eSafety Commissioner: Generative AI – position statement
Recent 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 Regulations
An 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.
IEEE SA Standards Association: Prioritizing People and Planet as the Metrics for Responsible AI
What 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.
While common business performance metrics focus on financial indicators primarily, organisations risk causing unintended harm when issues of human well-being or ecological sustainability are not prioritised in their planning.
Read the report [PDF · 9.7MB].
OECD - Artificial Intelligence and Responsible Business Conduct
Over 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.
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.
- How will GAI impact occupations and the workforce?
- What opportunities does GAI present for Australian industries?
- How can Australian businesses seize this potentially billion-dollar opportunity?
Navigating AI: Analysis and guidance on the use and adoption of AI
This 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.
Read the report [PDF · 3.3MB].
Responsible AI Index - a study of over 400 organisations
The 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:
- On average 82% of respondents believe they’re taking a best-practice approach to AI, but on closer inspection, only 24% are taking deliberate actions to ensure their own AI systems are developed responsibly.
- 60% of organisations surveyed have an enterprise-wide AI strategy that is tied to their wider business strategy, compared with 51% in 2021.
- Only 34% of organisations that have an enterprise-wide AI strategy have a CEO personally invested in driving the strategy.
- Organisations where the CEO is responsible for driving the AI strategy have a higher RAI Index score of 66 compared with a score of 61 for those where the CEO is not taking the lead.
- 61% of organisations now believe the benefits of taking a responsible approach to AI outweigh the costs.
- Evidence from the Second Edition of the Responsible AI Index (fifthquadrant.com.au).
Responsible AI Pattern Catalogue
Developed 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 Systems
The 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].
Tools for trustworthy AI: A framework to compare implementation tools for trustworthy AI
As 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.