Generative Authenticity

PROJECT SUMMARY

Generative Authenticity

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

Authenticity is a key problem for understanding and managing the impacts of generative AI and synthetic media in society, and a central target for automated decision-making systems in the information and media environment. From trustworthy news reporting to identity verification for social services and the everyday risk of scams, generative AI and synthetic media present significant real-world implications for practitioners, institutions, and publics in Australia and elsewhere. 

A wide range of technical solutions collectively understood as authenticity infrastructure promise to address these issues; but if adopted and embedded at scale, some of these solutions could have potentially significant downstream effects on stakeholders and implications for society.

This project will critically examine the assumptions underpinning these developments and debates, assess the technical and legal challenges associated with them, and explore novel technical responses that contribute to more responsible, ethical and inclusive ADM systems.

In doing so, the project will draw on the multidisciplinary  expertise of the Centre and our partners explore authenticity as both a socio-technical challenge and as a contested cultural idea. We address these challenges in practical and experimental ways within the innovative and Generative AI Test Range environment. It will also examine what happens after any determination of authenticity, including mechanisms for explaining and communicating determinations and increasing trust in such measures.

PROJECT OBJECTIVES

  • Produce a cross-disciplinary understanding of the problem of authenticity in the context of Generative AI;
  • Study and map the field of Authenticity-as-a-Service (AaaS), providing a detailed account of its infrastructure, operations, and political economy; 
  • Analyse how the integration of authenticity infrastructure is already playing out in practice in specific sectors, and impacting or likely to impact specific communities;
  • Within the Generative AI Test Range environment, simulate and evaluate competing ADM techniques for addressing the problem of authenticity in a range of real-world scenarios; and
  • Build on our findings to develop improved tools and techniques, and produce and share guidelines for explanation and communication for a range of stakeholders and audiences.

MORE INFORMATION

RESEARCHERS

ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Project Co-Leader and Chief Investigator,
QUT

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ADM+S Chief Investigator Christopher Leckie

Prof Christopher Leckie

Project Co-Leader and Chief Investigator,
University of Melbourne

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ADM+S Chief Investigator Anthony McCosker

Prof Anthony McCosker

Project Co-Leader and Chief Investigator,
Swinburne University

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Michael Richardson

Assoc Prof Michael Richardson

Project Co-Leader and Associate Investigator,
UNSW

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Jake Goldenfein

Dr Jake Goldenfein

Chief Investigator,
University of Melbourne

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Prof Flora Salim

Prof Flora Salim

Chief Investigator,
UNSW

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Jeffrey Chan

Assoc Prof Jeffrey Chan

Associate Investigator,
RMIT University

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ADM+S Investigator Sarah Erfani

Dr Sarah Erfani

Associate Investigator,
University of Melbourne

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ADM+S Investigator Timothy Graham

Assoc Prof Timothy Graham

Associate Investigator,
QUT

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Dr Ariadna Matamoros-Fernández

Associate Investigator,
QUT

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Dr Aaron Snoswell

Dr Aaron Snoswell

Associate Investigator,
QUT

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ADM+S partner investigator Wiebke Loosen

Prof Wiebke Loosen

Partner Investigator
Hans Bredow Institut

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ADM+S Investigator Julia Stoyanovich

Assoc Prof Julia Stoyanovich

Partner Investigator,
New York University

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Ned Watt

Ned Watt

PhD Student,
QUT

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Daniel Binns

Dr Daniel Binns

Affiliate,
RMIT University

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William He

Will He

Affiliate,
QUT

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Dr Silvia Montaña-Niño profile picture

Dr Silvia Montaña-Niño

Affiliate,
University of Melbourne

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Luke Munn

Dr Luke Munn

Affiliate,
The University of Queensland

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Michelle Riedlinger

Dr Michelle Riedlinger

Affiliate,
QUT

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TJ Thomson

Dr TJ Thomson

Affiliate,
RMIT University

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Kevin Witzenberger

Dr Kevin Witzenberger

Affiliate,
QUT

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PARTNERS

ABC logo

Australian
Broadcasting
Corporation

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Hans Bredow Institut Logo

Hans Bredow
Institut

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GenAISim: Simulation in the Loop for Multi-Stakeholder Interactions with Generative Agents

PROJECT SUMMARY

GenAISim: Simulation in the Loop for Multi-Stakeholder Interactions with Generative Agents

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

Traditional decision-making processes often struggle to adapt to the dynamic and multifaceted nature of the modern world. This research addresses a higher-level profound need for advanced automated decision-making tools that can address complex, context-rich challenges in society.

This project will investigate a hybrid decision-making system, leveraging cooperative knowledge from multiple stakeholders through socio-technical observations, and knowledge priors in Large Language Models (LLMs) and open datasets.

It will develop GenAISim, a novel suite of generative and data driven simulations, useful for depicting current and future urban scenarios, including in mobility, urban policymaking, and health domains. Through a multidisciplinary sociotechnical framework of investigation, this project will establish a new simulation in the loop paradigm.

PROJECT OBJECTIVES

  • Explore LLM agent-based synthetic data generation techniques to simulate and augment human behaviours in diverse contexts;
  • Develop a robust framework for hypothesis testing of real-world observations and relationships, while avoiding spurious correlations;
  • Investigate diverse stakeholder settings, often with nonoverlapping and potentially conflicting objectives, priorities, constraints, incentives and pain points; and
  • Explore questions around hybrid decision making – if an LLM agent is substituting for a decision maker in contexts.

MORE INFORMATION

RESEARCHERS

Prof Flora Salim

Prof Flora Salim

Project Co-Leader and Chief Investigator,
UNSW

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Hao Xue

Dr Hao Xue

Project Co-Leader and Associate Investigator,
UNSW

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Kim Weatherall

Prof Kimberlee Weatherall

Project Co-Leader and Chief Investigator,
University of Sydney

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Sarah Pink

Prof Sarah Pink

Project Co-Leader and Chief Investigator,
Monash University

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Daniel Angus

Prof Daniel Angus

Project Co-Leader and Chief Investigator,
QUT

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Jeffrey Chan

Assoc Prof Jeffrey Chan

Project Co-Leader and Chief Investigator,
RMIT University

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Jake Goldenfein

Dr Jake Goldenfein

Chief Investigator,
University of Melbourne

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ADM+S Chief Investigator Christopher Leckie

Prof Christopher Leckie

Chief Investigator,
University of Melbourne

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ADM+S Investigator Sarah Erfani

Dr Sarah Erfani

Associate Investigator,
University of Melbourne

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Danula Hettiachchi

Dr Danula Hettiachchi

Associate Investigator,
RMIT University

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Debora Lanzeni

Dr Debora Lanzeni

Associate Investigator,
Monash University

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ADM+S Chief Investigator Falk Scholer

Prof Falk Scholer

Associate Investigator,
RMIT University

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Dr Aaron Snoswell

Dr Aaron Snoswell

Associate Investigator,
QUT

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Dr Damiano Spina

Dr Daminao Spina

Associate Investigator,
RMIT University

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Maarten de Rijke

Prof Maarten de Rijke

Partner Investigator,
University of Amsterdam

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ADM+S Partner Investigator Ouri Wolfson

Prof Ouri Wolfson

Partner Investigator,
University of Illinois

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Shohreh Deldari

Dr Shohreh Deldari

Research Fellow,
UNSW

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Tiberio Caetoano

Prof Tiberio Caetano

Affiliate,
Gradient Institute

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PARTNERS

Bendigo Health logo

Bendigo
Hospital

Visit website

Halmstad University logo

Halmstad
University

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University of Amsterdam logo

University of
Amsterdam

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COLLABORATORS

Gradient Institute logo

Gradient Institute

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University of Illinois

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Critical Capabilities for Inclusive AI

PROJECT SUMMARY

Critical Capabilities for Inclusive AI

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

Inclusive AI is related to, but distinct from Responsible AI and the ethical principles and governance frameworks currently in development. At base it involves ensuring that all members of society benefit from AI tools and ADM systems and can participate in their design or respond to their deployment. We see capabilities – machine and human – as central to how inclusive AI might be achieved.

While much of the research focus is currently targeting the features, functions and ‘use cases’ of LLMs and other AI model types, not enough emphasis is placed on the ‘human factors’ or the co-learning and socialisation taking place in real-world settings and among different groups using these tools and systems.

This project addresses the knowledge, skills and literacies – the critical capabilities – needed to achieve inclusive AI in Australia. It will work with research partners, consumers and communities to better understand the capabilities and resources needed to access and use AI tools including Generative AI. Central to the project is the AI Capabilities Lab, a platform and space to experiment, observe and evaluate the use of new AI tools with our industry partners and members of the public.

Through the AI capabilities Lab and participatory research methods, the project will build an evidence base about the shifting lines of expertise, knowledge and decision making in organisational and everyday life settings as people begin to use AI tools.

PROJECT OBJECTIVES

  • Develop a model of AI capability and literacy for AI inclusion, tested with key domain areas and target populations;
  • Generate empirical evidence about the way people and organisations are using AI tools, and their potential for alleviating or deepening digital inequalities;
  • Co-design resources with partner organisations and their communities and consumers to enhance inclusive AI literacy and capability and foster responsible forms of ‘social governance’ for AI use and ADM processes; and
  • Develop and test AI capability and usage metrics, test and evaluate AI tools and systems through user studies and explore meta-evaluation approaches for targeted AI tools and applications.

MORE INFORMATION

RESEARCHERS

ADM+S Chief Investigator Anthony McCosker

Prof Anthony McCosker

Project Co-Leader and Chief Investigator,
Swinburne University

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Distinguished Professor Julian Thomas

Prof Julian Thomas

Project Co-Leader and Chief Investigator,
RMIT University

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Kath Albury

Prof Kath Albury

Project Co-Leader and Associate Investigator,
Swinburne University

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Chief Investigator,
QUT

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Paul Henman headshot

Prof Paul Henman

Chief Investigator,
The University of Queensland

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Prof Jackie Leach Scully

Chief Investigator,
UNSW

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Deborah Lupton

Prof Deborah Lupton

Chief Investigator,
QUT

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Haiqing Yu

Prof Haiqing Yu

Chief Investigator,
RMIT University

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Danula Hettiachchi

Dr Danula Hettiachchi

Associate Investigator,
RMIT University

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James Meese

Assoc Prof James Meese

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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Sharon Parkinson

Assoc Prof Sharon Parkinson

Associate Investigator,
Swinburne University

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Dr Damiano Spina

Dr Daminao Spina

Associate Investigator,
RMIT University

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Rowan Wilken

Assoc Prof Rowan Wilken

Associate Investigator,
RMIT University

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ADM+S Investigator Julia Stoyanovich

Assoc Prof Julia Stoyanovich

Partner Investigator,
New York University

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Daniel Featherstone

Dr Daniel Featherstone

Research Fellow,
RMIT University

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Dr Awais Hameed Khan

Research Fellow,
The University of Queensland

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Yong-Bin Kang

Dr Yong-Bin Kang

Research Fellow,
Swinburne University

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Amanda Lawrence

Dr Amanda Lawrence

Affiliate,
RMIT University

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TJ Thomson

Dr TJ Thomson

Affiliate,
RMIT University

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Xiaofang Yao

Dr Xiaofang Yao

Afilliate,
Federation University

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PARTNERS

ABC logo

Australian
Broadcasting
Corporation

Visit website

Australian Red Cross Logo

Australian
Red Cross

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Telstra

Telstra

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NYU Ultra Violet Logo

Centre for Responsible AI
New York University

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ADM, Ecosystems and Multispecies Relationships

PROJECT SUMMARY

Person standing in front of large digital screen with landscape image

ADM, Ecosystems and Multispecies Relationships

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

Automated Decision-Making (ADM) has become increasingly implicated in the relationships between people and other species and ecosystems. From delivery drones to digital bioacoustics, smart farming, smart garbage trucks to conservation and computation, proliferating ADM-enabled technologies are situated within and interact in complex ways with both social and eco-systems to create new mediations between humans, technologies, animals, and environments with diverse and unexpected consequences.

This project will make an innovative and transformational contribution to the advancement of knowledge about the impacts and entanglements of ADM with ecosystems and the capacity of institutions to make responsible decisions about ADM implementations, practices, and assessments.

 Drawing on interdisciplinary socio-technical research practices, researchers will undertake an inclusive approach that brings together diverse knowledges, methods, and sites. In collaboration with partners and communities this project will produce the ADM+Ecosystem Playbook, a policy and practice tool kit that includes addressing the potential for an environmental impact assessment legislative, policy and standards framework for ADM in Australia.

This project will intervene in the ongoing debates about ‘safe and responsible AI’ to critically examine the ecosystem impacts of ADM/AI and prioritise sustainable futures that benefit society and more-than-human ecologies alike.

PROJECT OBJECTIVES

  • To deliver an original account of how entanglements between ADM systems, diverse human stakeholder groups, other non-human species and Australian ecosystems/environments are evolving, with particular attention to Australia’s unique exposure to climate extremes of heat, drought, flood, and fire and demands of automated technologies to cover distance;
  • To generate new experimental and arts practice based methodologies for investigating, representing and creating public and diverse stakeholder engagement with the relationship between humans, other species and ADM systems, including challenges of environmentally responsible ADM; and
  • To produce accessible, practical recommendations for policies and standards that enable industry, government, civil society and advocacy organisations to apply a responsible and sustainable approach to relations between ADM systems, eco systems and other species, with the aim of intervening in the discourse, conception, and implementation of ‘safe and responsible AI’ and the wider public and civil society understanding of ADM and its impacts.

MORE INFORMATION

RESEARCHERS

ADM+S Investigator Christine Parker

Prof Christine Parker

Project Co-Leader and Chief Investigator,
University of Melbourne

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Deborah Lupton

Prof Deborah Lupton

Project Co-Leader and Chief Investigator,
UNSW

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Michael Richardson

Assoc Prof Michael Richardson

Project Co-Leader and Associate Investigator,
UNSW

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Sarah Pink

Prof Sarah Pink

Project Co-Leader and Chief Investigator,
Monash University

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Yolande Strengers

Prof Yolande Strengers

Project Co-leader and
Associate Investigator,
Monash University
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Loup Cellard

Dr Loup Cellard

Affiliate,
Datactivist/Sciences Partner Organisation
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ADM+S Investigator Fiona Haines

Prof Fiona Haines

Affiliate,
University of Melbourne

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Luke Munn

Dr Luke Munn

Affiliate,
University of Queensland
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James Parker

Assoc Prof James Parker

Affiliate,
University of Melbourne

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PARTNERS

Consumer Policy Research Centre Logo

Consumer Policy
Research Centre

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COLLABORATORS

CHOICE

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AI ReWired: How communities are using AI to Support Social and Environmental Justice

PROJECT SUMMARY

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AI ReWired: How communities are using AI to Support Social and Environmental Justice

Focus Areas: News & Media, Mobilities, Health
Research Program: People
Status: Completed

The future we are being sold is an automated wonderland, a techtopia that will use algorithms to heal our ecological crisis and restore social justice. A dream world where we enjoy endless innovation and growth in sparkling smart cities, where we are liberated from the burden of work, where the future of our species lies in billionaire funded missions to Mars.

But what if this promise sounds more like a nightmare?
What are the alternatives?

The AI ReWired project uses co-creative documentary film practice to uncover how diverse communities utilise AI systems to protect the environment, support social justice and promote fairness in their communities.

RESEARCHERS

Jeni Lee

Jeni Lee

Lead Investigator,
Monash University

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ADM+S Chief Investigator Sarah Pink

Prof Sarah Pink

Chief Investigator,
Monash University

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Dr Damiano Spina

Dr Damiano Spina

Associate Investigator,
RMIT University

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Yolande Strengers

Prof Yolande Strengers

Associate Investigator,
Monash University

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Georgia Van Toorn

Dr Georgia van Toorn

Associate Investigator,
UNSW

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Thao Phan

Dr Thao Phan

Research Fellow,
Monash University

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Emma Quilty

Dr Emma Quilty

Affiliate,
Monash University

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Melissa Gregg

De Mel Gregg

Senior Industry Fellow,
RMIT

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Nonie May

Dr Nonie May

Project support,
Monash University

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Humans, Machines, and Decision Responsibility

PROJECT SUMMARY

Businessman using cell phone on subway train

Humans, Machines, and Decision Responsibility

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

Automated decision-making provokes a range of anxieties around transparency, equality, and accountability. A key response has been the call to ‘re-humanise’ automated decisions, with the hope that human control of automated systems might defend human values from mindless technocracy. Regulation of automated decision-making and AI often embeds this form of human centrism by prescribing a ‘human in the loop’ and the need for automated decisions to be ‘explained’. These requirements are central elements of the risk-based approaches AI regulation currently in development.

Despite their intuitive appeal, empirical research is revealing the limitations and complexities of these approaches. AI explanations sometimes provide little that is useful for decision subjects or decision makers, and risk distracting from more meaningful interrogation of why decisions are made. A human in the loop sometimes functions as a rubber stamp for automated decisions, cleaving accountability away from the true sites of decision responsibility.

This project seeks to generate better understandings of the functions, capacities, and normative role of humans within automated decision systems. It will investigate the ways that automated systems ought to explain or be explained to humans within decision processes, and how elements of decision-making including processes, responsibility, authority, and what counts as a decision itself, are fragmented and redistributed between humans, machines, and organisations. The goal is to generate empirical knowledge of how automated systems, humans, and organisations interact in different contexts when making decisions, and to move past outdated understandings of decisions-making that are hindering effective governance of automation in new decision contexts.

RESEARCHERS

Jake Goldenfein

Dr Jake Goldenfein

Lead Investigator,
University of Melbourne

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Chief Investigator,
QUT

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Paul Henman headshot

Prof Paul Henman

Chief Investigator,
University of Queensland

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ADM+S Chief Investigator Christopher Leckie

Prof Chris Leckie

Chief Investigator,
University of Melbourne

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Prof Flora Salim

Prof Flora Salim

Chief Investigator,
UNSW

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Distinguished Professor Julian Thomas

Prof Julian Thomas

Chief Investigator,
RMIT University

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Kim Weatherall

Prof Kim Weatherall

Chief Investigator,
University of Sydney

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Henry Fraser

Dr Henry Fraser

Research Fellow,
QUT

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Dr Awais Hameed Khan

Research Fellow,
UQ

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Fan Yang

Dr Fan Yang

Research Fellow,
University of Melbourne

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Libby Young

Libby Young

PhD Student
University of Sydney

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Joe Brailsford

Joe Brailsford

Affiliate
University of Melbourne

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Fabio Mattioli

Dr Fabio Mattioli

Affiliate
University of Melbourne

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Christopher O'Neill

Dr Chris O’Neil

Affiliate,
Deakin University

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Ash Watson

Dr Ash Watson

Affiliate,
UNSW

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Australian Digital Inclusion Index

PROJECT SUMMARY

Australian Digital Inclusion Index

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

Digital inclusion is about ensuring that all Australians can access and use digital technologies effectively. We are experiencing an accelerating digital transformation in many aspects of economic and social life. Our premise is that everyone should have the opportunity to benefit from digital technologies: to manage their health, access education and services, participate in cultural activities, organise their finances, follow news and media, and connect with family, friends, and the wider world.

The Australian Digital Inclusion Index (ADII or “Index”) uses survey data to measure digital inclusion across three dimensions of Access, Affordability and Digital Ability. We explore how these dimensions vary across the country and across different social groups.

In partnership with Telstra and through biennial data collections presented through reports and data visualisation dashboards, the ADII is capturing and communicating the evolving state of digital inclusion in Australia. This is complemented by aligned sub-projects with local, state and federal government departments and community partners to drill down into specific digital inclusion challenges for social groups or geographical regions of interest.

A detailed measure of digital inclusion for Australia allows us to identify the critical barriers to inclusion. These may be related to accessing networks, the costs of devices or data, or skills and literacies. Through these measures, the Index shapes digital equity policy and initiatives, research, and practice to increase digital inclusion in Australia.

Visit the ADII website 

MORE INFORMATION

The Australian Digital Inclusion Index uses data from the ADM+S project, Mapping the Digital Gap. Learn more from the project brief below.

PUBLICATIONS

Uncovering digital divide in the western parkland city

Uncovering the digital divide in the Western Parkland City

ADM+S, Telstra, NSW Government, Sydney’s Parkland Councils

Report

Measuring Australia’s Digital Divide: 2023 Australian Digital Inclusion Index

ADM+S and Telstra

Report

Telstra Connected Students: Lessons for Digital Inclusion, 2022

ADM+S and Telstra

Report

Australian Digital Inclusion Index: Measuring Digital Inclusion in North-East Victorian SMEs Summary Findings Brief, 2022

Thomas, J., Parkinson, S., et al.

Report

2021 Digital Inclusion Index

ADM+S and Telstra

Report

RESEARCHERS

ADM+S Chief Investigator Anthony McCosker

Prof Anthony McCosker

Chief Investigator,
Swinburne University

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Distinguished Professor Julian Thomas

Prof Julian Thomas

Chief Investigator,
RMIT University

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Jenny Kennedy

Assoc Prof Jenny Kennedy

Associate Investigator,
RMIT University

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Sharon Parkinson

Dr Sharon Parkinson

Associate Investigator,
Swinburne University

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Daniel Featherstone

Dr Daniel Featherstone

Senior Research Fellow,
RMIT University

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Lyndon Ormond-Parker

Assoc Prof Lyndon Ormond-Parker

Senior Research Fellow,
RMIT University

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Kieran Hegarty

Dr Kieran Hegarty

Research Fellow,
RMIT University

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RESEARCH SUPPORT

Lucy Valenta profile image

Lucy Valenta

Research Coordinator,
RMIT University

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PARTNERS

Telstra

Telstra

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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

CHOICE

Visit website

Consumer Policy Research Centre Logo

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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Kelly Lewis

Dr Kelly Lewis

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

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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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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Risk, Rule-setters and Rule-takers: Regulatory approaches to risk in AI-supported and AI-automated decision-making for general welfare

PROJECT SUMMARY

Crowd in motion in busy precinct

Risk, Rule-setters and Rule-takers: Regulatory approaches to risk in AI-supported and AI-automated decision-making for general welfare

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

This project seeks to scope several approaches to deal with Automated Decision-Making and Decision-Support Systems-Related Risks (ADM/DSS RR) through norms and provide an evaluation of those approaches for their consideration in regulatory contexts.

The standpoint is to look at risk control of those systems beyond ethics or social principles and focus the discussion on the possible interventions from the regulator’s perspective.

The overarching questions and sub-questions guiding this project are:

  • What is risk in an ADM / DS System?
    – Is it possible to define it?
    – How is it different from technological risk?
    – How is it different from the concept of risk in
    management?
    – Are all “potential harms” risks of and ADM/DSS?
    – Is there a concept of risk usable for regulatory
    purposes?
  • What types of risks are common and which ones specific to ADM/DSS?
    – Due to the nature of the risk?
    – Due to the scale of the risk?
  • What is an acceptable risk:
    – From the point of view of society as a whole
    – From the point of view of the most vulnerable groups
    – From the point of view of the owner of the AI system
    – From the point of view of the users of the system
  • Can risk be separated from questions of liability/ responsibility or do they need to be regulated together?

PUBLICATIONS

Acceptable risks in Europe’s Proposed AI Act: Reasonableness and other principles for deciding how much risk management is enough, 2023

Bello y Villarino, J.M., Fraser, H.

Journal article

The Tale of Two Automated States: Why one-size-fits-all approach to administrative law reform to accommodate AI will fail, 2023

Bello y Villarino, J.M.

Book chapter

International Human Rights, Artificial Intelligence, and the Challenge for the Pondering State: Time to Regulate? 2022

Bello y Villarino, J.M., et al.

Journal article

Legal Issues Around Autonomous Systems – Civil Liability, Fault and System Safety, 2022

Fraser, H.

Conference paper

AI Opacity and Explainability in Tort Litigation, 2022

Snoswell, A., Fraser, H., Simcock, R.

Conference paper

Where residual risks reside: A comparative approach to art 9(4) of the EU’s Proposed AI Regulation, 2021

Bello y Villarino, J.M, Fraser, H.

Working paper

RESEARCHERS

Kimberlee Weatherall

Prof Kimberlee Weatherall

Chief Investigator,
University of Sydney

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ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Chief Investigator,
QUT

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José-Miguel Bello y Villarino

Dr José-Miguel Bello Villarino

Research Fellow,
University of Sydney

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Henry Fraser

Dr Henry Fraser

Research Fellow,
QUT

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PARTNERS

Gradient Institute logo

Gradient Institute

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Big Data, Sexual Surveillance and Alternative Governance

PROJECT SUMMARY

Woman using ipad in bed

Big Data, Sexual Surveillance and Alternative Governance

Focus Area: Health
Research Programs: Institutions
Status: Active

The contested governance of sexual technologies – from apps and platforms to bots and devices – provides a unique case study through which to identify current problems in automated decision-making and to generate new principles, values and approaches. This project will examine existing practices in the collection and use of sexual data by both private and public actors.

It will investigate how algorithms are taught to understand sex, gender and sexuality through digital proxies and their potential to amplify discrimination. It will explore alternative frameworks for governing sexual technologies, including collective approaches to content moderation and data governance.

PUBLICATIONS

High Risk Hustling: Payment Processors Sexual Proxies and Discrimination by Design (2023)

Dr Zahra Stardust, Danielle Blunt, Gabriella Garcia, et al.

Journal article

Submission to the Meta Oversight Board RE Gender, Identity and Nudity (2023)

Dr Zahra Stardust

Submission

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

Dr Zahra Stardust, Dr Rosalie Gillett and Prof Jean Burgess

Journal article

Manifesto for sex positive social media (2022)

Dr Zahra Stardust  Zahra, Emily van der Nagel, Katrin  Tiidenberg, et al.

Report

Automating Whorephoia: Sex, Technology and the Violence of Deplatforming (2021)

Dr Zahra Stardust and Danielle Blunt

Journal article

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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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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Public Interest Litigation for AI Accountability

PROJECT SUMMARY

Woman sitting down with laptop

Public Interest Litigation for AI Accountability

Focus Areas: News and Media, Health, Social Services, Transport and Mobilities
Research Program: Institutions
Status: Active

If you have been harmed by bad automated decision-making, from robots to loan assessments, what can you do to right the wrong? What can the law do to help you? A growing number of public controversies about discriminatory, unpredictable and dangerous automated decision-making has raised questions about the most effective methods of accountability.

Through qualitative interviews with stakeholders (including class action and pro bono lawyers), this project seeks to identify the opportunities, enablers and barriers for public interest litigation to promote accountability and fairness in automated decision-making.

RESEARCHERS

ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Lead Investigator,
QUT

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Henry Fraser

Dr Henry Fraser

Research Fellow,
QUT

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Zahra Stardust profile picture

Dr Zahra Stardust

Research Fellow,
QUT

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Ecological Implications of Data Centres

PROJECT SUMMARY

Data centre

Ecological Implications of Data Centres

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

The project seeks to understand how companies, public agencies and civil society address the environmental conditions and limitations facing the establishment and management of data centres and submarine cables in urban and coastal areas.

A central part of data centre management is heat management: servers produce heat, and as they are gathered in large numbers in close areas, temperatures rise raising the risk of fire. To overcome this, data centre operators have various techniques to cool down these facilities and avoid any risks of data loss caused by fires. Moreover, when landing, telecom subsea cables risk to damage the local biodiversity (especially marine plants).

Thus, this project will ask: what shapes the environmental impacts of data centres cooling infrastructures? What are the ecological implications involved with the landing of a telecom submarine cable or the creation of a new data centre? How are these ecological impacts made visible to stakeholders? To what extent do environmental assessments succeed in reconciling the various interests at stake (security of infrastructures, maritime trade, marine biodiversity) in the passage of a telecomunication cable? How do ecological and infrastructural vulnerabilities of both data centers and telecom submarine cables shape the world-wide interconnection of data at the heart of the digital economy?

In order to address this question, we will take as a case study the rapid growth of data centres and telecommunication subsea cables in Marseille (France), which is particularly interesting as this city is in a warm climate, making the issue of heat management more difficult there than in the north of Europe.

This project is conducted by ADM+S Research Fellow Dr Loup Cellard in collaboration with Dr Clément Marquet (Mines Paris).

PUBLICATIONS

Just Transitions in Australia: Moving Towards Low Carbon Lives Across Policy, Industry and Practice, 2022

Parker, C., Haines, F., et al.

Submission

RESEARCHERS

ADM+S Investigator Christine Parker

Prof Christine Parker

Lead Investigator,
University of Melbourne

Learn more

ADM+S Investigator Karen Yeung

Prof Karen Yeung

Partner Investigator,
University of Birmingham

Learn more

Loup Cellard

Dr Loup Cellard

Affiliate,
Datactivist Coop

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ADM+S Investigator Fiona Haines

Prof Fiona Haines

Affiliate,
University of Melbourne

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PARTNERS

Université de Technologie de Compiègne Logo

Université de Technologie de Compiègne

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University of Birmingham

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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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Transparent Machines: From Unpacking Bias to Actionable Explainability

PROJECT SUMMARY

Person typing on computer

Transparent Machines: From Unpacking Bias to Actionable Explainability

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

ADMs, their software, algorithms, and models, are often designed as “black boxes” with little efforts placed on understanding how they work. This lack of understanding does not only impact the final users of ADMs, but also the stakeholders and the developers, who need to be accountable for the systems they are creating. This problem is often exacerbated by the inherent bias coming from the data from which the models are often trained on.

Further, the wide-spread usage of deep learning models has led to increasing number of minimally-interpretable models being used, as opposed to traditional models like decision trees, or even Bayesian and statistical machine learning models.

Explanations of models are also needed to reveal potential biases in the models themselves and assist with their debiasing.

This project aims to unpack the biases in models that may come from the underlying data, or biases in software (e.g. a simulation) that could be designed with a specific purpose and angle from the developers’ point-of-view. This project also aims to investigate techniques to generate diverse, robust and actionable explanations for a range of problems and data types and modality, from large-scale unstructured data, to highly varied sensor data and multimodal data. To this end, we look to generate counterfactual explanations that have a shared dependence on the data distribution and the local behaviour of the black-box model by level, and offer new metrics in order to measure the opportunity cost of choosing one counterfactual over another. We further aim to explore the intelligibility of different representations of explanations to diverse audiences through an online user study.

PUBLICATIONS

i-Align: An Interpretable Knowledge Graph Alignment Model, 2023

Salim, F., Scholer, F., et al.

Journal article

TransCP: A Transformer Pointer Network for Generic Entity Description Generation with Explicit Content-Planning, 2023

Salim, F., et al.

Journal article

Contrastive Learning-Based Imputation-Prediction Networks for In-hospital Mortality Risk Modeling Using EHRs, 2023

Salim, F., et al.

Conference paper

How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies, 2023

Small, E., Chan, J., et al.

Journal article

Equalised Odds is not Equal Individual Odds: Post-processing for Group and Individual Fairness, 2023

Small, E., Sokol, K., et al.

Conference paper

Helpful, Misleading or Confusing: How Humans Perceive Fundamental Building Blocks of Artificial Intelligence Explanations, 2023

Small, E., Xuan, Y., et al.

Workshop paper

Navigating Explanatory Multiverse Through Counterfactual Path Geometry, 2023

Small, E., Xuan, Y., Sokol, K.

Workshop paper

Mind the gap! Bridging explainable artificial intelligence and human understanding with Luhmann’s Functional Theory of Communication, 2023

Sokol, K., et al.

Workshop paper

Measuring disentangled generative spatio-temporal representation, 2022

Chan, J., Salim, F., et al.

Conference paper

FAT Forensics: A Python toolbox for algorithmic fairness, accountability and transparency, 2022

Sokol, K., et al.

Journal article

Analysing Donors’ Behaviour in Non-profit Organisations for Disaster Resilience: The 2019–2020 Australian Bushfires Case Study, 2022

Chan, J., Sokol, K., et al.

Conference paper

BayCon: Model-agnostic Bayesian Counterfactual Generator, 2022

Sokol, K., et al.

Conference paper

RESEARCHERS

ADM+S Investigator Flora Salim

Prof Flora Salim

Lead Investigator,
UNSW

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Daniel Angus

Prof Daniel Angus

Chief Investigator,
QUT

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ADM+S Chief Investigator Paul Henman

Prof Paul Henman

Chief Investigator,
University of Queensland

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ADM+S Chief Investigator Mark Sanderson

Prof Mark Sanderson

Chief Investigator,
RMIT University

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Jeffrey Chan

Dr Jeffrey Chan

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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ADM+S Investigator Maarten de Rijke

Prof Maarten de Rijke

Partner Investigator,
University of Amsterdam

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Peibo Li

Peibo Li

PhD Student,
UNSW

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Edward Small

Edward Small

PhD Student,
RMIT University

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Kacper Sokol

Kacper Sokol

Affiliate,
ETH Zurich

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PARTNERS

University of Amsterdam logo

University of Amsterdam

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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

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

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PARTNERS

ABC logo

Australian Broadcasting Corporation

Visit website

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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Governing ADM Use

PROJECT SUMMARY

Blurred people in busy precinct

Governing ADM Use

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

The Governing ADM Use Project was an ‘umbrella’ project designed to seed the work of the ADM+S Institutions program in the rapidly evolving area of ADM and AI regulation. The project conceives the challenge of governing ADM use as a multi layered network incorporating the regulation of the use of ADM by government authorities, the regulation by government of ADM use in the commercial and private sector, and the interaction of ADM-specific regulation and governance with a range of other areas of law, regulation and governance that impinge and interact (more or less directly) with the specific governance of ADM/AI.

This latter category extends from data and privacy regulation to competition and consumer protection and beyond to sector and problem specific areas of regulation such as energy regulation, worker health and safety, labour force regulation and importantly environmental and planning laws. This program of work has sought to understand the special role of law as well as broader influences on public and private sector ADM use, and how these change – or need to change – to respond to the impacts of automation. A particular feature of this program of work has been to expand our understanding of the eco-system of law and governance properly concerned with regulating ADM/AI to include how we govern the ecological impact of ADM/AI use.

PUBLICATIONS

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

Coghlan, S., Parker, C.

Journal article

Data problems and legal solutions – some thoughts beyond privacy, 2023

Weatherall, K., et al.

Book chapter

Reconstituting the Contemporary Corporation Through Ecologically Responsive Regulation, 2022

Parker, C., Haines, F.

Journal article

From ‘Corporate Governance’ to Ecological Regulation: Flipping the Regulatory Story on Climate Change, 2022

Parker, C.

Journal article

Algorithms as Figures. Towards a post-digital ethnography of algorithmic contexts, 2022

Cellard, L.

Journal article

The crimes of digital capitalism, 2022

Jiménez, A.

Journal article

Just Transitions in Australia: Moving Towards Low Carbon Lives Across Policy, Industry and Practice, 2022

Parker, C., Haines, F., et al.

Submission

More on Convening Technology: Blockchain, Fashion, and the Right to Know, 2022

Richardson, M., et al.

Journal article

Australian Competition and Consumer Commission, Digital Platform Services Inquiry Discussion Paper for Interim Report No 5: Updating competition and consumer law for digital platform services, 2022

Weatherall, K., et al.

Submission

Online Privacy Bill Consultation Submission, 2022

Goldenfein, J., Weatherall, K., Parker, C.

Submission

Submission in response to the Privacy Act Review, 2022

Weatherall, K., Trezise, M.

Submission

Submission to the Statutory Reviewer on the Consumer Data Right, 2022

Weatherall, K., Bednarz, Z., Dolman, C.

Submission

Submission on the Commonwealth Government Trusted Digital Identity Framework Position Paper, 2021

Weatherall, K.

Submission

RESEARCHERS

ADM+S Investigator Christine Parker

Prof Christine Parker

Lead Investigator,
University of Melbourne

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Lead Investigator,
University of Melbourne

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Jake Goldenfein

Dr Jake Goldenfein

Chief Investigator,
University of Melbourne

Learn more

Kim Weatherall

Prof Kim Weatherall

Chief Investigator,
University of Sydney

Learn more

ADM+S Investigator Karen Yeung

Prof Karen Yeung

Partner Investigator,
University of Birmingham

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José-Miguel Bello y Villarino

Dr José-Miguel Bello y Villarino

Research Fellow,
University of Sydney

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Henry Fraser

Dr Henry Fraser

Research Fellow,
QUT

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Loup Cellard

Dr Loup Cellard

Affiliate,
Datactivist Coop

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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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Democratic Practices of Governance Given ADM

PROJECT SUMMARY

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Democratic Practices of Governance Given ADM

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

This project examines possibilities for democratic practice, institutions and governance given automated decision-making (ADM). It focuses on challenges to and opportunities for liberal and democratic institutions and governance presented by ADM. The project aims to bridge analysis of ADM’s deployment across different domains with scholarly literature on republican and positive freedom, the rule of law and liberal democratic rights.

Overall, the project seeks to develop a theoretically rich analysis of democracy and freedom given ADM and apply the analysis to specific examples of current regulatory and democratic challenge.

PUBLICATIONS

Just Transitions in Australia: Moving Towards Low Carbon Lives Across Policy, Industry and Practice, 2022

Parker, C., Haines, F.

Submission

Privacy in the Republic, 2022

Kenyon, A.

Book

Countering hate speech in context: positive freedom of speech, 2022

de Silva, A., Kenyon, A.

Journal article

Law as Counterspeech, 2022

de Silva, A., et al.

Journal article

A Platformed Response to Hate Speech Against Women, 2022

de Silva, A.

Journal article

Introduction: Conceptualisations of Violence, 2022

de Silva, A., et al.

Book Chapter

The Crimes of Digital Capitalism, 2022

Jiménez, A.

Journal article

Law, Code and Exploitation: How Corporations Regulate the Working Conditions of the Digital Proletariat, 2022

Jiménez, A.

Journal article

The Australian News Media Bargaining Code, 2021

Goldenfein, J.

Analysis brief

Democracy of ExpressionPositive Free Speech and Law, 2021

Kenyon, A.

Book

Hate Speech Against Women: Addressing a Democratic Crisis, 2021

de Silva, A.

Policy brief

Positive Free Speech: A Democratic Freedom, 2021

Kenyon, A.

Book chapter

Surveillance Punitivism: Colonialism, Racism, and State Terrorism in Spain, 2021

Jiménez, A.

Journal article

Privacy, Punishment and Private Law, 2021

Roberts, A., Richardson, M.

Book chapter

Digital capitalism, what are the possible alternatives? 2021

Jiménez, A., et al.

Journal article

Adtech and children’s data rights, 2021

Archbold, L., Clifford, D., et al.

Journal article

Children’s Privacy in Lockdown: Intersections between Privacy, Participation and Protection Rights in a Pandemic, 2021

Archbold, L., Clifford, D., et al.

Journal article

Esports and the Platforming of Children’s During COVID-19, 2021

Fordyce, R., Archbold, L., et al.

Journal article

RESEARCHERS

ADM+S Investigator Christine Parker

Prof Christine Parker

Lead Investigator,
University of Melbourne

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Mark Andrejevic

Prof Mark Andrejevic

Chief Investigator,
Monash University

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Jake Goldenfein

Dr Jake Goldenfein

Chief Investigator,
Melbourne University

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Distinguished Professor Julian Thomas

Prof Julian Thomas

Chief Investigator,
RMIT University

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ADM+S Investigator Sarah Erfani

Dr Sarah Erfani

Associate Investigator,
University of Melbourne

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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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Anjalee de Silva

Dr Anjalee de Silva

Research Fellow,
University of Melbourne

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Chathurika Akurugoda

Chathurika Akurugoda

PhD Student,
University of Melbourne

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Lisa Archbold

Lisa Archbald

PhD Student,
University of Melbourne

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Phoebe Galbally

Phoebe Galbally

PhD Student,
University of Melbourne

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Avantik Tamta

Avantik Tamta

PhD Student,
University of Melbourne

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Aitor Jiménez

Dr Aitor Jiménez

Affiliate,
University of Melbourne

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ADM+S Investigator Fiona Haines

Prof Fiona Haines

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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The Coronavirus Impact

PROJECT SUMMARY

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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

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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,
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

Affiliate,
University of Melbourne

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PARTNERS

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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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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

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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.

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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Diverse Experiences of ADM: Design, Curation and Use

PROJECT SUMMARY

Research Materials

Diverse Experiences of ADM: Design, Curation and Use

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

The ‘Diverse Experiences of ADM’ is the overarching thematic title for a collection of studies that examine the social, cultural and ethical dimensions of how people understand and experience ADM and other new and emerging technologies. This project explores how members of diverse communities shape existing, emerging and future practices of ADM in an effort to understand and develop equitable futures. Several studies address disabled people’s lived experiences of ADM and other emerging technologies and what services they would like to see introduced to better support their care and wellbeing. Others look at health technology startups and the thinking behind developers’ visions of future technologies and identify how health and medical technologies are portrayed in Australian industry websites and news reports. One strand addresses gender, sexual health and digital contraception technologies.

Digital mental health is also a focus of some of the studies conducted in this project. There is a strong emphasis on using participatory, experimental, creative and arts-based methods to conduct research and to engage in community research translation and engagement, including artworks, zines and exhibitions. There is also a more-than-human orientation across this project, identifying the entanglements of humans not only with digital devices, software and data but with other animals and living things and the physical elements of the ecosystems in which these technologies are imagined, developed, promoted, used or resisted.

PUBLICATIONS

The Internet of Animals: Human-Animal Relationships in the Digital Age, 2023

Lupton, D.

Book

Health information in creative translation: establishing a collaborative project of research and exhibition making, 2023

Watson, A., Wozniak-O’Connor, V., Lupton, D.

Journal article

More-than-Human Wellbeing, 2023

Lupton, D., Watson, A., et al.

Exhibition reader

Talking/Flowers, 2023

Watson, A.

Zine

Everyday Automation: Experiencing and Anticipating Emerging Technologies, 2022

Pink, S., Lupton, D., et al.

Book

Digitized and datafied embodiment: a more-than-human approach, 2022

Lupton, D., Clark, M., et al.

Book chapter

Everyday automation: setting a research agenda, 2022

Lupton, D., Pink, S., et al.

Book chapter

The quantified pandemic: digitised surveillance, containment and care in response to the COVID-19 crisis, 2022

Lupton, D.

Book chapter

Re-Imagining Care Through Arts-Based Methods, 2022

Watson, A., Rose, M.

Zine

The futures of qualitative research in the COVID-19 era: experimenting with creative and digital methods, 2022

Lupton, D., Watson, A., et al.

Book chapter

Remote fieldwork in homes during the COVID-19 pandemic: video-call ethnography and map drawing methods, 2022

Watson, A., Lupton, D.

Journal article

The presence and perceptibility of personal digital data: findings from a participant map drawing method, 2022

Lupton, D., Watson, A., et al.

Journal article

Research-creations for speculating about digitised automation: bringing creative writing prompts and vital materialism into the sociology of futures, 2022

Watson, A., Lupton, D.

Journal article

From human-centric digital health to digital One Health: crucial new directions for planetary health, 2022

Lupton, D.

Journal article

(Dis)assembling mental health through apps: the sociomaterialities of young adults’ experiences, 2022

Flore, J.

Journal article

The COVID digital home assemblage: transforming the home into a work space during the crisis, 2021

Watson, A., Lupton, D., et al.

Journal article

Pandemic fitness assemblages: the sociomaterialities and affective dimensions of exercising at home during the COVID-19 crisis, 2021

Clark, M., Lupton, D.

Journal article

The Lancet and Financial Times Commission on governing health futures 2030: growing up in a digital world, 2021

Lupton, D., et al.

Journal article

Living in, with and beyond the ‘smart home, 2021

Lupton, D., Pink, S., Horst, H.

Book chapter

RESEARCHERS

ADM+S Chief Investigator Heather Horst

Prof Heather Horst

Lead Investigator,
Western Sydney University

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Prof Deborah Lupton

Lead Investigator,
UNSW

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Sarah Pink

Prof Sarah Pink

Lead Investigator,
Monash University

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Prof Jackie Leach Scully

Chief Investigator,
UNSW

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Georgia Van Toorn

Dr Georgia van Toorn

Associate Investigator,
UNSW

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Cecily Klim

Cecily Klim

PhD Student,
UNSW

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Megan Rose NEW

Dr Megan Rose

PhD Student,
UNSW

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Jacinthe Flore

Dr Jacinthe Flore

Affiliate,
University of Melbourne

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PARTNERS AND COLLABORATING ORGANISATIONS

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Consumers Health Forum of Australia

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Health Consumers NSW

Health Consumers NSW

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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: 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)

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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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

OVIC Logo

Office of the Victorian Information Commissioner

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Data & Society Research Institute (US)

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Considerate and Accurate Multi-party Recommender Systems for Constrained Resources

PROJECT SUMMARY

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Considerate and Accurate Multi-party Recommender Systems for Constrained Resources

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

This project will create a next generation recommender system that enables equitable allocation of constrained resources. The project will produce novel hybrid socio-technical methods and resources to create a Considerate and Accurate REcommender System (CARES), evaluated with social science and behavioural economics lenses.

CARES will transform the sharing economy by delivering systems and methods that improve user and non-user experiences, business efficiency, and corporate social responsibility.

PARTICIPATE

Participate in an online user study on multi-party fair recommendations

We are looking for users of the Spotify music application to complete a brief online study. In the study, you are expected to browse music recommendations and answer a set of questions.

The study is expected to take less than 15 minutes, and you will receive a AU$10 gift card as a thank you.

You will need to have an active Spotify account with at least 6 months of listening history to take part.

To verify your eligibility and participate in the study, please fill out this form.

PUBLICATIONS

Are footpaths encroached by shared e-scooters? Spatio-temporal analysis of Micro-mobility services, 2023

Kegalle, H., Hettiachchi, D., et al.

Conference paper

Capacity-aware fair POI recommendation combining Transformer Neural Networks and Resource allocation Policy. Submitted to journal Knowledge Based Systems, 2023

Chan, J.

Journal article

More is Less: When do Recommender Systems Underperform for Data-rich Users? 2023

Xuan, Y., Sanderson, M., et al.

Conference paper

How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies, 2023

Small, E., Chan, J., et al.

Conference paper

RESEARCHERS

ADM+S Chief Investigator Mark Sanderson

Prof Mark Sanderson

Lead Investigator,
RMIT University

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ADM+S Chief Investigator Christopher Leckie

Prof Christopher Leckie

Chief Investigator,
University of Melbourne

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ADM+S Investigator Flora Salim

Prof Flora Salim

Chief Investigator,
UNSW

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Jeffrey Chan

Dr Jeffrey Chan

Associate Investigator,
RMIT University

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Danula Hettiachchi

Dr Danula Hettiachchi

Associate Investigator,
RMIT University

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PARTNERS

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University of Amsterdam

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Decentering ADM: A Review of Automated Decision-Making in the Global South

PROJECT SUMMARY

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Decentering ADM: A Review of Automated Decision-Making in the Global South

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

The Decentering Automated Decision-Making report offers a framework for studying automated decision-making technologies and their social effects that challenges and subverts this framing of ADM as spreading from the West. This is the centre that we aim to destabilize and displace by offering accounts of how ADM is being done otherwise. Here we do not limit ourselves to redemptive stories of emancipatory projects involving ADM, although readers may find elements of this. Rather we aim both to challenge dominant narratives of unidirectional flows of algorithmic power while also demonstrating what accounts that do not presume such dynamics might look like.

To do this we focus on parts of the world that are often left out of global narratives of ADM by bringing together academic and grey literature, online resources and interviews with key stakeholders in underrepresented regions (Africa, Caribbean, China, Latin America, Pacific Islands, South and Southeast Asia). We frame this as contributing to the Centre of Excellence as contributing to this broader project of decentering who, where, and how engagement with automated decision-making takes place. prioritise places and contexts in the world that were less visible in the field to demonstrate the diversity of ways in which ADM was being imagined, anticipated or practiced in different parts of the world.

PUBLICATIONS

5G and the digital imagination: Pacific Islands perspectives from Fiji and Papua New Guinea, 2023

Horst, H., Foster, R.

Journal article

Framing Fashion: Human-machine learning and the Amazon Echo Look, 2022

Horst, H., Mohammid, S.

Book chapter

Looking professional: How women decide what to wear with and through automated technologies. 2021

Horst, H., et al.

Journal article

RESEARCHERS