How we use artificial intelligence and machine learning

AI is a broad term used to describe a collection of technologies able to solve problems and perform tasks without direct human involvement. These tasks could include things like data analytics, suggesting recommendations, making predictions, natural language processing, image or text recognition, or other tasks that process large amounts of information much quicker than humans can.

AI systems may be pre-programmed to only follow certain rules using a static dataset. Other AI systems use memory to learn and improve over time based on the system’s own outputs. This kind of AI is known as machine learning, and uses algorithms to solve tasks given to them by humans based on large and dynamic datasets.

Using AI and machine learning can help us to understand our customers’ needs better by considering a broad range of information such as usage patterns, network performance and demographics data.

For example, we may use an AI solution to analyse a large set of data to identify and predict faults and issues that may impact our services, allowing for quicker rectification or prevention. These faults may not be detected by human review or may have taken a very long time to detect.

Sometimes, we may use AI or machine learning to make automated decisions, like allowing the purchase of a device online or offering products or services to customers on credit. Our commitment to responsible AI includes providing transparency so individuals can understand when they are being significantly impacted by an automated decision made by AI, when an AI system is engaging with them, what the system is doing and why, and have a timely process to challenge the use or outcomes of the AI system where there are significant impacts.

At Telstra, we have a commitment to Responsible AI. When implementing and using AI systems, we consider and adhere to the AI Ethics Framework developed by the Australian Government, which includes the AI Ethics Principles, as well as the broader human, societal and environmental impacts of those systems and the decisions they make and acting in accordance with the law in all the jurisdictions in which we operate.

The AI Ethics Principles are:

• Human, societal and environmental wellbeing: AI systems should benefit individuals, society and the environment.
• Human-centred values: AI systems should respect human rights, diversity, and the autonomy of individuals.
• Fairness: AI systems should be inclusive and accessible, and should not involve or result in unfair discrimination against individuals, communities or groups.
• Privacy protection and security: AI systems should respect and uphold privacy rights and data protection, and ensure the security of data.
• Reliability and safety: AI systems should reliably operate in accordance with their intended purpose.
• Transparency and explainability: There should be transparency and responsible disclosure so people can understand when they are being significantly impacted by AI, and can find out when an AI system is engaging with them.
• Contestability: When an AI system significantly impacts a person, community, group or environment, there should be a timely process to allow people to challenge the use or outcomes of the AI system.
• Accountability: People responsible for the different phases of the AI system lifecycle should be identifiable and accountable for the outcomes of the AI systems, and human oversight of AI systems should be enabled.

Our goal is to ensure that we fully understand any potential positive and negative impacts, and possible unintended consequences, that our AI systems can have on our customers, our people, and the community in which we operate, and to seek to make those impacts positive, fair, and sustainable.

We are also committed to the protection and security of our customers’ personal information as outlined in Telstra's Privacy Statement and we comply with all relevant privacy legislation.