Public Interest Litigation for AI Accountability

PROJECT SUMMARY

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Public Interest Litigation for AI Accountability

Focus Area(s): News and Media, Health, Social Services, Transport and Mobilities
Research Program(s): Institutions 

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

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

RESEARCHERS

ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Lead Investigator

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Zahra Stardust profile picture

Dr Zahra Stardust

Research Fellow

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Henry Fraser

Dr Henry Fraser

Research Fellow

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Ecological Implications of Data Centres

PROJECT SUMMARY

Data centre

Ecological Implications of Data Centres

Focus Area(s): All
Research Program: Institutions 

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

A central part of data centre management is heat management: servers produce heat, and as they are gathered in large numbers in close areas, temperatures rise raising the risk of fire. To overcome this, data centre operators have various techniques to cool down these facilities and avoid any risks of data loss caused by fires.

Thus, this project will ask: what shapes the environmental impacts of data centres cooling infrastructures?

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

This project is conducted in collaboration with Dr Clément Marquet (Université de Technologie de Compiègne, France).

RESEARCHERS

ADM+S Investigator Christine Parker

Prof Christine Parker

Lead Investigator

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ADM+S Investigator Fiona Haines

Prof Fiona Haines

Associate Investigator

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Loup Cellard

Dr Loup Cellard

Research Fellow

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ADM+S Investigator Karen Yeung

Prof Karen Yeung

Partner Investigator

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PARTNERS

Université de Technologie de Compiègne Logo

Université de Technologie de Compiègne

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Transparent Machines: From Unpacking Bias to Actionable Explainability

PROJECT SUMMARY

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Transparent Machines: From Unpacking Bias to Actionable Explainability

Focus Area(s): News and Media, Health, Social Services, Transport and Mobilities
Research Program: Machines

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

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

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

This project aims to unpack the biases in models that may come from the underlying data, or biases in software (e.g. a simulation) that could be designed with a specific purpose and angle from the developers’ point-of-view. This project also aims to investigate techniques to generate actionable explanations, for a range of problems and data types and modality, from large-scale unstructured data, to highly varied sensor data and multimodal data.

RESEARCHERS

ADM+S Investigator Flora Salim

Prof Flora Salim

Lead Investigator

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ADM+S Chief Investigator Paul Henman

Prof Paul Henman

Chief Investigator

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ADM+S Chief Investigator Mark Sanderson

Prof Mark Sanderson

Chief Investigator

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Daniel Angus

Prof Dan Angus

Associate Investigator

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Jeffrey Chan

Dr Jeffrey Chan

Associate Investigator

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ADM+S Chief Investigator Falk Scholer

Prof Falk Scholer

Associate Investigator

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ADM+S Investigator Damiano Spina

Dr Damiano Spina

Associate Investigator

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ADM+S Investigator Maarten de Rijke

Prof Maarten de Rijke

Partner Investigator

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PARTNERS

University of Amsterdam logo

University of Amsterdam

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Governing ADM Use

PROJECT SUMMARY

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Governing ADM Use

Focus Area(s): All
Research Program: Institutions 

This project examines possibilities for democratic practice, institutions and governance given automated decision-making (ADM). It focuses on challenges to and opportunities for liberal and democratic institutions and governance presented by ADM.

The project aims to bridge analysis of ADM’s deployment across different domains with scholarly literature on republican and positive freedom, the rule of law and liberal democratic rights.

RESEARCHERS

ADM+S Investigator Christine Parker

Prof Christine Parker

Lead Investigator

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Lead Investigator

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ADM+S Associate Investigator Jake Goldenfein

Dr Jake Goldenfein

Associate Investigator

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ADM+S Investigator Fiona Haines

Prof Fiona Haines

Associate Investigator

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Loup Cellard

Dr Loup Cellard

Research Fellow

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ADM+S Investigator Karen Yeung

Prof Karen Yeung

Partner Investigator

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Democratic Practices of Governance Given ADM

PROJECT SUMMARY

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Democratic Practices of Governance Given ADM

Focus Area(s): All
Research Program: Institutions 

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

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

RESEARCHERS

ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Lead Investigator

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ADM+S Chief Investigator Andrew Kenyon

Prof Andrew Kenyon

Lead Investigator

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Mark Andrejevic

Prof Mark Andrejevic

Chief Investigator

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ADM+S Investigator Christine Parker

Prof Christine Parker

Chief Investigator

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Julian Thomas

Prof Julian Thomas

Chief Investigator

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ADM+S Associate Investigator Jake Goldenfein

Dr Jake Goldenfein

Associate Investigator

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ADM+S Investigator Fiona Haines

Prof Fiona Haines

Associate Investigator

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Andrew Roberts

Prof Andrew Roberts

Associate Investigator

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Anjalee de Silva

Dr Anjalee de Silva

Research Fellow

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Aitor Jiménez

Dr Aitor Jiménez

Research Fellow

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ADM+S Investigator Ivana Jurko

Ivana Jurko

Partner Investigator

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The Coronavirus Impact

PROJECT SUMMARY

COVID19 Stay safe on mobile device

The Coronavirus Impact

Focus Area(s): All
Research Program: Data

Given the role that automated systems are playing in the response to the COVID-19 pandemic, from symptom tracking to the dissemination of (mis-) information, this project contributes to a range of related initiatives across the Centre that respond to the exigencies of the pandemic. The focus of this project will be on issues related to automated data collection, sorting, and response in pandemic contexts, and beyond.

As sensor systems are built out and repurposed to collect data in response to the pandemic, including workplace monitoring, contact tracing, or social distancing compliance, new data streams are being generated which are likely to endure beyond the pandemic for a range of uses and raises a host of issues.

RESEARCHERS

Mark Andrejevic

Prof Mark Andrejevic

Lead Investigator

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Chief Investigator

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ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Chief Investigator

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Julian Thomas

Prof Julian Thomas

Chief Investigator

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Kimberlee Weatherall

Prof Kimberlee Weatherall

Chief Investigator

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ADM+S Associate Investigator Jake Goldenfein

Dr Jake Goldenfein

Associate Investigator

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ADM+S Chief Investigator Andrew Kenyon

Prof Andrew Kenyon

Associate Investigator

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ADM+S Investigator Ellie Rennie

Prof Ellie Rennie

Associate Investigator

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Andrew Roberts

Prof Andrew Roberts

Associate Investigator

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ADM+S Investigator Robert Sparrow

Prof Robert Sparrow

Associate Investigator

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ADM+S Investigator Haiqing Yu

Assoc Prof Haiqing Yu

Associate Investigator

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ADM+S Investigator Ivana Jurko

Ivana Jurko

Partner Investigator

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ADM+S Investigator Frank Pasquale

Prof Frank Pasquale

Partner Investigator

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PARTNERS

Australian Red Cross Logo

Australian Red Cross

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Brooklyn Law School logo

Brooklyn Law School

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Data and Society logo

Data & Society Research Institute (US)

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OVIC Logo

Victorian Information Commissioner

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Data mapping and ADM to advance humanitarian action and preparedness

PROJECT SUMMARY

Volunteer charity workers

Data mapping and ADM to advance humanitarian action and preparedness

Focus Area(s): Social Services, News & Media
Research Program: Data

Humanitarian organisations and other NGOs are undergoing significant digital transformation. In a complicated digital media environment, new analytics capabilities can improve the role and effectiveness of organisations like Australian Red Cross in building community resilience, expanding volunteer networks, and informing rapid response. New practices for ethically sharing and analysing social media activity and public and open datasets can be combined with internal organisational data analysis to produce intelligent responses and predictive models.

This project aims to operationalise new data partnerships and implement data analysis to improve humanitarian sector work. It contributes to developing new techniques for improving data-driven mapping of community strengths, knowledge and resilience. The work will improve advocacy and preparedness and enhance Red Cross’s data analytics capability.

RESEARCHERS

ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Lead Investigator

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ADM+S Investigator Kath Albury

Prof Kath Albury

Associate Investigator

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Daniel Angus

Prof Dan Angus

Associate Investigator

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ADM+S Investigator Rowan Wilken

Assoc Prof Rowan Wilken

Associate Investigator

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ADM+S Investigator Ivana Jurko

Ivana Jurko

Partner Investigator

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Christian Stenta

Christian Stenta

Partner Investigator

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Yong-Bin Kang

Dr Yong-Bin Kang

Research Fellow

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PARTNERS

Australian Red Cross Logo

Australian Red
Cross

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Everyday Data Cultures

PROJECT SUMMARY

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Everyday Data Cultures

Focus Area(s): All
Research Program: Data

This project explores the role of everyday data practices and literacies in automated decision-making. The project develops our new conceptual framework of everyday data cultures, which is based on the cultural studies of everyday life. The project will produce a major monograph (forthcoming with Polity Press in 2022).

To test and further elaborate this framework in real-world settings, we undertake a number of additional empirical case studies using a combination of hybrid digital and qualitative methods. The project provides a framework for integrating everyday community experience into data projects in a variety of sectors.

RESEARCHERS

ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Lead Investigator

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ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Chief Investigator

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ADM+S Investigator Rowan Wilken

Assoc Prof Rowan Wilken

Associate Investigator

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ADM+S Investigator Kath Albury

Prof Kath Albury

Associate Investigator

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Mapping ADM Across Sectors

PROJECT SUMMARY

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Mapping ADM Across Sectors

Focus Area(s): All
Research Program(s): All

Focussing on the historical and conceptual approaches to the relationship between data and automated decision-making (ADM) systems, this project situates key issues in historical context and canvasses the range of theoretical approaches brought to bear on describing ADM and assessing the social issues, concerns, and potentials it invokes.

Given the historical focus on data as a locus of concern (with respect to ownership, privacy, accuracy, bias, security, accountability), the data contribution focusses on issue mapping across sectors. The project compliments and draws on the work being done in other research programs and areas to discern common themes with respect to the issues raised by the collection, storage, and use of data for ADM across object domains.

RESEARCHERS

Mark Andrejevic

Prof Mark Andrejevic

Lead Investigator

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Chief Investigator

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Julian Thomas

Prof Julian Thomas

Chief Investigator

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ADM+S Chief Investigator Heather Horst

Prof Heather Horst

Chief Investigator

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Deborah Lupton

Prof Deborah Lupton

Chief Investigator

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ADM+S Investigator Rowan Wilken

Assoc Prof Rowan Wilken

Associate Investigator

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Paul Henman

Prof Paul Henman

Chief Investigator

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ADM+S Chief Investigator Mark Sanderson

Prof Mark Sanderson

Chief Investigator

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ADM+S Chief Investigator Jason Potts

Prof Jason Potts

Chief Investigator

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Diverse Experiences of ADM: Design, Curation and Use

PROJECT SUMMARY

Research Materials

Diverse Experiences of ADM: Design, Curation and Use

Focus Area(s): All
Research Program: People

This project examines the ways in which automated decision-making (ADM) is being integrated into the lives of diverse and non-dominant communities across Australia.

Attending to issues of equity and power, this project explores how different communities shape existing, emerging and future practices of ADM in an effort to understand and develop equitable futures.

RESEARCHERS

ADM+S Chief Investigator Heather Horst

Prof Heather Horst

Lead Investigator

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Deborah Lupton

Prof Deborah Lupton

Lead Investigator

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Sarah Pink

Prof Sarah Pink

Lead Investigator

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Cecily Klim

 

Rakesh Kumar

Rakesh Kumar

PhD Student

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Jackie Leach Scully profile picture

Prof Jackie Leach Scully

Chief Investigator

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Jeni Lee

Jeni Lee

Research Fellow

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Jiyoon Lee

Jiyoon Lee

PhD Student

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Robert Lundberg profile picture

Robert Lundberg

PhD Student

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Iris Maher

Thao Phan

Dr Thao Phan

Research Fellow

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Emma Quilty

Dr Emma Quilty

Research Fellow

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Yolande Strengers

Prof Yolande Strengers

Associate Investigator

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Georgia Van Toorn

Dr Georgia van Toorn

Research Fellow

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Ash Watson

Dr Ash Watson

Research Fellow

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Vaughan Wozniak-O'Connor

Dr Vaughan Wozniak-O’Connor

Research Fellow

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Dr Daniel Featherstone

Dr Daniel Featherstone

Research Fellow

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Indigo Holcombe-James Headshot

Dr Indigo Holcombe-James

Research Fellow

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ADM+S Associate Investigator Jenny Kennedy

Dr Jenny Kennedy

Associate Investigator

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PARTNERS

Consumer Health Forum of Australia Logo

Consumers Health Forum of Australia

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Data and Society logo

Data & Society Research Institute (US)

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Health Consumers NSW

Health Consumers NSW

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Data Ethics, Rights, and Markets

PROJECT SUMMARY

Blurred people moving

Data Ethics, Rights, and Markets

Focus Area(s): All
Research Program: Data

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

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

RESEARCHERS

Julian Thomas

Prof Julian Thomas

Lead Investigator

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Chief Investigator

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Axel Bruns, Chief Investigator with the ADM+S Centre

Prof Axel Bruns

Chief Investigator

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Paul Henman

Prof Paul Henman

Chief Investigator

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ADM+S Chief Investigator Dan Hunter

Prof Dan Hunter

Chief Investigator

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ADM+S Chief Investigator Andrew Kenyon

Prof Andrew Kenyon

Associate Investigator

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ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Chief Investigator

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ADM+S Investigator Christine Parker

Prof Christine Parker

Chief Investigator

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Sarah Pink

Prof Sarah Pink

Chief Investigator

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Chief Investigator

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ADM+S Chief Investigator Mark Sanderson

Prof Mark Sanderson

Chief Investigator

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Kimberlee Weatherall

Prof Kimberlee Weatherall

Chief Investigator

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ADM+S Associate Investigator Jake Goldenfein

Dr Jake Goldenfein

Associate Investigator

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ADM+S Investigator Ivana Jurko

Ivana Jurko

Partner Investigator

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PARTNERS

Australian Red Cross Logo

Australian Red Cross

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Data and Society logo

Data & Society Research Institute (US)

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OVIC Logo

Victorian Information Commissioner

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Mapping ADM Machines in Australia and Asia-Pacific

PROJECT SUMMARY

People walking in city centre

Mapping ADM Machines in Australia and Asia-Pacific

Focus Area(s): Social Services
Research Program: Machines

This project involves adopting the (draft) taxonomy for automated decision-making (ADM) in undertaking a mapping exercise of ADM machines in Social Services in Australia. A key purpose is to test and refine the taxonomy and to provide foundational empirical and conceptual knowledge of ADM in social services beyond Europe and North America, and into the Asia-Pacific region. This mapping exercise will provide necessary baseline empirical understanding of where ADM is and how it is being used.

The approach will use a critical data studies theoretical framework to develop a countermapping of ADM systems in social services. This approach views ADM as an assemblage of data systems and decision making in social-political context, and aims to build knowledge about what ADMs are being used in government, and how they are used, and who is effected by this.

RESEARCHERS

Paul Henman

Prof Paul Henman

Lead Investigator

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Lyndal Sleep profile picture

Dr Lyndal Sleep

Research Fellow

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PARTNERS

AlgorithmWatch Logo

Algorithm Watch (Germany)

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Data capacity and collaboration for ADM in the community sector

PROJECT SUMMARY

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Data capacity and collaboration for ADM in the community sector

Focus Area(s): Social Services
Research Program: Data

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

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

RESEARCHERS

ADM+S Chief Investigator Anthony McCosker

Assoc Prof Anthony McCosker

Lead Investigator

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Kimberlee Weatherall

Prof Kimberlee Weatherall

Chief Investigator

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ADM+S Investigator Kath Albury

Prof Kath Albury

Associate Investigator

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Jane Farmer

Prof Jane Farmer

Associate Investigator

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ADM+S Associate Investigator Jake Goldenfein

Dr Jake Goldenfein

Associate Investigator

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ADM+S Investigator Julia Stoyanovich

Assistant Prof Julia Stoyanovich

Partner Investigator

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Xiaofang Yao

Dr Xiaofang Yao

Research Fellow

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PARTNERS

Infoxchange

Infoxchange

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Civic Automated Decision-Making

PROJECT SUMMARY

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Civic Automated Decision-Making

Focus Area(s): All
Research Program: Data

This project supplements work on ethical automated decision-making (ADM) with a focus on civic commitments and concerns. It adds a consideration of politics and power to ethical approaches in the area of ADM and civic life.

Such an approach adds an additional layer to the question of whether ADM processes are ethical by considering how they promote civic life and democracy.

RESEARCHERS

Mark Andrejevic

Prof Mark Andrejevic

Lead Investigator

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Axel Bruns, Chief Investigator with the ADM+S Centre

Prof Axel Bruns

Chief Investigator

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ADM+S Associate Director Jean Burgess

Prof Jean Burgess

Chief Investigator

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ADM+S Chief Investigator Megan Richardson

Prof Megan Richardson

Chief Investigator

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ADM+S Chief Investigator Nic Suzor

Prof Nicolas Suzor

Chief Investigator

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Julian Thomas

Prof Julian Thomas

Chief Investigator

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Kimberlee Weatherall

Prof Kimberlee Weatherall

Chief Investigator

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ADM+S Associate Investigator Jake Goldenfein

Dr Jake Goldenfein

Associate Investigator

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ADM+S Chief Investigator Andrew Kenyon

Prof Andrew Kenyon

Associate Investigator

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Andrew Roberts

Prof Andrew Roberts

Associate Investigator

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ADM+S Investigator Robert Sparrow

Prof Robert Sparrow

Associate Investigator

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ADM+S Investigator Frank Pasquale

Prof Frank Pasquale

Partner Investigator

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ADM+S Investigator Karen Yeung

Prof Karen Yeung

Partner Investigator

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PARTNERS

Brooklyn Law School logo

Brooklyn Law School

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Data and Society logo

Data & Society Research Institute (US)

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OVIC Logo

Victorian Information Commissioner

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Considerate and Accurate Multi-party Recommender Systems for Constrained Resources

PROJECT SUMMARY

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Considerate and Accurate Multi-party Recommender Systems for Constrained Resources

Focus Area(s): News and Media, Health, Social Services, Transport and Mobilities
Research Program: Machines

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

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

RESEARCHERS

ADM+S Chief Investigator Mark Sanderson

Prof Mark Sanderson

Lead Investigator

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ADM+S Chief Investigator Christopher Leckie

Prof Christopher Leckie

Chief Investigator

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Julian Thomas

Prof Julian Thomas

Chief Investigator

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Jeffrey Chan

Dr Jeffrey Chan

Associate Investigator

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Danula Hettiachchi

Dr Danula Hettiachchi

Research Fellow

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Indigo Holcombe-James Headshot

Dr Indigo Holcombe-James

Research Fellow

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ADM+S Investigator Flora Salim

Prof Flora Salim

Associate Investigator

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PARTNERS

University of Amsterdam logo

University of Amsterdam

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Building Ethical Machines in Social Services: Examining, Evaluating, Building Fairness and Explainability in ADM

PROJECT SUMMARY

A mother and daughter smiling at a garden centre.

Building Ethical Machines in Social Services: Examining, Evaluating, Building Fairness and Explainability in ADM

Focus Area(s): Social Services
Research Program: Machines

A significant area of automated decision-making (ADM) in social services relates to the use of predictive measures – such as predictions of risk to children to abuse/neglect in child protection, predictions of recidivism or crime in policing and criminal justice, predictions of welfare/tax fraud in compliance systems, predictions of long term unemployment in employment services. While earlier and current versions of these systems are based on standard statistical analyses, they are increasingly having machine learning developed and deployed.

Despite these changes in the machine/algorithm design, the issues of bias, fairness and explainability are not substantially shifted and have not been dealt with in the past. Working with computer scientists, lawyers, social scientists, and users of social services, this project will engage with substantive empirical examples of ADM in disability services, child protection, criminal justice and social security to develop an understanding of what social service users and professionals regard as fairness and explanation.

RESEARCHERS

ADM+S Chief Investigator Paul Henman

Prof Paul Henman

Lead Investigator

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ADM+S Chief Investigator Dan Hunter

Prof Dan Hunter

Chief Investigator

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Terry Carney

Prof Terry Carney AO

Associate Investigator

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ADM+S Investigator Philip Gillingham

Dr Philip Gillingham

Associate Investigator

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Amelia Radke

Dr Amelia Radke

Associate Investigator

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Paul Harpur

Assoc Prof Paul Harpur

Associate Investigator

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PARTNERS

ACOSS logo

Australian Council of Social Service

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Australian Human Rights Commission logo

Australian Human Rights Commission

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Australian Law Reform Commission logo

Australian Law Reform Commission

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Australian Red Cross Logo

Australian Red Cross

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

PROJECT SUMMARY

Cash register with payment barcode in a shop in Delhi

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

Focus Area(s): News and Media, Social Services, Health, Transport and Mobilities
Research Program: People

This project is a review of the current state of ADM implementation, practices and visions in different regions in the Global South. It includes an analysis of academic and grey literature, online resources and interviews with key stakeholders in four underrepresented regions (Latin America, Anglophone Africa, South and Southeast Asia and Pacific Island Archipelagos).

Our focus upon decentering ADM works to challenge dominant narratives of the discourse, practice and adoption of ADM across the world.

RESEARCHERS

ADM+S Chief Investigator Heather Horst

Prof Heather Horst

Lead Investigator

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Edgar Gómez Cruz

Dr Edgar Gómez Cruz

Associate Investigator

Adam Sargent

Dr Adam Sargent

Associate Investigator

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Jolynna Sinanan

Dr Jolynna Sinanan

Associate Investigator

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