issue of the journal New Media & Society. Our theme proposal was accepted and the theme issue is in its final stages pre-publication. We are still waiting for comments on one article, but 10 articles have been accepted for publication by the journal and the introduction has been written. We are only waiting for the decision on the last outstanding article before submitting the complete package to the editors for final review. The entire issue ended up being written by Centre members.

The focus of the issue is on the range of roles played by automated decision making systems in the pandemic response. These range from the automated curation of news content to automated contact tracing and air quality management. Contributions came from all four focus areas of the Centre. The timeframe for the issue enabled the inclusion of articles that tracked the shift from pandemic to endemic and an analysis of the ways in which systems developed in response to the pandemic persisted or faded away.

RESEARCHERS

Mark Andrejevic

Prof Mark Andrejevic

Lead Investigator,
Monash University

Learn more

ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Chief Investigator,
QUT

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ADM+S Chief Investigator Heather Horst

Prof Heather Horst

Chief Investigator,
Western Sydney University

Learn more

ADM+S Chief Investigator Sarah Pink

Prof Sarah Pink

Chief Investigator,
Monash University

Learn more

Gerard Goggin

Prof Gerard Goggin

Associate Investigator,
Western Sydney University

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Prof Ariadna Matamoros-Fernandez

Associate Investigator,
QUT

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Michael Richardson

Assoc Prof Michael Richardson

Associate Investigator,
UNSW

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Georgia Van Toorn

Dr Georgia van Toorn

Associate Investigator,
UNSW

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Rowan Wilken

Assoc Prof Rowan Wilken

Associate Investigator,
RMIT University

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Christopher O'Neill

Dr Christopher O’Neil

Research Fellow,
Monash University

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Dr Silvia Montaña-Niño profile picture

Dr Silvia Montaña-Niño

Affiliate,
University of Melbourne

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PARTNERS

Australian Red Cross Logo

Australian Red Cross

Visit website

OVIC Logo

Victorian Information Commissioner

Visit website

Data & Society Research Institute (US)

Visit website

Data mapping and ADM to advance humanitarian action and preparedness

PROJECT SUMMARY

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Data mapping and ADM to advance humanitarian action and preparedness

Focus Areas: News & Media, Social Services
Research Program: Data
Status: Completed

Humanitarian organisations and other NGOs are undergoing significant digital transformation. In a complicated digital media environment, new analytics capabilities can improve the role and effectiveness of organisations like Australian Red Cross in building community resilience, expanding volunteer networks, and informing rapid response. New models are needed for building data capability within communities prone to disaster and emergency. This includes community-driven practices for gathering useful open access data and local knowledge to aid and automate decision-making in disaster preparedness.

This project aimed to explore the potential of data partnerships and local community data capability for improving humanitarian preparedness and response to emergency situations. It contributes to developing new techniques for improving data-driven mapping of community strengths, knowledge and resilience. The work will improve advocacy and preparedness and enhance Red Cross’s data analytics capability as the organisation seeks to work with and empower local communities.

The project’s interim report, Mapping Community Resources for Disaster Preparedness: Humanitarian Data Capability and Automated Futures, sets out background knowledge about open data and mapping practices for disaster response, prediction and preparedness. Building on stakeholder workshops and international collaboration, the Mapping Community Resources report presents a model for community-oriented, open access and strengths-based data mapping capability.

PUBLIC RESOURCES

Volunteers packing boxes into a van

Open Source Software: Community Resource Mapping Platform

Target audience: Researchers, Software Developers
Content type: Dataset

View on Github

PUBLICATIONS

Towards resilient communities: data capability and resource mapping for disaster preparedness, 2023

McCosker, A., Shaw, F., Kang, Y.B.

Report

Mapping Community Resources for Disaster Preparedness: Humanitarian Data Capability and Automated Futures, 2022

McCosker, A., Shaw, F., Calyx, C., Kang, Y.B.

Report

RESEARCHERS

ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Lead Investigator,
Swinburne University

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Daniel Angus

Prof Daniel Angus

Chief Investigator,
QUT

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Kath Albury

Prof Kath Albury

Associate Investigator,
Swinburne University

Learn more

Jane Farmer

Prof Jane Farmer

Associate Investigator,
Swinburne University

Learn more

Rowan Wilken

Assoc Prof Rowan Wilken

Associate Investigator,
RMIT University

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ADM+S Investigator Ivana Jurko

Ivana Jurko

Partner Investigator,
Red Cross Australia

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PARTNERS

Australian Red Cross Logo

Australian Red
Cross

Visit website

Everyday Data Cultures

PROJECT SUMMARY

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Everyday Data Cultures

Focus Areas: News and Media, Transport and Mobility, Health, and Social Services
Research Program: Data
Status: Completed

This project explored the role of everyday data practices and literacies in automated decision-making. Its primary contribution is the novel conceptual framework of everyday data cultures, which is based on the cultural studies of everyday life. As well as a number of papers and public talks, it produced a co-authored monograph: Everyday Data Cultures (Polity Press, 2022).

Members of this team used this framework in subsequent research that sought to integrate everyday community experience into data projects with our partners in a variety of sectors across aspects of all four of the Centre’s focus areas. It will be used in future work within the Centre seeking to make sense of the impact and take-up of Generative AI in daily life – at home, at work, and in intimate relationships.

PUBLICATIONS

Everyday Data Cultures, 2022

Burgess, J., Wilken, R., McCosker, A., Albury, K.

Book

Everyday data cultures: beyond Big Critique and the technological sublime, 2022

Burgess, J.

Journal article

Everyday Data Cultures and USB Portable Flash Drives, 2022

Kennedy, J., Wilken, R.

Journal article

Making sense of deepfakes: Socializing AI and building data literacy on GitHub and YouTube, 2022

McCosker, A.

Journal article

Liminoid Media: On the Enduring Significance of USB Portable Flash Drives, 2021

Kennedy, J., Wilken, R.

Journal article

RESEARCHERS

ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Lead Investigator,
QUT

Learn more

ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Chief Investigator,
Swinburne University

Learn more

Rowan Wilken

Assoc Prof Rowan Wilken

Associate Investigator,
RMIT University

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Kath Albury

Prof Kath Albury

Associate Investigator,
Swinburne University

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Mapping ADM Across Sectors

PROJECT SUMMARY

Blurred crowd of people

Mapping ADM Across Sectors

Focus Areas: News and Media, Transport and Mobility, Health, and Social Services
Research Programs: Data, Machines, Institutions, and People
Status: Active

ADM systems have the potential to greatly improve the overall quality of life in society, but they may also exacerbate social, political, and economic inequality. The role they play in reinforcing, reproducing, and reconfiguring power relations is, as recent events demonstrate, a key concern with respect to the deployment of automated decision making systems. When such systems are used to decide how benefits, resources, services, or information are allocated in society, they bear directly on the character and quality of life in that society. We are interested in both the potential benefits of the deployment of the technology and the potential harms. We do not treat such systems in the abstract, but are centrally concerned with the social, political, and economic relations in which they are embedded and which shape their deployment. A key question for the ADM+S Centre, in other words, is not just how best to design and deploy the technology, but what economic and political arrangements are most compatible with their fair, ethical, responsible, and democratic use.

The Social Issues in Automated Decision-Making report brings together material collected from discussions with leaders in the Centre’s focus areas and feedback from an international collection of experts in their respective domains. For each focus area we followed a similar methodology for canvassing key social issues. We started by discussing key social issues with Focus Area leaders and their teams. We then canvassed the academic literature, reports by industry groups and relevant independent organisations, and media coverage. For each area, we sought to identify key applications of ADM and the possible social benefits and harms with which they are associated. We also sought to identify continuities in these social issues both within and across the Centre’s main focus areas.

This is neither a final nor a definitive report. It marks the first step in the Centre’s ongoing social issues mapping project. The document will develop over time to reflect the insights that emerge from ongoing collaborations.

Read the report.

PUBLICATIONS

Social issues in ADM

Social Issues in Automated Decision Making, 2022

O’Neill, C., Sadowski, J.,  Andrejevic, M. et al

Report

RESEARCHERS

Mark Andrejevic

Prof Mark Andrejevic

Lead Investigator,
Monash University

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Paul Henman

Prof Paul Henman

Chief Investigator,
University of Queensland

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ADM+S Investigator Ramon Lobato

Assoc Prof Ramon Lobato

Associate Investigator,
RMIT University

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Jathan Sadowski

Dr Jathan Sadowski

Associate Investigator,
Monash University

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Georgia Van Toorn

Dr Georgia van Toorn

Associate Investigator,
UNSW

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Kelly Lewis

Dr Kelly Lewis

Research Fellow,
Monash University

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Christopher O'Neill

Dr Christopher O’Neil

Research Fellow,
Monash University

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Daniel Binns

Dr Daniel Binns

Affiliate,
RMIT University

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Dr Lyndal Sleep

Affiliate,
Central Queensland University

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PARTNERS

OVIC Logo

Office of the Victorian Information Commissioner

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Australian Red Cross Logo

Australian Red Cross

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Data Ethics, Rights, and Markets

PROJECT SUMMARY

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Data Ethics, Rights, and Markets

Focus Areas: News and Media, Transport and Mobility, Health, and Social Services
Research Program: Data
Status: Active

The goal of this project is to contribute to the theoretical “backbone” of the ADM+S Centre and help synthesise the findings from projects in different focus areas and research programs through the creation of an historically informed theoretical overview to the social issues associated with the rise of automated decision-making (ADM).

The project supplements the descriptive mapping project (typologies and taxonomies of ADM) with an issue mapping project that connects directly with the core social concerns of the Centre: fairness, ethics, inclusion, and effectiveness.

RESEARCHERS

Distinguished Professor Julian Thomas

Prof Julian Thomas

Lead Investigator,
RMIT University

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Chief Investigator,
QUT

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Axel Bruns, Chief Investigator with the ADM+S Centre

Prof Axel Bruns

Chief Investigator,
QUT

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Jake Goldenfein

Dr Jake Goldenfein

Chief Investigator,
University of Melbourne

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Paul Henman

Prof Paul Henman

Chief Investigator,
University of Queensland

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ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Chief Investigator,
Swinburne University

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ADM+S Investigator Christine Parker

Prof Christine Parker

Chief Investigator,
University of Melbourne

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Sarah Pink

Prof Sarah Pink

Chief Investigator,
Monash University

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ADM+S Chief Investigator Mark Sanderson

Prof Mark Sanderson

Chief Investigator,
RMIT University

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Kimberlee Weatherall

Prof Kimberlee Weatherall

Chief Investigator,
University of Sydney

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Affiliate,
University of Melbourne

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PARTNERS

Australian Red Cross Logo

Australian Red Cross

Visit website

Data & Society Research Institute (US)

Visit website

OVIC Logo

Victorian Information Commissioner

Visit website

Automated Content Regulation (Sexuality Education and Health Information)

PROJECT SUMMARY

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Automated Content Regulation (Sexuality Education and Health Information)

Focus Area: Health
Research Program: Data
Status: Completed

This project involved a series of informal dialogues between ADM&S researchers, UNESCO staff and researchers in the fields of sexual justice and international development in 2021. These meetings discussed the multiple anecdotal accounts by sexual health promotion organisations worldwide of the chilling effect of existing content moderation practices, primarily in relation to Facebook and Instagram.

It was concluded that a large-scale global survey would be the most effective and actionable means of generating data that UNESCO and other NGOs could use within training and advocacy activities.
The participating researchers and practitioners co-designed a draft survey framework that could be used to assess the impacts of content moderation on sexuality educators and health promoters globally.

While the survey did not proceed as an ADM&S activity, UNESCO representatives were able to build on these discussions to inform the development of an internal community of practice for global content developers.

Key findings from these dialogues were shared at the 2021 Youth Tech Health Conference, hosted by the US-based not-for-profit health promotion organisation ETR, and HDR Williams has since presented at Australian health promotion conferences.

Other key outputs included submissions by HDR Williams and Research Fellow Stardust that informed Meta Oversight Board’s 2023 Decision on Gender Identity and Nudity on Instagram. Both submissions were cited in the Oversight Board’s report, informing recommendations to overturn existing bans, and revise and clarify existing guidelines relating to nudity and ‘sexual solicitation’.

RESEARCHERS

Kath Albury

Prof Kath Albury

Lead Investigator,
Swinburne University

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ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Chief Investigator,
Swinburne University

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ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Chief Investigator,
QUT

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Dr Zahra Stardust

Research Fellow,
QUT

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Joanna Williams

Joanna Williams

PhD Student,
Swinburne University

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COLLABORATORS AND PROJECT ADVISORS

  • Sally Beadle
    Programme Specialist, UNESCO
  • Pauline Oosterhof
    Research Fellow, Institute of Development Studies (UK)
  • Susie Jolly
    Independent Scholar and Associate, Institute of Development Studies (UK)

Data capacity and collaboration for ADM in the community sector

PROJECT SUMMARY

Group of people in huddle

Data capacity and collaboration for ADM in the community sector

Focus Area: Social Services
Research Program: Data
Status: Active

The project works toward a replicable framework for building capacity (expertise, literacy, data partnerships and data governance) to unlock the social value and impact of advanced data analytics, AI and ADM across the not-for-profit sector. The aim is to develop models for responsible data practices suitable for addressing the goals and challenges faced by the NFP sector, and assess and advance data literacy and expertise to improve ADM outcomes.

This project takes an innovative approach to addressing challenges in data collaboration and developing data capability across the not-for-profit (NFP) sector. Through participatory methods, it integrates technical approaches to responsible data management in computer science, legal approaches to data sharing, and social science approaches to data capability building and ‘data and AI for social good’.

The project works toward a replicable framework for building capacity (expertise, literacy, data partnerships and data governance) to unlock the social value and impact of advanced data analytics, AI and ADM across the not-for-profit sector. The aim is to develop models for responsible data practices suitable for addressing the goals and challenges faced by the NFP sector and assess and advance data literacy and expertise to improve ADM outcomes.

Phase One of the project worked with a range of not-for-profit organisations to establish the key challenges and opportunities in the sector for using data and ADM to address disadvantage in the community.

This research phase resulted in an Interim report: ‘Building Data Capacity in the Not-for-Profit Sector’. Our research has shown that data capability involves fostering effective and responsible data practices across three integrated dimensions: data access and infrastructure, data skills and data governance. Insights from Phase One were used to co-design a NFP specific Data Capability Framework and test the Framework through three participatory workshops throughout Phase Two.

Phase Two of the project applied participatory methods to generate a Data Capability Framework designed to support the Not-for-Profit sector.

As social and community services rapidly digitise, they are generating more data than ever before. Co-designed with organisations from across the sector, the Data Capability Framework for the Not-for-Profit Sector sets out a pathway for developing effective and responsible data practices across three integrated dimensions: data access and infrastructure, data skills and data governance. This work lays the foundations for safe, responsible and inclusive automated decision-making and AI use across the sector.

The Framework distils the challenges and successes of organisations we have worked with. It represents both the factors that underpin effective data capability and the pathways to achieving it. In other words, as technologies and data science techniques continue to change, data capability is both an outcome to aspire to, and a dynamic, ongoing process of experimentation and adaption.

PUBLICATIONS

Developing data capability with non-profit organisations using participatory methods, 2022

McCosker, A., Yao, X., Stoyanovich, J.

Journal article

A Data Capability Framework for the not-for-profit sector, 2022

McCosker, A. Shaw, F., Yao, X., Albury, K.

Report

 Building Data Capacity in the Not-For-Profit Sector, 2021

McCosker, A., Yao, X., Albury, K. Farmer, J., Maddox, A.

Report

RESEARCHERS

ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Lead Investigator,
Swinburne University

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Jake Goldenfein

Dr Jake Goldenfein

Chief Investigator,
University of Melbourne

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Kimberlee Weatherall

Prof Kimberlee Weatherall

Chief Investigator,
University of Sydney

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Kath Albury

Prof Kath Albury

Associate Investigator,
Swinburne University

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Jane Farmer

Prof Jane Farmer

Associate Investigator,
Swinburne University

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ADM+S Investigator Julia Stoyanovich

Assistant Prof Julia Stoyanovich

Partner Investigator,
New York University

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Yong-Bin Kang

Dr Yong-Bin Kang

Research Fellow,
Swinburne University

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Xiaofang Yao

Dr Xiaofang Yao

Affiliate,
Federation University

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PARTNERS

Infoxchange

Infoxchange

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Australian Red Cross Logo

Australian Red Cross

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The Australian Ad Observatory Project

PROJECT SUMMARY

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The Australian Ad Observatory Project

Focus Area(s): News & Media
Research Program: Data
Status: Active

The Ad Observatory develops and applies tools for observing how so-called ‘dark ads’ are targeted on Facebook. The goal is to respond to changes in the advertising environment by providing models for accountability and transparency of advertising targeted to individuals on social media. The current tool is limited to the use of Facebook on desktop and laptop computers. The Observatory team, however, has worked with different approaches on other platforms and is developing a mobile app that will collect ads from users.

To date we have over 1900 volunteers participating in the Facebook component of the project by installing the Observatory’s browser extension which allows them to share with us the sponsored content that appears in their news feeds. This participation has yielded more than 700,000 ad observations of more than 300,000 unique ads. These ads have, in turn, served as the basis for research projects on greenwashing and on the advertising of harmful products and services including: alcohol, gambling, ultra-processed foods, and financial services.

Outputs so far include six documents including working papers, technical reports, and academic publications. The project has also received substantial media attention, resulting in stories by partner organisation ABC about illegal gambling ads and scam ads. It has also resulted in collaboration with organisations including CHOICE, the Consumer Policy Research Centre, the Alliance for Gambling Reform, and VicHealth. Project findings and approaches have been presented at international conferences and we continue to develop partnerships both nationally and internationally.

Visit the public facing Australian Ad Observatory page for further information, and to join the project.

PUBLIC RESOURCES

Blurred image with apps on a mobile device

Open Source Software: Mobile Ad Observatory

Target audience: Researchers, Software Developers
Content type: Javascript

View on Github

Magnifying glass looking at Facebook page

Open Source Software: Australian Ad Observatory Dashboard API

Target audience: Researchers, Software Developers
Content type: Javascript

View on Github

PUBLICATIONS

ADM+S submission to the Feasibility study on options to limit unhealthy food marketing to children

June 2024

Read the submission

Report cover: The Australian Ad Observatory Technical and Data Report

ADM+S Working Paper Series. The Australian Ad Observatory Technical and Data Report.

January 2024

Read the report

Report Cover: Seeing Green

Seeing Green. Prevalence of environmental claims on social media.

November 2023

Read the report

Cover: Addition Research & Theory

Addressing the accountability gap: gambling advertising and social media platform responsibilities

June 2023

Access the journal article

Alcohol advertising on social media platforms – A 1-year snapshot. Foundation for Alcohol Research and Education: Canberra.

March 2023

Read the report

Report: Advertisements on digital platforms: How transparent and observable are they?

Advertisements on digital platforms: How transparent and observable are they?

March 2022

Read the report

ADM+S Working Paper Series: Australian Ad Observatory

The Australian Ad Observatory: Background Paper

July 2022

Read on APO

Journal Article: Critical simulation as hybrid digital method for exploring the data operations and vernacular cultures of visual social media platforms

Critical simulation as hybrid digital method for exploring the data operations and vernacular cultures of visual social media platforms.

SocArXiv, 2021

Access the Journal Article

Journal Article: Sheding Light on Dark Ads

Shedding Light on Dark Ads

Continuum, November 2023

Access Journal Article

Book Chapter: Ad Accountability Online

Ad Accountability Online: A methodological approach

In Everyday Automation, pp. 213-225. Routledge, 2022

Read Book Chapter

Regulating Platforms’ Algorithmic Brand Culture: The Instructive Case of Alcohol Marketers on Social Media

Regulating Platforms’ Algorithmic Brand Culture: The Instructive Case of Alcohol Marketers on Social Media

In Digital Platform Regulation, 2022

Read the Article

GitHub logo

The Australian Ad Observatory Data Donation Plugin

Github, September 2021

Code and Documentation on Github

RESEARCHERS

Mark Andrejevic

Prof Mark Andrejevic

Lead Investigator,
Monash University

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Daniel Angus

Prof Daniel Angus

Chief Investigator,
QUT

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Chief Investigator,
QUT

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ADM+S Investigator Christine Parker

Prof Christine Parker

Chief Investigator,
University of Melbourne

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Kim Weatherall

Prof Kim Weatherall

Chief Investigator,
University of Sydney

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ADM+S Chief Investigator Christopher Leckie

Prof Chris Leckie

Chief Investigator,
University of Melbourne

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Nicholas Carah

Prof Nicholas Carah

Associate Investigator,
University of Queensland

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ADM+S Investigator Timothy Graham

Assoc Prof Timothy Graham

Associate Investigator,
QUT

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Lauren Hayden

Lauren Hayden

PhD Student,
University of Queensland

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ADM+S professional staff Abdul Obeid

Dr Abdul Obeid

Data Engineer,
QUT

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César Albarrán-Torres

Dr César Albarrán-Torres

Affiliate,
Swinburne University

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Julian Bagnara

Julian Bagnara

Affiliate,
University of Melbourne

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Bronwyn Carlson

Prof Bronwyn Carlson

Affiliate,
Macquarie University

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Loup Cellard

Dr Loup Cellard

Affiliate,
Datactivist Coop

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Robbie Fordyce

Dr Robbie Fordyce

Affiliate,
Monash University

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Kelly Lewis

Dr Kelly Lewis

Affiliate,
Monash University

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Tanita Northcott

Tanita Northcott

Affiliate,
University of Melbourne

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Christopher O'Neill

Dr Christopher O’Neil

Affiliate,
Deakin University

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Affiliate,
University of Melbourne

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Verity Trott

Dr Verity Trott

Affiliate,
Monash University

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PARTNERS AND COLLABORATING ORGANISATIONS

ABC logo

Australian Broadcasting Corporation

Visit website

AlgorithmWatch logo

Algorithm Watch

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Consumer Policy Research Centre Logo

Consumer Policy Research Centre (CPRC)

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FARE Logo

Foundation for Alcohol Research and Education (FARE)

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RMIT ABC Fact Check Logo

RMIT ABC Fact Check

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New York university

New York University

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Civic Automated Decision-Making

PROJECT SUMMARY

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Civic Automated Decision-Making

Focus Areas: News and Media, Transport and Mobility, Health, and Social Services
Research Program: Data
Status:
Completed

As part of the ARC Centre’s mandate to create the knowledge and strategies necessary for responsible, ethical, and inclusive automated decision-making, this project engages with the role played by such systems in democracy and civic life. The impetus for this project is to supplement discussions of AI ethics with those of AI civics – and, in particular to consider the practices, policies, technologies, and social-political arrangements of automated decision making systems that are most compatible with a vibrant democracy.

Recent developments render such a conversation increasingly pressing. The institutions that to which we have entrusted the development of some of the most powerful automated contemporary information and communication technologies available do not necessarily have civic or democratic concerns as top priority – this is not what they are built to do. Our steering mechanisms are having a difficult time keeping up – and it is crucially important to consider alternative possible arrangements for storing and processing the data upon which society relies. These questions lie at the heart of what it means to formulate world-leading policy and practice, as envisioned by the Centre.

This project draws upon expertise from across the Centre’s programs and Focus Areas to develop conceptual and practical interventions designed to align automated systems with civic and democratic imperatives. The initial phase of the project was an agenda setting workshop to consider key issues and approaches. The next step will be a themed issue or edited collection that develops approaches to Civic ADM. The final stage will include integration of these approaches with practical initiatives in the Centre, including observability and accountability projects.

RESEARCHERS

Mark Andrejevic

Prof Mark Andrejevic

Lead Investigator,
Monash University

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Jake Goldenfein

Dr Jake Goldenfein

Chief Investigator,
University of Melbourne

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ADM+S Investigator Christine Parker

Prof Christine Parker

Chief Investigator,
University of Melbourne

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Distinguished Professor Julian Thomas

Prof Julian Thomas

Chief Investigator,
RMIT University

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Kimberlee Weatherall

Prof Kimberlee Weatherall

Chief Investigator,
University of Melbourne

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ADM+S Investigator James Meese

Assoc Prof James Meese

Associate Investigator,
RMIT University

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ADM+S Chief Investigator Andrew Kenyon

Prof Andrew Kenyon

Associate Investigator,
University of Melbourne

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Kylie Pappalardo profile picture

Dr Kylie Pappalardo

Associate Investigator,
QUT

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Michael Richardson

Assoc Prof Michael Richardson

Associate Investigator,
UNSW

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Andrew Roberts

Prof Andrew Roberts

Associate Investigator,
University of Melbourne

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Dr Aaron Snoswell

Dr Aaron Snoswell

Associate Investigator,
QUT

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ADM+S Investigator Robert Sparrow

Prof Robert Sparrow

Associate Investigator,
Monash University

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Georgia Van Toorn

Dr Georgia van Toorn

Associate Investigator,
UNSW

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ADM+S Investigator Frank Pasquale

Prof Frank Pasquale

Partner Investigator,
Cornell Tech

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Kelly Lewis

Dr Kelly Lewis

Research Fellow,
Monash University

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Jathan Sadowski

Dr Jathan Sadowski

Research Fellow,
Monash University

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Zoe Horn

Zoe Horn

PhD Student,
Western Sydney University

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Lucinda Nelson

Lucinda Nelson

PhD Student,
QUT

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Christopher O'Neill

Dr Christopher O’Neil

Affiliate,
Deakin University

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PARTNERS

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Office of the Victorian Information Commissioner

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Data & Society Research Institute (US)

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The Australian Search Experience

PROJECT SUMMARY

Person searching laptop with labrador by their side

The Australian Search Experience

Focus Area: News and Media
Research Program: Data
Status: Active

There is a lot of speculation about the impact that search engines have on the information we encounter. Search engine personalisation may be influencing individuals’ search results, and thereby shape what they know of the world. This may affect their personal decisions, and our collective decisions as a society – from how we spend our money or who we vote for to our attitudes on critical issues such as the safety of COVID-19 vaccines.

This research examines the extent to which search results are personalised, by various leading search engines and their algorithms, based on the profiles established by those search engines for their different users. It compiles and analyses the search recommendations encountered by a wide range of genuine users across prominent digital media platforms, for a variety of generic and specific topics, and over time.

The project launched in late July 2021 and over 12 months collected over 350 million search results from more than 1,000 participants. The project took a citizen science approach, relying on data donations from the general public made through a unique desktop browser plugin. ADM+S researchers have been analysing the data to understand the personalisation of search results for critical news and information, across key platforms including Google and YouTube, based on the profiles these platforms establish for their different users.

CASE STUDIES

Case Study: Google News
This project is examining Google News results to understand how recommender systems and search personalisation intersect with news distribution. Preliminary findings show limited evidence of personalisation, with news and information sources recommended for particular searches mainly influenced by the search topic. The team is now exploring the diversity of news outlets in the dataset, with the goal of finding out how much local and national news is featured in Google News results. The project will also reveal whether particular news outlets appear more often than others.

Case Study: Comparing search results across Google platforms/services
This project examines search results across Google News, Google Search, Google videos, and YouTube to understand how different Google services and platforms operationalise ‘authoritativeness’ across socio-cultural issues and over time. The project focuses on the sources that are ranked at the top on each service/platforms and reflects on issues of media diversity in relation to these results.

PUBLIC RESOURCES

Person typing on laptop keyboard with search bar in foreground

Open Source Software: The Australian Search Experience: Background Paper

Target audience: Researchers, Software Developers
Content type: HTML

View on Github

PUBLICATIONS

The Australian Search Experience: Background Paper

15 Jan 2022

Read on APO

RESEARCHERS

Axel Bruns, Chief Investigator with the ADM+S Centre

Prof Axel Bruns

Lead Investigator, QUT

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Mark Andrejevic

Prof Mark Andrejevic

Chief Investigator, Monash University

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Chief Investigator, QUT

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ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Chief Investigator, QUT

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Kimberlee Weatherall

Prof Kimberlee Weatherall

Chief Investigator, University of Sydney

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Daniel Angus

Prof Daniel Angus

Associate Investigator, QUT

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ADM+S Investigator Timothy Graham

Dr Timothy Graham

Associate Investigator, QUT

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Ariadna Matamoros Fernandez profile picture

Dr Ariadna Matamoros-Fernández

Associate Investigator, QUT

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James Meese

Assoc Prof James Meese

Associate Investigator, RMIT University

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ADM+S Chief Investigator Falk Scholer

Prof Falk Scholer

Associate Investigator, RMIT University

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ADM+S Investigator Damiano Spina

Dr Damiano Spina

Associate Investigator, RMIT University

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Louisa Bartolo

PhD Student,
QUT

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Ehsan Dehghan

Dr Ehsan Dehghan

Affiliate,
QUT

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PARTNERS

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AlgorithmWatch
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University of Twente

University of Twente

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