To support the adoption of AI in Australia and empower local industry to create world-class technology, the Responsible AI Network (RAIN) has curated a list of resources and best practice guidance that align with RAIN's seven actionable pillars:
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Law |
Navigating AI: Analysis and guidance on the use and adoption of AIThis report provides a deepened understanding of the AI regulatory landscape globally and within Australia and the need to continue to progress a conversation around appropriate regulation. Stakeholders from across government and industry contributed to the development of this report, including a selection of AIIA members who were interviewed by KPMG. This report is ideal for leaders interested in or tasked with creating policies, governance and oversight of AI technology. EU AI ActThe world’s first, comprehensive AI law was finally agreed by lawmakers in the European Union in late 2023. In collaboration with Reuters, the World Economic Forum has summarised some of the key elements of the EU AI Act in this article. |
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Standards |
Artificial Intelligence Management System Standard
Published in late 2023, ISO/IEC 42001 is the world’s first international standard that specifies requirements for an Artificial Intelligence Management System (AIMS) within an organisation. This comprehensive resource outlines how an organisation might use AI responsibly and effectively.
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Principles |
Implementing Australia's AI Ethics Principles reportTo help bridge the gap between the Australian AI Ethics Principles and the business practice of responsible artificial intelligence (RAI), the National AI Centre (NAIC) has worked with Gradient Institute to develop 'Implementing Australia’s AI Ethics Principles: A selection of Responsible AI practices and resources.' The report explores some of the practical steps needed to implement the Australian Government’s eight AI ethics principles, explaining each practice and its organisational context, including the roles that are key to successful implementation. Practices such as impact assessments, data curation, fairness measures, pilot studies and organisational training are some of the simple but effective approaches outlined in this report. Read the report to learn how to implement Australia's AI Ethics Principles to create responsible AI practices. OECD - Artificial Intelligence and Responsible Business ConductOver the last decade, rapid advancements in artificial intelligence (AI) and machine learning have opened up new opportunities for productivity, economic development, and advancements in various sectors, from agriculture to healthcare. While current and future AI applications have the potential to advance responsible business, they can also pose risks to human rights, the environment and other important elements of responsible business conduct as addressed in the OECD Guidelines for multinational enterprises. On the other hand, the use of AI in hiring, law enforcement, lending, and other fields could lead to discriminatory outcomes through the reliance on inappropriately biased data or algorithms. Relying on and collecting increasing amounts of personal data, there is a risk of AI adversely impacting privacy. When used in autonomous weapons systems, AI could lead to impacts on the human right to life, personal security, and due process. This background paper provides an overview of the different types of AI applications, the ways in which humans and AI can interact, and potential adverse human rights and societal impacts that AI technology may introduce.
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Governance |
eSafety Commissioner: Generative AI – position statementRecent advancements have rapidly improved generative AI due to the availability of more training data, enhanced artificial neural networks with larger datasets and parameters, and greater computing power. Some experts now claim AI systems are moving rapidly towards ‘human-competitive intelligence’. This could impact almost every aspect of our lives, in both positive and negative ways. The possible threats related to generative AI are not just theoretical – real world harms are already present. The online industry can take a lead role by adopting a Safety by Design approach.Technology companies can uphold these principles by making sure they incorporate safety measures at every stage of the product lifecycle. eSafety recognises the need to safeguard the rights of users, preserve the benefits of new tools and foster healthy innovation. Read the full position statement. Navigating AI Governance: A Comprehensive Look at Existing and New EU and US AI RegulationsAn overview of EU, US, and China AI regulations and governance initiatives, including key action points to help organizations with AI compliance. In this blog post, Daiki aim to offer pointers to both existing and new EU and US AI regulations and governance initiatives. Additionally, we will provide some key action points to help organizations effectively prepare for regulatory changes and navigate the complexities of AI compliance. |
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Leadership |
IEEE SA Standards Association: Prioritising People and Planet as the Metrics for Responsible AIWhat are the metrics of success for Responsible AI? Defining how to be responsible with artificial intelligence systems (AIS) is critical for modern technological design.This report provides direction for business readers so they can utilise these metrics - large enterprises as well as small - and medium-sized businesses (SMBs) - while also informing policy makers of the issues these metrics will create for citizens as well as buyers. Microsoft and Tech Council Australia: Australia's Generative AI Opportunity report (July 2023)Generative AI (GAI) represents a substantial economic opportunity for Australia, with the potential to add tens of billions to the economy by 2030. But where to start? Developed.‘Australia’s Generative AI Opportunity’ report answers three crucial questions.
Responsible AI Index - a study of over 400 organisationsThe study was conducted by Fifth Quadrant CX, led by the Responsible Metaverse Alliance, supported by Gradient Institute and sponsored by IAG and Transurban. Key details:
AI Ecosystem Report 2023
Commissioned by the National AI Centre (NAIC) and written by CSIRO's Data61, Australia's AI Ecosystem - Catalysing an AI Industry provides businesses, investors, government and research institutions with the most up-to-date analysis of Australia’s AI ecosystem and how to advance it. |
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Technology |
Tools for trustworthy AI: A framework to compare implementation tools for trustworthy AIAs AI advances across economies and societies, stakeholder communities are actively exploring how best to encourage the design, development, deployment and use of AI that is human-centred and trustworthy. This report presents a framework for comparing tools and practices to implement trustworthy AI systems as set out in the OECD AI Principles. The framework aims to help collect, structure and share information, knowledge and lessons learned to date on tools, practices and approaches for implementing trustworthy AI. As such, it provides a way to compare tools in different use contexts. The framework will serve as the basis for the development of an interactive, publicly available database on the OECD.AI Policy Observatory. This report informs ongoing OECD work towards helping policy makers and other stakeholders implement the OECD AI Principles in practice. Responsible Technology Review Template – AtlassianLeading Australian software company Atlassian has developed and shared a Responsible Technology Review Template. With input and advice from the UTS Human Technology Institute, the tool can be used to help organisations review and avoid AI-related unintentional bias and harmful, unintended consequences. To learn more about Atlassian’s approach to the development of responsible technologies, and to download the tool, go to Atlassian’s Responsible Technology Principles. |
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Design |
What is human-centred AI and why do you need it?Discover the fundamentals of human-centred design for AI and why it's important in this short clip produced by the University of Technology’s Human Technology Institute (HTI) in collaboration with the National AI Centre (NAIC). Watch the video What is human-centred AI and why do you need it?. Responsible AI Pattern CatalogueDeveloped by CSIRO's Data61 and published by IEEE software, this collection of patterns for the design of responsible AI systems can be embedded into AI systems as a product feature or a piece of structural design across multiple architectural elements. In software engineering, a pattern is a reusable solution to a problem commonly occurring within a given context in software development. The focus is on patterns that practitioners and broader stakeholders can undertake to ensure that responsible AI systems are responsibly developed throughout the entire lifecycle with different levels of governance. The current version of our Responsible AI Pattern Catalogue contains over 60 patterns to assist stakeholders at all levels in implementing responsible AI in practice. Towards Responsible AI in the Era of ChatGPT: A Reference Architecture for Designing Foundation Model-based AI SystemsThe release of ChatGPT, Bard, and other large language model (LLM)-based chatbots has drawn huge attention on foundations models worldwide. There is a growing trend that foundation models will serve as the fundamental building blocks for most of the future AI systems. To address the new challenges of responsible AI and moving boundary and interface evolution, we propose a reference architecture for designing foundation model-based AI systems. Towards Responsible AI in the Era of ChatGPT: A Reference Architecture for Designing Foundation Model-based AI Systems provides readers with the fundamental building blocks to design future AI systems. Discover them and read the research [PDF · 227KB]. Microsoft’s HAX ToolkitDeveloped by Microsoft Research and Microsoft’s advisory body on AI Ethics, the Human AI Toolkit is a comprehensive library of practical resources and tools for technology and design teams. Google’s People + AI GuidebookGoogle’s People + AI Guidebook is a set of methods, best practices and examples for designing with AI, incorporating key elements of responsible AI throughout. |