OCED Framework for Classifying of AI Systems

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Over the past few months we have seen more and more countries looking at how they can support and regulate the use and development of AI within their geographic areas. For those in Europe, a lot of focus has been on the draft AI Regulations. At the time of writing this post there has been a lot of politics going on in relation to the EU AI Regulations. Some of this has been around the definition of AI, what will be included and excluded in their different categories, who will be policing and enforcing the regulations, among lots of other things. We could end up with a very different set of regulations to what was included in the draft (published April 2021). It also looks like the enactment of the EU AI Regulations will be delayed to the end of 2022, with some people suggesting it would be towards mid-2023 before something formal happens.

I mentioned above one of the things that may or may not change is the definition of AI within the EU AI Regulations. Although primarily focused on the inclusion/exclusion of biometic aspects, there are other refinements being proposed. When you look at what other geographic regions are doing, we start to see some common aspects on their definitions of AI, but we also see some differences. You can imagine the difficulties this will present in the global marketplace and how AI touches upon all/many aspects of most businesses, their customers and their data.

Most of you will have heard of OCED. In recent weeks they have been work across all member countries to work towards a Definition of AI and how different AI systems can be classified. They have called this their OCED Framework for Classifying of AI Systems.

The OCED Framework for Classifying AI System is a tool for policy-makers, regulators, legislators and others so that they can assess the opportunities and risks that different types of AI systems present and to inform their national AI strategies.

The Framework links the technical characteristics of AI with the policy implications set out in the OCED AI Principles which include:

  • Inclusive growth, sustainable development and well-being
  • Human-centred values and fairness
  • Transparency and explainability
  • Robustness, security and safety
  • Accountability

The framework looks are different aspects depending on if the AI is still within the lab (sandbox) environment or is live in production or in use in the field.

The framework goes into more detail on the various aspects that need to be considered for each of these. The working group have apply the frame work to a number of different AI systems to illustrate how it cab be used.

Check out the framework document where it goes into more detail of each of the criterion listed above for each dimension of the framework.

Australia New AI Regulations Framework

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Over the past few weeks/months we have seen more and more countries addressing the potential issues and challenges with Artificial Intelligence (and it’s components of Statistical Analysis, Machine Learning, Deep Learning, etc). Each country has either adopted into law controls on how these new technologies can be used and where they can be used. Many of these legal frameworks have implications beyond their geographic boundaries. This makes working with such technology and ever increasing and very difficult challenging.

In this post, I’ll have look at the new AI Regulations Framework recently published in Australia.

[I’ve written posts on what other countries had done. Make sure to check those out]

The Australia AI Regulations Framework is available from, is a 240 page report giving 38 different recommendations. This framework does not present any new laws, but provides a set of recommendations for the government to address and enact new legislation.

It should be noted that a large part of this framework is focused on Accessible Technology. It is great to see such recommendations.  Apart from the section relating to Accessibility, the report contains 2 main sections addressing the use of Artificial Intelligence (AI) and how to support the implementation and regulation of any new laws with the appointment of an AI Safety Commissioner.

Focusing on the section on the use of Artificial Intelligence, the following is a summary of the 20 recommendations:

Chapter 5 – Legal Accountability for Government use of AI

Introduce legislation to require that a human rights impact assessment (HRIA) be undertaken before any department or agency uses an AI-informed decision-making system to make administrative decisions. When an AI decision is made measures are needed to improve transparency, including notification of the use of AI and strengthening a right to reasons or an explanation for AI-informed administrative decisions, and an independent review for all AI-informed administrative decisions.

Chapter 6 – Legal Accountability for Private use of AI

In a similar manner to governmental use of AI, human rights and accountability are also important when corporations and other non-government entities use AI to make decisions. Corporations and other non-government bodies are encouraged to undertake HRIAs before using AI-informed decision-making systems and individuals be notified about the use of AI-informed decisions affecting them.

Chapter 7 – Encouraging Better AI Informed Decision Making

Complement self-regulation with  legal regulation to create better AI-informed decision-making systems with standards and certification for the use of AI in decision making, creating ‘regulatory sandboxes’ that allow for experimentation and innovation, and rules for government procurement of decision-making tools and systems.

Chapter 8 – AI, Equality and Non-Discrimination (Bias)

Bias occurs when AI decision making produces outputs that result in unfairness or discrimination. Examples of AI bias has arisen in in the criminal justice system, advertising, recruitment, healthcare, policing and elsewhere. The recommendation is to provide guidance for government and non-government bodies in complying with anti-discrimination law in the context of AI-informed decision making

Chapter 9 – Biometric Surveillance, Facial Recognition and Privacy

There is lot of concern around the use of biometric technology, especially Facial Recognition. The recommendations include law reform to provide better human rights and privacy protection regarding the development and use of these technologies through regulation facial and biometric technology (Recommendations 19, 21), and a moratorium on the use of biometric technologies in high-risk decision making until such protections are in place (Recommendation 20).

In addition to the recommendations on the use of AI technologies, the framework also recommends the establishment of a AI Safety Commissioner to support the ongoing efforts with building capacity and implementation of regulations, to monitor and investigate use of AI, and support the government and private sector with complying with laws and ethical requirements with the use of AI.