The ADM+S Centre draws on our the collective specialist knowledge of our researchers and partner organisations to develop the following resources for researchers, government, non-for-profit and private organisations, as well as schools and the general public.
PUBLIC DASHBOARDS
Australian Digital Inclusion Index
Target audience: Government agencies, researchers, general public
Research project: Australian Digital Inclusion Index
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The Australian Digital Inclusion Index uses data from the Australian Internet Usage Survey to measure digital inclusion across three dimensions of Access, Affordability and Digital Ability. We explore how these dimensions vary across Australia and across different social groups.
To cite: 2023 Australian Digital Inclusion Index. (2023). Interactive data dashboards. Telstra.
Mapping the Digital Gap
Target audience: Government agencies, researchers, general public
Research project: Mapping the Digital Gap
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This First Nations page provides a snapshot of the scale of the Digital Gap for First Nations people compared with other Australians, by remoteness categories. It includes results from 10 remote and very remote communities surveyed under the Mapping the Digital Gap project (2022-2024).
To cite: Thomas, J., McCosker, A., Parkinson, S., Hegarty, K., Featherstone, D., Kennedy, J., Holcombe-James, I., Ormond-Parker, L., & Ganley, L. (2023). Measuring Australia’s Digital Divide: Australian Digital Inclusion Index: 2023. Melbourne: ARC Centre of Excellence for Automated Decision-Making and Society, RMIT University, Swinburne University of Technology, and Telstra.
FRAMEWORKS AND TOOLKITS
AI Sub Zero Bias Cards
Target audience: For researchers and practitioners to further interrogate and explore LLMs as analytical tools
Research project: Sub-Zero. A Comparative Thematic Analysis Experiment of Robodebt Discourse Using Humans and LLMs
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The AI Sub Zero Bias Cards are a generative, analytical, and reflexive design toolkit created to help users structure prompts and interrogate bias in outputs of generative AI tools such as Large Language Models. The toolkit comprises of 58 cards, framed as provocations, across three card-categories: (1) Structure: These provocations interrogate decisions being made during the creation of prompts (i.e., semantic phrasing, organisation, and configuration); (2) Consequences: These provoke users to reflect on the generated outcomes in response to the prompts and their implications; (3) Output: Drawing on creativity principles, these provocations explore how reformatting and reframing the generated outputs into alternative structures can facilitate reflexive thinking.
Towards Resilient Communities: Data capability and resource mapping for disaster preparedness
Target audience: Disaster management organisations, Communities
Research project: Data for Social Good: Non-profit sector data projects
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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.
Responsible and timely community data practices along with accessible platforms to support data availability are central to realising benefits on the ground. 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. The team developed a model for involving communities in the data-gathering process and supporting them to improve disaster preparedness through an open mapping platform.
To cite: McCosker, A., Kang, Y.B., Shaw, F. (2023) ‘Towards Resilient Communities: Data Capability and Resource Mapping for Disaster Preparedness’, Swinburne University of Technology and ARC Centre of Excellence for Automated Decision-Making and Society, Melbourne. hhtps://doi.org/10.26185/hgz2-h212
A Data Capability Framework for the not-for-profit sector
Target audience: Not-for-profit sector
Research project: Data for Social Good: Non-profit sector data projects
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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.
To cite: McCosker A., Shaw F., Yao X., Albury K. (2022). A Data Capability Framework for the Not-for-Profit Sector. Swinburne University, Melbourne, DOI: https://doi.org/10.25916/h2s6-r178
See also
Building Data Capacity in the Not-For-Profit Sector: Interim Report. Swinburne University: Melbourne,
https://doi.org/10.26185/ey72-s303 | Developing data capability with non-profit organisations using
participatory methods. Big Data & Society, 9(1), https://doi.org/10.1177/20539517221099882
Building a Trauma-Informed Algorithmic Assessment Toolkit
Target audience: Social service organisations
Research project: Trauma-informed AI: Developing and testing a practical AI audit framework for use in social services
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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.
To cite: Maitra, S., Sleep, L., Fay, S., Henman, P. (2024) Building a Trauma-Informed Algorithmic Assessment Toolkit, Project Report. Brisbane: ARC Centre of Excellence for Automated Decision-Making and Society, University of Queensland, DOI: 10.60836/f01c-4a18.
LEARNING RESOURCES
Keywords of the Datafied State
Target audience: Teachers seeking curriculum to explore the state’s relationship with technology.
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ADM+S partner organisation Data and Society have released a curated collection of essays bringing together global scholars, including ADM+S researchers Dr Georgia van Toorn, Dr Chris O’Neill and Prof Mark Andrejevic for their essay, ‘Automation’ (co-authored with Maitreya Shah).
Keywords of the Datafied State is a collection of essays on concepts that are central to understanding the relationship between government and technology, and how it differs across geographies.
Keywords of the Datafied State was edited by Jenna Burrell, Ranjit Singh, and Patrick Davison.
To cite: Burrell, Jenna, Ranjit Singh, and Patrick Davison, eds. Keywords of the Datafied State. Data & Society Research Institute. http://dx.doi.org/10.2139/ssrn.4734250
Generative AI Concepts
Target audience: Public service workers wanting to understand how automation is used in the public sector, as well as the general public.
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This page offers basic GenAI terms and examples, developed in collaboration with the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S) and partner organisation the Office of the Victorian Information Commissioner (OVIC).
Researchers have developed diagrams to visually communicate the matrix of terms associated with Artificial Intelligence (AI), and categorised keywords into either Operational, Technical, and Regulatory terms.
To cite: Fan Yang, Jake Goldenfein, and Kathy Nickels, ‘GenAI concepts’, ADM+S and OVIC (Web Page, 2024), https://www.admscentre.org.au/genai-concepts/
Learn about AI for Text Journalists
Target audience: Text Journalists
Subject areas: Large Language Models (LLMs), Prompt Engineering
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Visit The Walkley Foundation AI and Journalism Training Program to access handouts and learning materials for Session 2: Learn about AI for Text Journalists.
This session is part of an eight-part webinar series on AI and journalism, hosted and supported by the Walkley Public Fund. Each session provides an overview of a specific area of journalism, explores opportunities and risks, and provides a practical activity or question about implementation to try out as homework.
This session features Trainer, Dr James Meese and expert speakers Lisa Main and Craig McCosker.
We Are AI
Target audience: Anyone can use this material to facilitate a learning group or educate themselves on the topic of AI. (No math, programming skills, or existing understanding of AI is required.)
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Because of how important AI is in our lives, we should understand how it works so that we can control it together! The goal of this 5-week learning circle course is to introduce the basics of AI, discuss some of the social and ethical dimensions of the use of AI in modern life, and empower individuals to engage with how AI is used and governed.
Course materials were developed under the leadership of Dr. Eric Corbett and Dr. Julia Stoyanovich.
To cite: Corbett, E., Stoyanovich, J., Sloane, M., Falaah, A.K., McDermott, M., Margraf, B., Peterson, G., Lambert, J., Coughlin-Prego, S., Bohra, K. (2022). We arę AI. Comics.
More-than-Human Wellbeing
Target audience: Year Levels 9-12
Subject areas: Digital Technologies, Media Arts, Biological Sciences, Health & Physical Education
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The More-than-Human Wellbeing Learning Activities and Resources provides students with an understanding of digital technologies, data and their application in the context of health information in an era of emerging technologies.
To cite: Heck, E., Lupton, D. (2023) More-Than-Human Wellbeing. Curriculum resource.
Artificial Intelligence (AI) for Social Impact
Target audience: Policymakers, researchers, and non-specialists in emerging economies
Subject areas: Artificial Intelligence (AI), AI Ethics and Governance, AI and Social Impact
Duration: 1h 10 min
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This course is designed for policymakers, and anyone interested in learning about AI and its potential—especially about how it can be harnessed to foster positive societal change. It delivers solid foundational knowledge on AI, upon which more advanced applications can be built.
It covers AI fundamentals including explanation of terminologies, and practical uses—providing insights into Generative AI (genAI), how it operates and its current applications. Importantly, related ethical considerations are discussed, as well as cutting-edge developments in AI for social impact.
To cite: Nguyễn, D. (2024). Artificial Intelligence for Social Impact. Asian Development Bank Institute. Short Course.
The Expert Explained Collection
Subject areas: The ADM+S Expert Explained video collection addresses key questions and topics of discourse to do with AI and ADM systems, the research environment, methods, and more.
Target audience: Our researchers simplify complex topics, suitable for a general audience with varying levels of age or expertise.
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Series produced by Natalie Campbell
SHORT COURSES & TRAINING
Training workshops, short courses & briefings
Our training workshops, short courses and briefings aim to translate the Centre’s extraordinary reservoir of specialist knowledge to develop industry capacity and expertise in ADM. We have delivered training to policymakers, practitioners, regulators, businesses, utility providers, community workers and advocates, teachers, librarians, artists, CEOs and CTOs of start-up companies and military officers.
Learn about AI for Text Journalists
Target audience: Text Journalists
Subject areas: Large Language Models (LLMs), Prompt Engineering
Read more
Visit The Walkley Foundation AI and Journalism Training Program to access handouts and learning materials for Session 2: Learn about AI for Text Journalists.
This session is part of an eight-part webinar series on AI and journalism, hosted and supported by the Walkley Public Fund. Each session provides an overview of a specific area of journalism, explores opportunities and risks, and provides a practical activity or question about implementation to try out as homework.
This session features Trainer, Dr James Meese and expert speakers Lisa Main and Craig McCosker.
Artificial Intelligence (AI) for Social Impact
Target audience: Policymakers, researchers, and non-specialists in emerging economies
Subject areas: Artificial Intelligence (AI), AI Ethics and Governance, AI and Social Impact
Duration: 1h 10 min
Read more
This course is designed for policymakers, and anyone interested in learning about AI and its potential—especially about how it can be harnessed to foster positive societal change. It delivers solid foundational knowledge on AI, upon which more advanced applications can be built.
It covers AI fundamentals including explanation of terminologies, and practical uses—providing insights into Generative AI (genAI), how it operates and its current applications. Importantly, related ethical considerations are discussed, as well as cutting-edge developments in AI for social impact.
To cite: Nguyễn, D. (2024). Artificial Intelligence for Social Impact. Asian Development Bank Institute. Short Course.
OPEN SOURCE SOFTWARE
Factchecking – presentations
Target audience: Researchers, Software Developers
Code type: Python
Research project: Quantifying and Measuring Bias and Engagement
The Australian Search Experience – 2021
Target audience: Researchers, Software Developers
Content type: HTML
Research project: The Australian Search Experience
Australian Ad Observatory Dashboard API
Target audience: Researchers, Software Developers
Content type: Javascript
Research project: The Australian Ad Observatory
Community Resource Mapping Platform
Target audience: Researchers, Software Developers
Content type: Dataset
Research project: Data mapping and ADM to advance humanitarian action and preparedness
Mobile Ad Observatory
Target audience: Researchers, Software Developers
Content type: Javascript
Research project: The Australian Ad Observatory
DIGITAL MEDIA & MEDIA RELEASES
Podcast Series
Learn more about how automated decision-making (ADM) is being incorporated, reinvented or resisted as part of everyday lives and how we can make it responsible, ethical and inclusive.
ADM+S Documentaries
The ADM+S Centre uses ethnographic research and people-centred documentary practice to research and advocate for ethical, inclusive and responsible automated decision-making.
Media Releases
Access past media releases for significant Centre announcements.