Language and Cultural Diversity in ADM: Australia in the Asia Pacific

PROJECT SUMMARY

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Language and Cultural Diversity in ADM: Australia in the Asia Pacific

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

This project investigates the challenges and opportunities for cultural and linguistic diversity in automated decision making (ADM) across Australia and the Asia-Pacific region. Focusing upon language and cultural diversity as the central concern, the project aims to better understand the ways in which AI and ADM may be utilised to promote diversity and social cohesion across our region, in addition to identifying the roles of bias and manipulation in ADM.

Moving beyond the dominant paradigms and voices that inform debates about contemporary technologies (e.g. Anglo-centric and superpowers-focused), the Diversity in ADM project focuses on: (1) culturally and linguistically diverse (CALD) communities in Australia, and (2) communities across the Asia-Pacific. It has significance in highlighting both the comparative and connecting perspectives, viewpoints and life experiences, and dialogues in relation to ADM and in increasing creativity and problem-solving capabilities in our multicultural society and workplace.

PROJECT OBJECTIVES

  • Develop a better understand the landscapes of ADM across the region, including the role of NGOs, industry, government and other stakeholders; 
  • Empower community members to participate in dialogues concerning diversity in ADM; and
  • Build capacity for community organisations in collective bargaining with public policymakers for inclusive and equitable ADM policies.

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RESEARCHERS

Haiqing Yu

Prof Haiqing Yu

Project Co-Leader and Chief Investigator,
RMIT University

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ADM+S Chief Investigator Heather Horst

Prof Heather Horst

Project Co-Leader and Chief Investigator,
University of Western Sydney

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Deborah Lupton

Prof Deborah Lupton

Project Co-Leader and Chief Investigator,
UNSW

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ADM+S Chief Investigator Anthony McCosker

Prof Anthony McCosker

Chief Investigator,
Swinburne University
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Sarah Pink

Prof Sarah Pink

Chief Investigator,
Monash University

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Distinguished Professor Julian Thomas

Prof Julian Thomas

Chief Investigator,
RMIT University

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Daniel Featherstone

Dr Daniel Featherstone

Research Fellow,
RMIT University
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Gerard Goggin

Prof Gerard Goggin

Associate Investigator,
University of Western Sydney
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ADM+S Associate Investigator Jenny Kennedy

Assoc Prof Jenny Kennedy

Associate Investigator,
RMIT University
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Dang Nguyen

Dr Dang Nguyen

Research Fellow,
RMIT University

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Dr Damiano Spina

Dr Damiano Spina

Associate Investigator,
RMIT University

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Yong-Bin Kang

Dr Yong-Bin Kang

Research Fellow,
Swinburne University

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Thao Phan

Dr Thao Phan

Research Fellow,
Monash University
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Xiaofang Yao

Dr Xiaofang Yao

Affiliate,
Federation University

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Prof Jason G. Karlin

Research Partner,
Interfaculty Initiative in Information Studies,
University of Tokyo, Japan

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Lee Kwang-Suk

Prof Kwang-Suk Lee

Research Partner,
Seoul National University of Science & Technology,
South Korea

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Cheryll soriano

Prof Cheryll Ruth Soriano

Research Partner,
La Salle Institute of Governance and Social Development Research Center,
De La Salle University, The Philippines

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Prof-Jack-Linchuan-Qiu 4x5small

Prof Jack Qiu

Research Partner,
Asian Communication Research Centre,
Nanyang Technological University, Singapore

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PARTNERS

Digital Asia Hub logo

Digital Asia Hub
(Hong Kong)

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Telstra

Telstra

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COLLABORATORS

Centre for Trusted
Internet and Community

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The Regulatory Project

PROJECT SUMMARY

The Regulatory Project

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

ADM systems (including AI, foundation models and generative AI) pose ongoing regulatory challenges for Australian governments at every level, and across multiple domains. 

2024-2027 is a critical period for the development of regulation of AI. Worldwide, governments are taking concrete steps to adapt existing laws to technological, social and other changes brought about by expanding uses of AI, and to develop new, risk-based regulatory frameworks.

At the same time others are moving to provide more governance for AI: for example via the development of technical standards and other frameworks. 

The Regulatory Project will contribute to this process, examining fundamental questions that these technologies pose for our regulatory techniques, and engaging research and researchers from across the Centre and the Centre’s partners to inform and respond to regulatory initiatives and quandaries.

PROJECT OBJECTIVES

  • Examine and understand the deployment of ADM systems (including AI), by public and private sector actors and across supply chains, and the effect on fundamental legal concepts, such as natural justice (procedural fairness) as it applies to ADM use by government and firms; responsibility, and accountability, delivering critical new knowledge regarding the changing nature of law and regulation in the AI/ADM space; 
  • Examine and analyse emerging regulatory and governance mechanisms for the development and deployment of AI, including their interaction with socio-technical context, in order to understand what mechanisms are emerging, whether they work, and (if so) how;
  • Translate these understandings across other projects and themes in the centre by collaborating on emerging regulatory implications of research and projects across ADM+S; and
  • Provide a hub for ongoing government and policy engagement and to bring legal and regulatory perspectives to research across the Centre.

PUBLIC RESOURCES

GenAI Concepts

Target audience: Government agencies, industry, researchers, general public

This resource offers technical, operational and regulatory terms and concepts for generative artificial intelligence (GenAI), developed in collaboration with the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S) and the Office of the Victorian Information Commissioner (OVIC).

View website
View PDF guide

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RESEARCHERS

Kim Weatherall

Prof Kimberlee Weatherall

Project Co-Leader and Chief Investigator,
University of Sydney

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ADM+S Investigator Christine Parker

Prof Christine Parker

Project Co-Leader and Chief Investigator,
University of Melbourne

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Jake Goldenfein

Dr Jake Goldenfein

Project Co-Leader and Chief Investigator,
University of Melbourne

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Michael Richardson

Assoc Prof Michael Richardson

Project Co-Leader and Associate Investigator,
UNSW

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ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Chief Investigator,
QUT

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Zofia Bednarz

Dr Zofia Bednarz

Associate Investigator,
University of Sydney

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Emeritus Professor Terry Carney

Prof Terry Carney

Associate Investigator,
University of Sydney

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Kylie Pappalardo profile picture

Prof Kylie Pappalardo

Associate Investigator,
QUT

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Scarlet Wilcock

Dr Scarlet Wilcock

Associate Investigator,
University of Sydney

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José-Miguel Bello y Villarino

Dr Jose-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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Fan Yang

Dr Fan Yang

Research Fellow,
University of Melbourne

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Tegan Cohen

Dr Tegan Cohen

Affiliate,
QUT

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PARTNERS

ABC logo

Australian
Broadcasting
Corporation

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AlgorithmWatch logo

Algorithm Watch
(Germany)

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Consumer Policy Research Centre Logo

Consumer Policy R
esearch Centre

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Cornell Tech logo

Cornell Tech

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OVIC Logo

Victorian Information
Commissioner

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COLLABORATORS

University of Melbourne logo

Centre for Artificial Intelligence
and Digital Ethics (CAIDE)

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CHOICE

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Gradient Institute logo

Gradient Institute

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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.

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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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Ariadna Matamoros Fernandez profile picture

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.

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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

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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.

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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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Awais Hameed Khan profile image

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

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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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The Australian Search Experience 2.0

PROJECT SUMMARY

The Australian Search Experience 2.0

Focus Areas: News & Media
Status: Active

The first phase of The Australian Search Experience project launched in late July 2021 and over 12 months collected over 350 million search results from more than 1,000 participants. Results from phase 1 showed that personalisation of results for generic queries in major search engines is minimal, and generally limited to ensuring geographic relevance for users. Yet partisanship is rife. Eight billion queries are issued daily to Google alone, and many partisans use search engines for fact checking, can it really be that this ubiquitous ADM plays no role in the growing partisanship of society? 

The Australian Search Experience 2.0 will address a critically overlooked part of the story. We already know individual searchers formulate their queries very differently, and that this directly affects the results obtained, but understanding the extent and form of query variation as well as its impact is methodologically challenging.

The query is one of the key means people have to control not just search, but with the rise of generative AI, text queries and instructions are becoming the dominant way that ADM systems are controlled. 

When considering the impact of search on society, we know that individual searchers formulate their queries very differently, and that this directly affects the results obtained.

This project will generate significant new knowledge about the breadth and quality of information returned in response to diverse search queries, and offers a significantly more realistic perspective than past research for the impact of variations in users’ queries on the results recommended to them. It will significantly advance the state of the art in the field by developing novel methodologies for the study of search and recommendation in conventional (text-based) and emerging (voice-based and AI assisted) search interfaces, and producing new insights into their impact on users and content creators.

Findings from this research will have both productive and preventative implications: a better understanding of query diversity for a given topic will enable the designers of textbased and non-text-based search interfaces to enhance the ability of such interfaces to produce quality results; similarly, it will also enable educators and non-profit organisations to develop more targeted interventions for improving search literacy and preventing the spread of misinformation.

PROJECT OBJECTIVES

  • Explore novel ways of measuring effectiveness of search engines, by considering a diverse pool of demographic groups that represent the breadth of the Australian population, and observing their approaches to developing search queries;
  • Evaluate the range of search results that such queries return using AI to simulate the full diversity of search queries on controversial topics;
  • Develop an understanding of how non-traditional search interfaces and contextual factors drive query variation; and
  • Determine relationships between queries and search results for specific types of query, public interest topics and key news and information sources such as Wikipedia projects.

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RESEARCHERS

ADM+S Chief Investigator Mark Sanderson

Prof Mark Sanderson

Project Co-Leader and Chief Investigator,
RMIT University

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Axel Bruns

Prof Axel Bruns

Project Co-Leader and Chief Investigator,
QUT

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Daniel Angus

Prof Daniel Angus

Chief Investigator,
QUT

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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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Dr Ariadna Matamoros-Fernández

Associate Investigator,
QUT

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ADM+S Chief Investigator Falk Scholer

Prof Falk Scholer

Associate Investigator,
RMIT University

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Dr Damiano Spina

Dr Damiano Spina

Associate Investigator,
RMIT University

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Johanne Trippas

Dr Johanne Trippas

Associate Investigator,
RMIT University

Maarten de Rijke

Prof Maarten de Rijke

Partner Investigator,
University of Amsterdam

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ADM+S professional staff Abdul Obeid

Dr Abdul Obeid

Data Engineer,
QUT

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Amanda Lawrence

Dr Amanda Lawrence

Affiliate,
RMIT University

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Natali Helberger

Prof Natali Helberger

Research Partner,
University of Amsterdam

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Judith Moller

Prof Judith Möller

Research Partner,
Hans Bredow Institut

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Kim Osman

Dr Kim Osman

Research Partner,
QUT

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PARTNERS

ABC logo

Australian
Broadcasting
Corporation

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AlgorithmWatch logo

AlgorithmWatch

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Hans Bredow Institut Logo

Hans-Bredow-Institut

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University of Amsterdam logo

University of Amsterdam

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Evaluating Automated Cultural Curating and Ranking Systems with Synthetic Data

PROJECT SUMMARY

Evaluating Automated Cultural Curating and Ranking Systems with Synthetic Data

Focus Areas: News & Media
Status: Active

As culture becomes increasingly mediated through automated systems, it is crucial to devise means of evaluating their performance from a societal perspective. Automated systems increasingly navigate a sea of content on our behalf, shaping the flow of culture and cultural products such as news, information retrieval and search, recommender systems and music and video.

This project addresses the question of how to study and evaluate the role that automated systems play in shaping this flow. It brings together technical innovations in the use of synthetic data for hybrid approaches to simulate a broad range of behaviours that influence automated decision-making systems, with a specific focus on ranking-based systems.

It will build tools and approaches to evaluate how recommender and ranking-based systems might incorporate cultural and civic values, such as better representation of artists of colour on streaming platforms or higher visibility and circulation for information of significant public interest.

This project will develop strategies for intervening in the automated flow of culture to advance Centre priorities of responsive, ethical, and inclusive automated decision making.

PROJECT OBJECTIVES

  • Understand what cultural products people are exposed to and in what order and why;
  • Evaluate whether and how ranking-based systems might incorporate factors and values that range from commercial to cultural and civic;
  • Understand how different automated systems create an overall cultural milieu through their combinations and interactions with one another;
  • Provide key insights into how ADMs are experienced in specific sites;
  • Develop ways to ensure that automated intervention in cultural flows aligns with social priorities, including commitments to diversity, fairness, and inclusion; and
  • Demonstrate the appropriate contexts and methods for using synthetic data in evaluating ADM systems.

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RESEARCHERS

Mark Andrejevic

Prof Mark Andrejevic

Project Co-Leader and Chief Investigator,
Monash University

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Jeffrey Chan

Assoc Prof Jeffrey Chan

Project Co-Leader and Associate Investigator,
RMIT University

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Kylie Pappalardo profile picture

Dr Kylie Pappalardo

Project Co-Leader and Associate Investigator,
QUT

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James Meese

Assoc Prof James Meese

Project Co-Leader and Chief Investigator,
RMIT University

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Chief Investigator,
QUT

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Prof 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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Distinguished Professor Julian Thomas

Prof Julian Thomas

Chief Investigator,
RMIT University
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Danula Hettiachchi

Dr Danula Hettiachchi

Associate Investigator,
RMIT University
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Joel Stern

Dr Joel Stern

Associate Investigator,
RMIT University
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Patrik Wikstrom

Prof Patrik Wikstrom

Associate Investigator,
QUT

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PARTNERS

ABC logo

Australian
Broadcasting
Corporation

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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

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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.

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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

Learn more

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
Learn more

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

Visit website

COLLABORATORS

CHOICE

Visit website

Australian Ad Observatory: Investigating mobile and dynamic advertising via computational and participatory approaches

PROJECT SUMMARY

Australian Ad Observatory: Investigating mobile and dynamic advertising via computational and participatory approaches

Focus Areas: News & Media
Status: Active

Advertising remains the dominant model for supporting commercial media platforms, and continues to pioneer strategies of data driven customisation and targeting. Advertisers are at the forefront of experimenting with automated digital media across recommendation, targeting, synthetic and augmented content, logistics and retail. Revenue from advertising funds the digital media platforms that in turn invest in engineering automated models that curate, augment and synthesise our media experience. 

Phase one of the Ad Observatory pioneered a way to observe the targeting of social media advertising across populations of users. We generated the largest known collection of targeted ads that people encounter on Facebook in Australia – 328,107 unique ads from 1909 participants –and built world-first research infrastructure that involved citizens in doing so. The project led to significant findings and impact, and new ways of approaching the study of automated advertising, not only in terms of individually targeted, discrete ads, but as ongoing sequences of ads that are ‘tuned’ to work in tandem with people’s identities and daily rhythms.

Responding to significant recent and ongoing developments in automated advertising (including Generative AI), the Phase 2 Ad Observatory will develop approaches for studying contemporary media and information environments, where there are no longer either shared flows of content, nor stable texts.

It will conduct participatory research with diverse groups of Australians to provide visibility into the targeting of harmful products to particular groups. It will explore experiences of advertising and understand its cultural impact, combining citizen science with data collection.

This project will significantly advance our conceptual understanding of automated advertising, playing a crucial role in documenting the emergence of this new form of advertising and enabling industry, civil society and government to respond to the challenges it will create to observability and accountability.

PROJECT OBJECTIVES

  • Develop research infrastructure and methods to observe dark, ephemeral, and automatically generated ad content and sequences, using a prototype Mobile Ad Observatory Toolkit to collect digital ads across platforms;
  • Conduct participatory research with diverse groups of Australians to explore their experiences of advertising and understand its cultural impact, combining citizen science with data collection;
  • Develop tools for automatically identifying defined categories of advertising (such as political ads and ads for harmful products and services);
  • Provide visibility into the targeting of political advertising during the next Federal election in Australia by recruiting undecided voters in marginal and swinging electorates;
  • Develop a detailed account of competing advertising explanatory models: those offered by the platforms, those offered by users, and those informed from our observations;
  • Conceptualise and develop models for simulating automated advertising at individual and cultural levels, creating tools for users to compare ad sequences and question the automated processes behind them;
  • Examine implications of automated advertising, including the use of generative AI, for current and contemplated platform governance policies, legal tools, and regulatory frameworks; and
  • Collaborate with partners to build a public interest network focused on digital advertising, promoting observability, advocacy, and influencing the development of responsible advertising practices.

MORE INFORMATION

  • Develop research infrastructure and methods to observe dark, ephemeral, and automatically generated ad content and sequences, using a prototype Mobile Ad Observatory Toolkit to collect digital ads across platforms;
  • Conduct participatory research with diverse groups of Australians to explore their experiences of advertising and understand its cultural impact, combining citizen science with data collection;
  • Develop tools for automatically identifying defined categories of advertising (such as political ads and ads for harmful products and services);
  • Provide visibility into the targeting of political advertising during the next Federal election in Australia by recruiting undecided voters in marginal and swinging electorates;
  • Develop a detailed account of competing advertising explanatory models: those offered by the platforms, those offered by users, and those informed from our observations;
  • Conceptualise and develop models for simulating automated advertising at individual and cultural levels, creating tools for users to compare ad sequences and question the automated processes behind them;
  • Examine implications of automated advertising, including the use of generative AI, for current and contemplated platform governance policies, legal tools, and regulatory frameworks; and
  • Collaborate with partners to build a public interest network focused on digital advertising, promoting observability, advocacy, and influencing the development of responsible advertising practices.

RESEARCHERS

ADM+S Investigator Christine Parker

Prof Christine Parker

Project Co-Leader and Chief Investigator,
University of Melbourne

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Nicholas Carah

Assoc Prof Nicholas Carah

Project Co-Leader and Associate Investigator,
University of Queensland

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Mark Andrejevic

Prof Mark Andrejevic

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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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Project Co-Leader and Chief Investigator,
QUT
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Prof Flora Salim

Prof Flora Salim

Chief Investigator,
UNSW

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Kim Weatherall

Prof Kimberlee Weatherall

Chief Investigator,
University of Sydney
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ADM+S Investigator Timothy Graham

Assoc Prof Timothy Graham

Associate Investigator,
QUT

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ADM+S professional staff Abdul Obeid

Dr Abdul Obeid

Data Engineer,
QUT
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Thao Phan

Dr Thao Phan

Research Fellow,
Monash University
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Maria-Gemma Brown research partner

Maria-Gemma Brown

PhD Student,
The University of Queensland

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Lauren Hayden

Lauren Hayden

PhD Student,
The University of Queensland
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César Albarrán-Torres

Dr César Albarrán-Torres

Affiliate,
Swinburne University

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Robbie Fordyce

Dr Robbie Fordyce

Affiliate,
Monash University

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Giselle Newton

Dr Giselle Newton

Affiliate,
The University of Queensland

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Verity Trott

Dr Verity Trott

Affiliate,
Monash University
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PARTNERS

ABC logo

Australian
Broadcasting
Corporation

Visit website

Consumer Policy Research Centre Logo

Consumer Policy
Research Centre

Visit website

COLLABORATORS

CHOICE

Visit website

FARE Logo

Foundation for Alcohol
Research & Education

Visit website

Vic Health Logo

VicHealth

Visit website

Automated informality: generative frictions in ADM systems

PROJECT SUMMARY

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

Automated informality: generative frictions in ADM systems

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

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

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

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

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

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

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

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

RESEARCHERS

Dang Nguyen

Dr Dang Nguyen

Lead Investigator,
RMIT University

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Danula Hettiachchi

Dr Danula Hettiachchi

Associate Investigator,
RMIT

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Rakesh Kumar

Rakesh Kumar

PhD Student,
Western Sydney University

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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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Awais Hameed Khan profile image

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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Testbed Australia

PROJECT SUMMARY

Drone in sky

Testbed Australia

Focus Areas: Transport and Mobilities
Research Program: People

Australia has a long history as a site for scientific experimentation. The Australian land and its people have, over the course of its colonial history, been continuously treated as a “low risk” site for the empirical testing of high-risk theories and procedures.

Most recently, Big Tech corporations have begun to experiment with the country’s potential as test bed for new features and products. The streaming service Spotify used Australia as a testing site for its then experimental Discover Weekly playlist. The dating app Tinder piloted features like “Tinder Social” and “Super Like” in the Australian market before releasing it globally. And Facebook trialled its 2018 upvote downvote feature first on users based in Australia and New Zealand.

While techniques like prototyping, beta testing, and other forms of testing “in the wild” are common practices, the impacts of such testing on communities and environments are under-examined.

This project explores the role of testing, prototyping, trialling and other techniques of controlled experimentation for AI and other automated decision-making systems in Australia.

It focuses on transport and mobilities, investigating techniques of testing for the deployment of automated systems, such as those used in Autonomous vehicle (AVs) and commercial delivery drones.

It brings together expertise in feminist science and technology studies (STS), critical legal studies, and media studies to address questions such as:

  • What are the features of the environment and landscape that make Australia well-suited as a site for testing?
  • Which communities are targets for testing?
  • How does policy and other forms of state discourse contribute to creating an ideal regulatory environment for testing?
  • What are the potential harms and benefits involved?

RESEARCHERS

Thao Phan

Dr Thao Phan

Lead Investigator,
Monash University

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Jake Goldenfein

Dr Jake Goldenfein

Chief Investigator,
University of Melbourne

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Michael Richardson

Assoc Prof Michael Richardson

Associate Investigator,
UNSW

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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

Learn more

ADM+S Chief Investigator Anthony McCosker

Prof Anthony McCosker

Chief Investigator,
Swinburne University

Learn more

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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Designing Automated Tools to Support Welfare Rights Advocacy

PROJECT SUMMARY

Person typing on laptop with graphic overlay

Designing Automated Tools to Support Welfare Rights Advocacy

Focus Areas: Social Services
Research Program: Machines
Status: Active

Welfare rights lawyers across Australia advocate for claimants of income support payments (e.g., unemployment benefits, disability support pension, family tax benefit etc.) paid by Services Australia — Centrelink. Claimants rely on welfare payments as a substantive part of their income, and often depend on welfare rights organisations to assist them in disputing decisions by Centrelink. These disputes can range from alleged debt due to overpayment, cessation of payment, or denial of payment altogether.

When engaging a client to support a dispute claim, welfare rights lawyers often submit a Freedom of Information (FOI) request to Centrelink, to access client files. Centrelink provides this information in the form of a large PDF document (colloquially referred to as THE BRICK), which contains hundreds of pages of client data, including case notes and screenshots from Centrelink computers, documents using a lot of system and internal acronyms. Lawyers must then trawl through and make sense of this detailed document, reconstructing the history of a client’s case, while attempting to decipher the decisions made by Centrelink and their rationale. This is a heavy time consuming and onerous process, reducing the actual time a lawyer spends in engaging with their client, and making the legal arguments for the case.

Working closely with welfare rights lawyers (and their teams), advocacy groups, and users of social services — this project aims to collaboratively design, prototype, and pilot an automated data extraction tool to support welfare rights lawyers in making sense of Services Australia (Centrelink) system-generated FOI documents.

This project explores the following research questions:

  1. How can we digitally scaffold and support sense-making of Freedom of Information (FOI) system-generated responses through a data extraction tool outside the government system?
  2. What methods/approaches can facilitate collaborative design of Automated Decision-Making (ADM) support systems in social services with key stakeholders?
  3. How might we reclaim and democratize sense-making/deciphering of government ADM outputs from outside of government systems — designing for controlled activism?
  4. What impact can using an ADM support system, such as the data extraction tool, have on an organisational work flow and capacity of welfare rights lawyers to support their clients?

Key objectives are to:

  • Design, prototype and build an automated data extraction tool to support welfare rights lawyers in sense-making of system-generated FOI documents
  • Involve welfare rights lawyers, advocacy groups, and social service users and professionals in co-design of ADM tools to support such sense-making
  • Evaluate the Implications of the tool on organisational practice and processes

RESEARCHERS

Paul Henman headshot

Prof Paul Henman

Lead Investigator,
University of Queensland

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Terry Carney profil picture

Prof Terry Carney

Associate Investigator,
University of Sydney

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Robert Mullins profile picture

Dr Robert Mullins

Associate Investigator,
University of Queensland

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Awais Hameed Khan profile image

Dr Awais Hameed Khan

Research Fellow,
University of Queensland

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ADM+S professional staff Abdul Obeid

Dr Abdul Obeid

Data Engineer,
QUT

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Dan Trang

Dan Trang

Software Developer,
QUT

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PARTNERS

Economic Justice Australia

Economic Justice of Australia

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Services Australia

Services Australia

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Welfare Rights Centre

Welfare Rights Centre

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Trauma-informed AI: Developing and testing a practical AI audit framework for use in social services

PROJECT SUMMARY

Woman's face with artificial intelligence graphic on right side

Trauma-informed AI: Developing and testing a practical AI audit framework for use in social services

Focus Areas: Social Services
Research Program: Machines
Status: Completed

Artificial Intelligence (AI) is increasingly being used in the delivery of social services. While it offers opportunities for more efficient, effective and personalised service delivery, AI can also generate greater problems, reinforcing disadvantage, generating trauma or re-traumatising service users.

Conducted by a multi-disciplinary research team with extensive expertise in the intersection of social services and digital technology, this project seeks to co-design an innovative AI trauma-informed audit framework to assess the extent to which an AI’s decisions may generate new trauma or re-traumatise.

The value of a trauma-informed AI audit framework is not simply to assess digital technologies after they are built and in operation, but also to inform designs of digital technologies and digitally enabled social services from their inception.

It will be road-tested using multiple case studies of AI use in child/family services, domestic and family violence services, and social security/welfare payments.

PUBLIC RESOURCES

Building a Trauma-Informed Algorithmic Assessment Toolkit

Target audience: Social service organisations

This Toolkit has been designed to assist organisations in their use of automation in service delivery at any stage of their automation journey: ideation; design; development; piloting; deployment or evaluation. While of particular use for social service organisations working with people who may have experienced past trauma, the tool will be beneficial for any organisation wanting to ensure safe, responsible and ethical use of automation and AI.

View toolkit

RESEARCHERS

Paul Henman

Prof Paul Henman

Lead Investigator,
University of Queensland

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ADM+S Investigator Philip Gillingham

Dr Philip Gillingham

Associate Investigator,
University of Queensland

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Lyndal Sleep profile picture

Dr Lyndal Sleep

Affiliate,
Central Queensland University

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Suzanna Fay

Dr Suzanna Fay

Senior Lecturer,
University of Queensland

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PARTNERS

University of Notre Dame-IBM Tech Ethics Lab

University of Notre Dame-IBM Tech Ethics Lab

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Mapping automated decision-making tools in administrative decision-making in NSW

PROJECT SUMMARY

In motion people walking by office building

Mapping automated decision-making tools in administrative decision-making in NSW

Focus Areas: Social Services
Research Program: Institutions
Status: Completed

The project is a partnership between ADM+S and the New South Wales Ombudsman to map and analyse the use of automated systems in state and local government sectors in New South Wales (NSW). The project follows from a ground-breaking report on the use of technology in government decision-making published by the NSW Ombudsman in 2022.

The project will first map where and how NSW state and local government agencies are using automated systems in administrative decision processes. This is the first attempt to undertake such a systematic mapping in any jurisdiction in Australia and one of the very few attempts across the world. This first stage, led by Prof Paul Henman, Chief Investigator at ADM+S, and Dr Lyndal Sleep, Research Fellow at ADM+S, will distribute questionnaires and conduct targeted interviews with NSW state and local government agencies; building on the work from the ‘Mapping ADM in Australian Social Services’ project which mapped the use of automated systems in social security settings in Australia.

The second part of the research will be led by ADM+S Chief Investigator Prof Kimberlee Weatherall, and ADM+S Research Fellow Dr José-Miguel Bello y Villarino, which will analyse the different systems planned and in use by NSW public authorities, and the key risks and issues that emerge.

Researchers from ADM+S and Macquarie University will contribute to different legal and technical elements of the project.

The NSW Ombudsman will table a report to NSW Parliament with the findings of the research by the end of 2023.

 

This project culminated in the release of ‘Automated decision-making in New South Wales: mapping and analysis of the use of ADM systems by State and Local governments’, a report published in partnership with ADM+S and the New South Wales Ombudsman.

The report findings were presented as evidence during the first hearing of the NSW Artificial Intelligence Inquiry at Parliament House in Canberra on 8 March 2024.

Listen to Chief Researcher Prof Paul Henman on the ADM+S Podcast.

RESEARCHERS

Kimberlee Weatherall

Prof Kimberlee Weatherall

Chief Researcher, University of Sydney

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Paul Henman

Prof Paul Henman

Chief Researcher, UQ

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José-Miguel Bello y Villarino

Dr José-Miguel Bello y Villarino

Principal Researcher, University of Sydney

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ADM+S Member

C. Allan

Principal Project Officer, NSW Ombudsman’s Office

ADM+S Member

K. Whitworth

Senior Project Officer, NSW Ombudsman’s Office

Lyndal Sleep profile picture

Dr Lyndal Sleep

Associate Researcher,
Central Queensland University

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Jenny van der Arend

Dr Jenny van der Arend

Senior Research Assistant, UQ

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Jeffrey Chan

Assoc Prof Jeffrey Chan

Associate Researcher

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Terry Carney

Prof Terry Carney

Senior Researcher, University of Sydney

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Scarlet Wilcock

Dr Scarlet Wilcock

Associate Researcher, University of Sydney

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Rita Matulionyte

Dr Rita Matulionyte

Associate Researcher, Macquarie University

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Distinguished Professor Julian Thomas

Dist. Prof Julian Thomas

Advisory Board Member, RMIT University

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PARTNERS

NSW Ombudsman

Visit website

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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The Toxicity Scalpel: Prototyping and evaluating methods to remove harmful generative capability from foundation models

PROJECT SUMMARY

Person with colourful text overlay

The Toxicity Scalpel: Prototyping and evaluating methods to remove harmful generative capability from foundation models

Focus Areas: News and Media
Research Programs: Machines
Status: Completed

AI language models have made significant strides over the past few years. Computers are now capable of writing poetry and computer code, producing human-like text, summarising documents, engaging in natural conversation about a variety of topics, solving math problems, and translating between languages.

This rapid progress has been made possible by a trend in AI development where one general ‘foundational’ model is developed (usually using a large dataset from the internet) and then adapted many times to fit diverse applications, rather than beginning from scratch each time.

This method of ADM development can appear time and cost effective, but ‘bakes in’ negative tendencies like the creation of toxic content, misogyny, or hate speech at the foundational layer, which subsequently spread to each downstream application.

The goal of this project is to examine how language models used in ADM systems might be improved by making modifications at the foundation model stage, rather than at the application level, where computational interventions, social responsibility, and legal liability have historically focussed.

PUBLICATIONS

First page of Journal Article: Measuring Misogyny in Natural Language Generation: Preliminary Results from a Case Study on two Reddit Communities

Measuring Misogyny in Natural Language Generation: Preliminary Results from a Case Study on two Reddit Communities,2023

Snoswell, A., Nelson, L., Xue, H., Salim, F., Suzor, N., & Burgess, J.

Journal article

RESEARCHERS

ADM+S Investigator Flora Salim

Prof Flora Salim

Chief Investigator,
UNSW

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ADM+S Chief Investigator Nic Suzor

Prof Nic Suzor

Chief Investigator,
QUT

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Dr Aaron Snoswell

Dr Aaron Snoswell

Associate Investigator,
QUT

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Hao Xue

Dr Hao Xue

Associate Investigator,
UNSW

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Lucinda Nelson

Lucinda Nelson

PhD Student,
QUT

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She’s Not Alone

PROJECT SUMMARY

She's Not Alone

She’s Not Alone

Focus Area: Transport & Mobilities
Research Program: People

In partnership with Monash University’s Emerging Technologies Research Lab and She’s A Crowd, a social enterprise working to end gender-based violence, this drama-documentary invites us to consider: how people and organisations might effectively use automated decision-making (ADM) in the rideshare sector to deliver a safe and trusted service; and where the starting points for design for rideshare ADM systems and technologies should be.

She’s Not Alone is a short film co-produced by ADM+S researchers Jeni Lee and Dr Emma Equilty that highlights some of the safety issues women and gender diverse people experience in and around transport. In a world where automated systems, technology and digital data are increasingly present, the film raises discussion around automated safety features including tracking, surveillance and emergency alerts.

The docu-drama challenges the idea that artificial intelligence is the way to solve problems that arise for so many rideshare users, suggesting instead that we imagine a future where safety involves a combination of technology, human connections and community support.

RESEARCHERS

Jeni Lee

Jeni Lee

Lead Investigator,
Monash University

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Sarah Pink

Prof Sarah Pink

Chief Investigator,
Monash University

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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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PARTNERS

She's A Crowd Logo

She’s A Crowd

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Emerging Technologies Research Lab

Emerging Technologies Research Lab, Monash University

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RELATED PROJECTS

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

Learn more

ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Chief Investigator,
QUT

Learn more

Collateral Data: Automated Decision-Making and the Future of Credit in India

PROJECT SUMMARY

Young Indian woman looking at letter while using laptop

Collateral Data: Automated Decision-Making and the Future of Credit in India

Focus Areas: Social Services
Research Programs: People
Status: Active

This project aims to investigate the increasing use of automated decision-making systems in the provision of automated loans in India. These systems can use a potential borrower’s personal data (including call histories, location, contact lists) to create credit scores for people without formal credit histories. Hailed as a revolutionary step forward in financial inclusion on the one hand and decried as a dangerous invasion of privacy on the other, these new loan products have significant impacts.

Focusing on designers, regulators, and users of automated loans in India, the project asks how these products shape financial inclusion and socio-economic mobility at an everyday level. Through conducting interviews and collecting financial diaries the project aims to elucidate how these technologies are taken up and transform borrowers’ livelihoods and social networks.

Expected outcomes include detailed accounts of how automated financial services can exacerbate inequality even as they expand financial inclusion. Understanding these dynamics will be crucial not only for intervening in social inequality in India but also in regulating the adoption of similar practices of credit-scoring and loan distribution that are already starting to emerge in Australia. In providing a detailed picture of how ADM is changing the landscape of credit and economic inequality in a context where these tools have been widely adopted, the project seeks to provide critical foresight to regulators and industry actors in countries like Australia where data sharing, and alternative data are just beginning to be taken up in the financial sector.

RESEARCHERS

ADM+S Chief Investigator Heather Horst

Prof Heather Horst

Lead Investigator,
Western Sydney University

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

PROJECT SUMMARY

Brimbank City Council garbage truck

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

Focus Area: Mobilities
Research Program: Data
Status: Completed

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

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

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

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

PUBLICATIONS

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

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

Report

RESEARCHERS

ADM+S Chief Investigator Anthony McCosker

Prof Anthony McCosker

Lead Investigator,
Swinburne University

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Yong-Bin Kang

Dr Yong-Bin Kang

Research Fellow,
Swinburne University

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Milovan Savic

Dr Milovan Savic

Research Fellow,
Swinburne University

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Yong-Bin Kang

Thomas Graham

PhD Student,
Swinburne University

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Affiliate,
University of Melbourne

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PARTNERS

Brimbank City Council

Brimbank City Council

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OVIC Logo

Office of the Victorian Information Commissioner (OVIC)

Visit website

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

Learn more

Ariadna Matamoros Fernandez profile picture

Dr Ariadna Matamoros-Fernández

Associate Investigator,
QUT

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James Meese

Dr James Meese

Associate Investigator,
RMIT University

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Andrew Roberts

Prof Andrew Roberts

Associate Investigator,
University of Melbourne

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ADM+S Investigator Ivana Jurko

Ivana Jurko

Partner Investigator,
Red Cross Australia

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José-Miguel Bello y Villarino

Dr José-Miguel Bello Villarino

Research Fellow,
University of Sydney

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Anjalee de Silva

Dr Anjalee de Silva

Research Fellow,
University of Melbourne

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Henry Fraser

Dr Henry Fraser

Research Fellow,
QUT

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Dr Rosalie Gillett profile picture

Dr Rosalie Gillett

Research Fellow,
QUT

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Damian Clifford

Dr Damian Clifford

Affiliate,
ANU

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ADM+S Investigator Fiona Haines

Prof Fiona Haines

Affiliate,
University of Melbourne

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Aitor Jiménez

Dr Aitor Jiménez

Affiliate,
University of Melbourne

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Kobi Leins

Dr Kobi Leins

Affiliate,
King’s College

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Jeannie Paterson

Prof Jeannie Paterson

Affiliate,
University of Melbourne

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Affiliate,
University of Melbourne

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PARTNERS

OVIC Logo

Office of the Victorian Information Commissioner (OVIC)

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Data for Social Good: Non-profit sector data projects

PROJECT SUMMARY

Diverse group of people using digital devices

Data for Social Good: Non-profit sector data projects

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

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

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

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

PUBLIC RESOURCES

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

Target audience: Not-for-profit sector

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

View Framework

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

Target audience: Disaster management organisations, Communities

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

View Framework

PUBLICATIONS

Data for Social Good - Front Cover

Data for social good: non-profit sector data projects

27 October 2022

Read on APO

RESEARCHERS

ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Lead Investigator,
Swinburne University

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Kath Albury

Prof Kath Albury

Associate Investigator,
Swinburne University

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Jane Farmer

Prof Jane Farmer

Associate Investigator,
Swinburne University

Learn more

PARTNERS & COLLABORATING ORGANISATIONS

Australian Red Cross Logo

Australian Red Cross

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Bendigo Bank

Bendigo Bank

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Victorian Government

Department of Premier and Cabinet, Victorian Government

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Entertainment Assist

Entertainment Assist

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Good Cycles

Good Cycles

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Infoxchange

Infoxchange

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ReachOut

ReachOut

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Yooralla

Yooralla

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Enabling digital transformation and considering digital futures within the cultural sector: Evaluating ACMI’s CEO digital mentoring project

PROJECT SUMMARY

ACMI building in the evening

Enabling digital transformation and considering digital futures within the cultural sector: Evaluating ACMI’s CEO digital mentoring project

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

This research investigated the enablers of digital transformation and considers digital futures within the cultural sector through evaluating the outcomes of ACMI’s CEO Digital Mentoring Program.

Funded by the Ian Potter Foundation and delivered in conjunction with the Australia Council, ACMI’s CEO Digital Mentoring Program offered strategic technology and digital mentoring for senior decision-making staff within the Australian cultural sector.

With digital platforms fundamentally reshaping how cultural content is created, distributed, and consumed, this research considered how cultural organisations might be better equipped to, and supported in, adopting, managing, and mitigating the risks associated with increasingly advanced technologies.

PUBLICATIONS

National Cultural Policy consultation: ADM+S together with the Digital Media Research Centre (DMRC), 2022

Holcombe-James, I., Pappalardo, K., et al.

Submission

From the top: learning from ACMI’s CEO Digital Mentoring Program 2021-22, 2022

Holcombe-James, I., et al.

Report

Enabling digital transformation within the cultural sector? Documenting ACMI’s CEO digital mentoring pilot program: executive summary, 2022

Holcombe-James, I.

Report

RESEARCHERS

Indigo Holcombe-James

Dr Indigo Holcombe-James

Lead Investigator

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Stephanie Livingstone

Stephanie Livingstone

PhD Student

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PARTNERS

Trust in ADM: Rethinking the anticipatory modes of technological determinism

PROJECT SUMMARY

Blurred colourful walkway

Trust in ADM: Rethinking the anticipatory modes of technological determinism

Focus Area: News and Media, Transport and Mobility, Health, and Social Services
Research Program: People
Status: Completed

If we are to bring people into the process of ADM technology design then we need to ensure that the conceptual categories that frame theory and practice in innovation account for people.

This project interrogates a suite of anticipatory categories and the arrays of concepts that support them, which are commonly used in innovation narratives, amongst industry and policy stakeholders and in academic disciplines that are complicit with their agenda—such as human-computer interaction research and other computer science and engineering disciplines, and organisation studies.

It identifies the key categories and concepts, analyses how they are mobilised in narratives of innovation, their relationships to solutionist paradigms, how they structure processes of research and how they are actually implied in research and design practice.

The project unpicks the detail of the conceptual frameworks that inform ADM as well as the ways they are engaged in the everyday work practices of developers, designers, businesses and policy makers. It also asks how we might most fruitfully define and engage such categories and concepts, in order to use them to structure interdisciplinary collaboration.

The analysis will include established anticipatory categories common in technology discourses—of trust, barriers, anxiety and acceptance—as well as contemporary (and different types of) categories such as sharing, transparency and others, which are associated with new technologies and automation. Other new and emerging concepts and categories will be identified during the course of the research.

SUB-PROJECTS

PUBLICATIONS

Emerging Technologies / Life at the Edge of the Future, 2023

Pink, S.

Book

An Anthropology of Futures and Technologies, 2023

Lanzeni, D., Pink, S., et al.

Book

Trust in Automation, 2022

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

Book

Digital social work: Conceptualising a hybrid anticipatory practice, 2022

Pink, S., et al.

Journal article

Sensuous futures: re-thinking the concept of trust in design anthropology, 2021

Pink, S.

Journal article

Trusting Autonomous Vehicles: an interdisciplinary approach, 2020

Raats, K., Fors, V., Pink, S.

Journal article

RESEARCHERS

Sarah Pink

Prof Sarah Pink

Chief Investigator,
Monash University

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Mark Andrejevic

Prof Mark Andrejevic

Chief Investigator,
Monash University

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Gerard Goggin

Prof Gerard Goggin

Associate Investigator,
Western Sydney University

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ADM+S partner investigator Vaike Fors

Prof Vaike Fors

Partner Investigator,
Halmstad University

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Kaspar Raats

Kaspar Raats

PhD Student,
Monash University

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Emma Quilty

Dr Emma Quilty

Affiliate,
Monash University

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PARTNERS

Halmstad University logo

Halmstad University

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Volvo Logo

Volvo Cars (Sweden)

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Highway to the Sky

PROJECT SUMMARY

Blurred vision in airplane

Highway to the Sky

Focus Area: Transport & Mobilities
Research Program: People
Status: Completed

Highway to the Sky is a short film co-created with 3 neuro-diverse artists and art therapist Isabelle Ashford from The Art to Wellbeing.

The participants in the workshops used collage, art works and dance to imagine future mobilities and explore what sensations arise from automated travel and what they would like to be automated (or not) in the future.

The creative process elicited reflection and thoughtful responses from the project participants and highlighted their sensory experiences.

Remembering the frustration they may have previously felt on the train, for instance, might create a tightness in their chest or a dizzy sensation.

By documenting experiences of the so-called 17%, the people who see the world differently, this project reveals biases and threats of automated transport mobilities and also uncovers creative opportunity and innovation.

SHORT FILM

RESEARCHERS

Jeni Lee

Jeni Lee

Lead Investigator,
Monash University

Learn more

Sarah Pink

Prof Sarah Pink

Chief Investigator,
Monash University

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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

Learn more

RELATED PROJECTS

Flight Paths, Freeways and Railroads

PROJECT SUMMARY

My phone is my eyes

Flight Paths, Freeways and Railroads

Focus Area: Transport & Mobilities
Research Program: People

Through a series of short film vignettes, this research project explores how diverse participants currently experience transport mobilities and how automated technologies might be part of our future lives.

These films aim to surface impacts of ADM that haven’t been accounted for and explore barriers and biases propagated and amplified by ADM in society.

In 2021, filmmaker Jeni Lee accompanied and filmed two blind and one deaf participant as they moved around urban and regional spaces. The act of commuting was intended to elicit reflection and thoughtful responses from the research participants. Each participant’s commute forms the backbone and narrative arc of a short film.

Flight Paths, Freeways and Open Roads still preview

RESEARCHERS

Jeni Lee

Jeni Lee

Lead Investigator,
Monash University

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Sarah Pink

Prof Sarah Pink

Chief Investigator,
Monash University

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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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RELATED PROJECTS

Future Automated Mobilities: Imaginaries and possibilities for a world in crisis

PROJECT SUMMARY

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Future Automated Mobilities: Imaginaries and possibilities for a world in crisis

Focus Area: Transport & Mobilities
Research Program: People
Status: Active

Future visions of self-driving cars, digital mobility services, flying taxis and autonomous industrial vehicles dominate industry and policy hype; new mobilities technologies, communities and aspirations are rapidly shaping; and automated and connected mobility technologies are increasingly present, and unevenly distributed in everyday life.

Our research addresses how these and other shifts in and imaginaries of mobilities technologies, services, communities and personal trajectories are changing the landscape of everyday mobility, and reframes emerging automated and connected mobility technologies and data as part of inclusive and diverse everyday worlds and respectful, responsible futures.

To achieve this we will develop critical and innovative methods of research and engagement including documentary film and design materials.

This project will:

  1. Determine how future automated (and automated features of) transport mobilities are being reimagined in post COVID-19 and post-bushfire crisis -across industry, policy and everyday life.
  2. Investigate what can be done to design differently, so that we do not simply replicate the problem-solution paradigm of the innovation paradigm when considering the place of ADM in future mobilities.
  3. Develop innovative interventional and interdisciplinary (design ethnographic) research methods through which to undertake this research
  4. Propose pathways towards open designs that social innovation will play a part in and suggest how ADM might play an ethical, responsible and beneficial (to people) role?
How would you like to travel in the future?

REPORT

Automated Decision-Making for Future Transport and Mobilities: Stakeholder Perspectives

2023

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Automated Decision Making in Transport Mobilities - Front Cover

Automated decision making in transport mobilities: review of industry trends and visions for the future

12 August 2022

View report

SUB-PROJECTS

RESEARCHERS

Thao Phan

Dr Thao Phan

Lead Investigator,
Monash University

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Sarah Pink

Prof Sarah Pink

Chief Investigator,
Monash University

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ADM+S partner investigator Vaike Fors

Prof Vaike Fors

Partner Investigator,
Halmstad University

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Jeni Lee

Jeni Lee

Research Fellow,
Monash University

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Kaspar Raats