Australia New AI Regulations Framework
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 tech.humanrights.gov.au, 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.
Responsible AI: Principles & Standards around the World
During 2019 there was been a increase awareness of AI and the need for Responsible AI. During 2020 (and beyond) we will see more and more on this topic. To get you started on some of the details and some background reading, here are links to various Principles and Standards for Responsible AI from around the World.
|EU AI Ethics Guidelines||The Ethics Guidelines for Trustworthy Artificial Intelligence developed by EU High-Level Expert Group on AI highlights that trustworthy AI should be lawful, ethical and robust. Puts forward seven key requirements for AI systems should meet in order to be deemed trustworthy, including among others diversity, non-discrimination, societal and environmental well-being, transparency and accountability.|
|OECD principles on Artificial Intelligence||OECD’s member countries along with partner countries adopted the first ever set of intergovernmental policy guidelines on AI, agreeing to uphold international standards that aim to ensure AI systems are designed in a way that respects the rule of law, human rights, democratic values and diversity. They emphasize that AI should benefit people and the planet by driving inclusive growth, sustainable development and well-being.|
|CoE: Human Rights impacts of Algorithms||Council of Europe draft recommendation on the human rights impacts of algorithmic AI systems, released for consultation in August 2019 and to be adopted in early 2020. The document explicitly refers to the UN Guiding Principles on Business and Human Rights as a guidance for due diligence process and Human Rights Impact Assessments.|
|IEEE Global Initiative: Ethically Aligned Design||Ethically Aligned Design (EAD) Document is created to educate a broader public and to inspire academics, engineers, policy makers and manufacturers of autonomous and intelligent systems to take action on prioritizing ethical considerations. The general principles for AI design, manufacturing and use include: human rights, wellbeing, data agency, effectiveness, transparency, accountability, awareness of misuse, competence. The unique IEEE P7000 Standards series address specific issues at the intersection of technology and ethics and aimed to empower innovation across borders and enable societal benefit.|
|UN Sustainable Development Goals||The UN Sustainable Goals include the annual AI for Good Global Summit is the leading UN platform for global and inclusive dialogue on how artificial intelligence could help accelerate progress towards the Global Goals.|
|UN Business and Human Rights||The UN Guiding Principles on Business and Human Rights (UNGPs)gives a framework offering a roadmap to navigate responsibility-related challenges, rapid technological disruption and rising inequality, business has a unique opportunity to implement human-centered innovation by taking into account social, ethical and human rights implications of AI.|
|EU Collaborative Platforms and Social Learning||Several EU countries have articulated their ambitions related to artificial intelligence, it is of paramount importance to find your unique voice, track and join essential conversations, strategically engage in collective efforts and leave meaningful digital footprint.|
Always watching, always listening. Be careful with your data
The saying ‘Big Brother is Watching’ has been around a long time and typically gets associated with government organisations. But over the past few years we have a few new Big Brothers appearing. These are in the form of Google and Facebook and a few others.
These companies gather lots and lots. Some companies gather enormous amounts of data. This data will include details of your interactions with the companies through various websites, applications, etc. But some are gathering data in ways that you might not be aware. For example, take this following video. Data is being gathered about what you do and where you go even if you have disconnected your phone.
Did you know this kind of data was being gathered about you?
Just think of what they could be doing with that data, that data you didn’t know they were gathering about you. Companies like these generate huge amounts of income from selling advertisements and the more data they have about individuals the more the can understand what they might be interested. The generate customer profiles and sell expensive advertising based on having these very detailed customer profiles.
But it doesn’t stop there. Recently Google bought Fitbit. Just think about what they can do now. Combining their existing profiles of you as a person with you activities throughout every day, week and month. Just think about how various health and insurance companies would love to have this data. Yes they would and companies like Google would be able to charge these companies even more money for this level of detail on individuals/customers.
But it doesn’t stop there. There have been lots of reports of various apps sharing health and other related data with various companies, without their customers being aware this is happening.
What about Google Assistant? In a recent article by MIT Technology Review title Inside Amazon’s plan for Alexa to run your entire life, they discuss how Alexa can be used to control virtually everything. In this article Alexa’s cheif scientist say “plan is for the voice assistant to move from passive to proactive interactions. Rather than wait for and respond to requests, Alexa will anticipate what the user might want. The idea is to turn Alexa into an omnipresent companion that actively shapes and orchestrates your life. This will require Alexa to get to know you better than ever before.” When combined with other products this will allow “these new products let Alexa listen to and log data about a dramatically larger portion of your life“.
Just imagine if Google did the same with their Google Assistant! Big Brother isn’t just Watching, they are also Listening!
There has been some recent report of Google looking to get into Banking by offering checking accounts. The project, code-named Cache, is due to launch in 2020. Google has partnered with Citigroup and a credit union at Stanford University, which will administer the accounts. Users will be able to access their accounts through Google’s digital payment platform, Google Pay.
And there are the reports of Google having access to the health records of over 50 million people. In addition to this, Google has signed a deal with Ascension, the second-largest hospital system in the US, to collect and analyze millions of Americans’ personal health data. Ascension operates in 150 hospitals in 21 states.
What if they also had access to your banking details and spending habits? Google is looking at different options to extend financial products from the google pay into more main stream banking. There has been some recent report of them looking at offering current accounts.
I won’t go discussing their attempts at Ethics and their various (failed) attempts at establishing and Ethics Advisory Board. This has been well documented elsewhere.
Things are getting a bit scary and the saying ‘Big Brother is Watching You’, is very, very true.
In the ever increasing connected world, all of us have a responsibility to know what data companies are gathering on us. We need to decide how comfortable we are with this and if you aren’t then you need to take steps to ensure you protect yourself. Maybe part of this protection requires us to become less connected, stop using some apps, turn off more notification, turn off updates, turn off tracking, etc
While taking each product or offering individually, it may seem ok to us for Google and other companies to offer such services and to analyze our data to provide a better service. But for most people the issues arise when each of these products start to be combined. By doing this they get to have greater access and understanding our our data and our behaviors. What role does (digital) ethics play in all of this? This is something for the company and the employees to decide where things should stop. But when/how do you decide this? when do you/they know things have gone too far? how can you undo some of this work to go back to an acceptable level? what is an acceptable level and how do you define this?
As yo can see there are lots of things to consider and a vital component is the role of (digital) ethics. All organizations who process and analyze data need to have an ethics board and ethics needs to be a core part of every project. To support this everyone needs more training and awareness of ethics and what is acceptable or not.
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