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

PROJECT SUMMARY

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

CHOICE

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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?

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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Kelly Lewis

Dr Kelly Lewis

Research Fellow,
Monash University

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Christopher O'Neill

Dr Chris O’Neill

Research Fellow,
Monash University

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Thao Phan

Dr Thao Phan

Research Fellow,
Monash University

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Zoe Horn

Zoe Horn

PhD 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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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: Transport and 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.

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

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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

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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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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Aitor Jiménez

Dr Aitor Jiménez

Research Fellow,
University of Melbourne

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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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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: Active

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.

BOOK

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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ReachOut

ReachOut

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Yooralla

Yooralla

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Political Economy of Sex Tech

PROJECT SUMMARY

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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.

RESEARCHERS

Zahra Stardust profile picture

Dr Zahra Stardust

Lead 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: Active

This project identifies how misunderstandings of harm and safety flow into flawed data logics and ineffective automated digital platform responses. To date, platforms have presented the principal unit of harm as individual pieces of content or media objects.

Based on this assumption, platforms’ responses to harm have primarily focused on moderating discrete pieces of content.

RESEARCHERS

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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Dr Rosalie Gillett profile picture

Dr Rosalie Gillett

Research Fellow,
QUT

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ADM+S professional staff Abdul Obeid

Dr Abdul Obeid

Data Engineer,
QUT

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Automated Content Regulation (Disinformation and Political Bias)

PROJECT SUMMARY

A group of people using mobile phones

Automated Content Regulation (Disinformation and Political Bias)

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

This project will evaluate the moderation of social media content, which has become radically more reliant on machine learning classifiers during the Covid-19 pandemic. We examine moderation at this time through two case studies, which aim to:

  1. Test allegations of political bias in the removal of tweets, and
  2. Identify coordinated bot activity involved in spreading misinformation and the moderation responses of platforms.

Ultimately, this project will provide new knowledge about particular case studies, import insights into trends across cases and time, and new methodological techniques for assessing automated content moderation on social media platforms.

RESEARCHERS

ADM+S Chief Investigator Nic Suzor

Prof Nic Suzor

Lead Investigator,
QUT

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Chief Investigator,
QUT

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ADM+S Chief Investigator Andrew Kenyon

Prof Andrew Kenyon

Chief Investigator,
University of Melbourne

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ADM+S Investigator Timothy Graham

Dr Timothy Graham

Associate Investigator,
QUT

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PARTNERS

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American University

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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: Active

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.

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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Peter Kamstra

Dr Peter Kamstra

Associate Investigator,
Swinburne University

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Yong-Bin Kang

Dr Yong-Bin Kang

Research Fellow,
Swinburne University

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Frances Shaw

Dr Frances Shaw

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

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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: Active

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.

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.

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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ADM+S Associate Investigator Jenny Kennedy

Dr 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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Danula Hettiachchi

Dr Danula Hettiachchi

Research Fellow,
RMIT University

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Nuha Abu Onq

PhD Student,
RMIT University

Marwah Alaofi

Marwah Alaofi

PhD Student,
RMIT University

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Hmdh Alknjr

PhD Student,
RMIT University

Danula Hettiachchi

Sachin Cherumanal

PhD Student,
RMIT University

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Kaixin Ji

Kaixin Ji

PhD Student,
RMIT University

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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

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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:
 Active

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

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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

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ADM+S Chief Investigator Sarah Pink

Prof Sarah Pink

Chief Investigator,
Monash University

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Gerard Goggin

Prof Gerard Goggin

Associate Investigator,
University of Sydney

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Prof Ariadna Matamoros-Fernandez

Associate Investigator,
QUT

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Christopher O'Neill

Assoc Prof Michael Richardson

Associate Investigator,
UNSW

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Rowan Wilken

Assoc Prof Rowan Wilken

Associate Investigator,
RMIT University

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Dr Silvia Montaña-Niño

Research Fellow,
QUT

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Christopher O'Neill

Dr Christopher O’Neil

Research Fellow,
Monash University

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Dr Georgia van Toorn

Research Fellow,
UNSW

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PARTNERS

Australian Red Cross Logo

Australian Red Cross

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OVIC Logo

Victorian Information Commissioner

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Data & Society Research Institute (US)

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Data mapping and ADM to advance humanitarian action and preparedness

PROJECT SUMMARY

Volunteer charity workers

Data mapping and ADM to advance humanitarian action and preparedness

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

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.

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

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Jane Farmer

Prof Jane Farmer

Associate Investigator,
Swinburne University

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Peter Kamstra

Dr Peter Kamstra

Associate Investigator,
Swinburne University

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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

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Everyday Data Cultures

PROJECT SUMMARY

Businessman using cell phone on subway train

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.

RESEARCHERS

ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Lead Investigator,
QUT

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ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Chief Investigator,
Swinburne University

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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

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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.

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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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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Georgia Van Toorn

Dr Georgia van Toorn

Research Fellow,
UNSW

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Ash Watson

Dr Ash Watson

Research Fellow,
UNSW

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Vaughan Wozniak-O'Connor

Dr Vaughan Wozniak-O’Connor

Research Fellow,
UNSW

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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

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Office of the Victorian Information Commissioner

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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

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Data & Society Research Institute (US)

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OVIC Logo

Victorian Information Commissioner

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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: Active

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

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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.

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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ADM+S Investigator Julia Stoyanovich

Dr Frances Shaw

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

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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.

For more information, and to join the Australian Ad Observatory,
click here.

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

Assoc Prof Nicholas Carah

Associate Investigator,
University of Queensland

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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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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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ADM+S Investigator Christine Parker

Dr César Albarrán-Torres

Affiliate,
Swinburne University

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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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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

Consumer Policy Research Centre Logo

Consumer Policy Research Centre (CPRC)

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New York university

New York University

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AlgorithmWatch logo

Algorithm Watch

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RMIT ABC Fact Check Logo

RMIT ABC Fact Check

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CHOICE

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Foundation for Alcohol Research and Education (FARE)

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ABC logo

Australian Broadcasting Corporation

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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:
 Active

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

Dr 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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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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ADM+S Investigator Robert Sparrow

Prof Robert Sparrow

Associate Investigator,
Monash University

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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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Christopher O'Neill

Dr Christopher O’Neil

Research Fellow,
Monash University

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Jathan Sadowski

Dr Jathan Sadowski

Research Fellow,
Monash University

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Dr Aaron Snoswell

Dr Aaron Snoswell

Research Fellow,
QUT

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Georgia Van Toorn

Dr Georgia van Toorn

Research Fellow,
UNSW

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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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PARTNERS

Brooklyn Law School logo

Brooklyn Law School

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Data & Society Research Institute (US)

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OVIC Logo

Office of the Victorian Information Commissioner

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The Australian Search Experience

PROJECT SUMMARY

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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.

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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Dr Ariadna Matamoros-Fernández

Associate Investigator, QUT

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ADM+S Investigator James Meese

Dr 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

PrD Student,
QUT

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Arjun Srinivas

Arjun Srinivas

PhD Student,
QUT

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PARTNERS

AlgorithmWatch logo

AlgorithmWatch
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University of Twente

University of Twente

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