HTI has partnered with CSIRO’s National Artificial Intelligence Centre to produce a series of training videos aimed at people who are currently using or looking to use AI in their organisation. These videos provide guidance on how they can make responsible, human-focussed decisions regarding AI technology.

This video series is designed to give a crash course in human-centred AI in easy-to-understand language, including why AI is so transformative, why governance matters, and how you can ensure that AI is used responsibly in your business. The aim of the videos is to equip decision makers with the strategic AI skills that they need to consider how new technologies can be designed, implemented and used in ways that embed human values. 

This work is part of HTI’s Skills Lab which was established to build Australia’s capability in strategic skills associated with AI and other technology, by building skills in procurement, implementation and oversight of AI. 

What is AI?

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Transcript

[Upbeat music plays. The UTS logo appears on screen, followed by the title: "What is AI?"]

Artificial intelligence is core to how businesses operate today. It's the technology powering your phone, targeting your customers on social media, and helping you recruit. Whether you know it or not, your organisation relies on multiple AI systems every day.

They might employ AI to help them be more efficient, or to improve how they engage with customers. The Human Technology Institute's research reveals that almost every Australian business relies on multiple AI systems today.

You may only be aware of a fraction of the AI applications that your employees use at work, often without any official sign-off from management or IT. Some of these AI systems are valuable and low-risk. For example, AI-powered navigation systems. But others can introduce a range of risks and challenges, from cyber security concerns to the threat of physical harm.

As AI becomes an essential part of doing business, every business leader needs to cultivate what we call a minimum viable understanding around AI. And this starts with understanding how AI systems work, and why managing them carefully is critical to your organisation's success.

AI is challenging to define, partly because our understanding of AI changes over time. When the field of AI began in the 1950s, AI systems tried to mimic how humans made decisions. These became known as expert systems.

Thanks to massive increases in data and computing power, the last decade has seen the rise of machine learning. This is where digital systems apply algorithms to large historical data sets to learn deep patterns. This allows them to make predictions when applied to new situations.

Most recently, generative AI has changed the way we think about the possibilities of AI systems. Applications like ChatGPT and DALL·E rely on models trained on huge amounts of data to produce fluent text, novel images, and even video from simple text prompts.

It's critical to remember that all AI systems are based on maths, not magic. Machine learning is underpinned by statistics, linear algebra, probability theory and calculus. While impressive AI systems are powered by complex algorithms and vast amounts of computing power, these systems do not possess common sense, interpersonal skills, or a true understanding of the world. They can and do fail in many different ways.

As a business leader, you can think of AI as being a very broad collective term for digital computer systems that have three characteristics.

First, AI systems do impressive things. AI systems combine algorithms and data to do things we have traditionally expected only of humans, such as predicting outcomes, classifying complex information, optimising processes, or generating content. Many of the largest large language models are also remarkably flexible, able to do many of these tasks through the same interface.

Second, AI systems tend not to be explicitly programmed. Neural networks in particular work by learning from data, often finding patterns and relationships that would be impossible for a human being to discern. They are therefore deeply influenced by the data on which they are trained, which can result in errors and biased outputs.

Third, AI systems tend to be unpredictable and opaque. They produce different outputs depending on how they've been trained and the input they are given. It takes special effort to understand how and why they come to a particular conclusion or decision.

All of this means that AI systems are more than just another IT application for your business. They offer huge promise, but also require special attention to manage safely and responsibly.

This video series is designed to give you a crash course in human-centred AI. In the videos that follow, we will cover why AI is so transformative, why governance matters, and how you can ensure that AI is used responsibly in your business.

[Music fades out. UTS and Human Technology Institute logos appear.]

AI is crucial for modern business operations, driving technologies like smartphones, social media targeting, and recruitment. While some AI systems, like navigation tools, pose minimal risk, others introduce cybersecurity and safety concerns. As AI becomes fundamental to business, leaders must develop a basic understanding of its workings and the importance of managing it carefully. 

AI encompasses a broad range of digital systems that perform human-like tasks, learn from data without explicit programming, and can operate unpredictably and opaquely. Managing these risks  necessitates careful management to harness AI’s potential safely and responsibly.

What is human-centred AI and why do you need it?

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Transcript

What is AI? Artificial intelligence is core to how businesses operate today. It's the technology powering your phone, targeting your customers on social media, and helping you recruit. Whether you know it or not, your organisation relies on multiple AI systems every day. They might employ AI to help them be more efficient or to improve how they engage with customers.

The Human Technology Institute's research reveals that almost every Australian business relies on multiple AI systems today. You may only be aware of a fraction of the AI applications that your employees use at work, often without any official sign-off from management or IT. Some of these AI systems are valuable and low-risk. For example, AI-powered navigation systems. But others can introduce a range of risks and challenges, from cyber security concerns to the threat of physical harm.

As AI becomes an essential part of doing business, every business leader needs to cultivate what we call a minimum viable understanding around AI. And this starts with understanding how AI systems work and why managing them carefully is critical to your organisation's success.

AI is challenging to define, partly because our understanding of AI changes over time. When the field of AI began in the 1950s, AI systems tried to mimic how humans made decisions. These became known as expert systems. Thanks to massive increases in data and computing power, the last decade has seen the rise of machine learning. This is where digital systems apply algorithms to large historical data sets to learn deep patterns. This allows them to make predictions when applied to new situations.

Most recently, generative AI has changed the way we think about the possibilities of AI systems. Applications like ChatGPT and DALL·E rely on models trained on huge amounts of data to produce fluent text, novel images and even video from simple text prompts.

It's critical to remember that all AI systems are based on maths, not magic. Machine learning is underpinned by statistics, linear algebra, probability theory and calculus. While impressive AI systems are powered by complex algorithms and vast amounts of computing power, these systems do not possess common sense, interpersonal skills or a true understanding of the world. They can and do fail in many different ways.

As a business leader, you can think of AI as being a very broad collective term for digital computer systems that have three characteristics. First, AI systems do impressive things. AI systems combine algorithms and data to do things we have traditionally expected only of humans, such as predicting outcomes, classifying complex information, optimising processes or generating content. Many of the largest large language models are also remarkably flexible, able to do many of these tasks through the same interface.

Second, AI systems tend not to be explicitly programmed. Neural networks in particular work by learning from data, often finding patterns and relationships that would be impossible for a human being to discern. They are therefore deeply influenced by the data on which they are trained, which can result in errors and biased outputs.

Third, AI systems tend to be unpredictable and opaque. They produce different outputs depending on how they have been trained and the input they are given. It takes special effort to understand how and why they come to a particular conclusion or decision.

All of this means that AI systems are more than just another IT application for your business. They offer huge promise, but also require special attention to manage safely and responsibly.

This video series is designed to give you a crash course in human-centred AI. In the videos that follow, we will cover why AI is so transformative, why governance matters and how you can ensure that AI is used responsibly in your business.

To realise the benefits of AI, we need to take steps to ensure it is responsible and fit-for-purpose. That’s why it’s essential that they draw on the principles and philosophy of human-centred design, which is a methodology that places people at its core. It's about designing objects, processes and systems in a way that responds to a deep understanding of human desires, contexts, capabilities and needs.

Managing the risks of AI 

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Transcript

What is AI? Artificial intelligence is core to how businesses operate today. It's the technology powering your phone, targeting your customers on social media, and helping you recruit. Whether you know it or not, your organisation relies on multiple AI systems every day. They might employ AI to help them be more efficient or to improve how they engage with customers.

The Human Technology Institute's research reveals that almost every Australian business relies on multiple AI systems today. You may only be aware of a fraction of the AI applications that your employees use at work, often without any official sign-off from management or IT. Some of these AI systems are valuable and low-risk, for example, AI-powered navigation systems. But others can introduce a range of risks and challenges, from cyber security concerns to the threat of physical harm.

As AI becomes an essential part of doing business, every business leader needs to cultivate what we call a minimum viable understanding around AI. And this starts with understanding how AI systems work and why managing them carefully is critical to your organisation's success.

AI is challenging to define, partly because our understanding of AI changes over time. When the field of AI began in the 1950s, AI systems tried to mimic how humans made decisions. These became known as expert systems. Thanks to massive increases in data and computing power, the last decade has seen the rise of machine learning. This is where digital systems apply algorithms to large historical data sets to learn deep patterns. This allows them to make predictions when applied to new situations.

Most recently, generative AI has changed the way we think about the possibilities of AI systems. Applications like ChatGPT and DALL·E rely on models trained on huge amounts of data to produce fluent text, novel images and even video from simple text prompts.

It's critical to remember that all AI systems are based on maths, not magic. Machine learning is underpinned by statistics, linear algebra, probability theory and calculus. While impressive AI systems are powered by complex algorithms and vast amounts of computing power, these systems do not possess common sense, interpersonal skills or a true understanding of the world. They can and do fail in many different ways.

As a business leader, you can think of AI as being a very broad collective term for digital computer systems that have three characteristics.

First, AI systems do impressive things. AI systems combine algorithms and data to do things we have traditionally expected only of humans, such as predicting outcomes, classifying complex information, optimising processes or generating content. Many of the largest large language models are also remarkably flexible, able to do many of these tasks through the same interface.

Second, AI systems tend not to be explicitly programmed. Neural networks in particular work by learning from data, often finding patterns and relationships that would be impossible for a human being to discern. They are therefore deeply influenced by the data on which they are trained, which can result in errors and biased outputs.

Third, AI systems tend to be unpredictable and opaque. They produce different outputs depending on how they have been trained and the input they are given. It takes special effort to understand how and why they come to a particular conclusion or decision.

All of this means that AI systems are more than just another IT application for your business. They offer huge promise, but also require special attention to manage safely and responsibly.

This video series is designed to give you a crash course in human-centred AI. In the videos that follow, we will cover why AI is so transformative, why governance matters and how you can ensure that AI is used responsibly in your business.

The same technological features that make AI systems so powerful also make them less predictable, and more difficult to understand. This introduces new commercial, reputational and regulatory risks for organisations using AI, and result in significant harms to their stakeholders.. To ensure that these risks don’t happen for your business, use a human centred-approach by identifying effective prevention and mitigation strategies on harms, and linking these to risks that may arise later.

Addressing AI system harms

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Transcript

What is AI? Artificial intelligence is core to how businesses operate today. It's the technology powering your phone, targeting your customers on social media, and helping you recruit. Whether you know it or not, your organisation relies on multiple AI systems every day. They might employ AI to help them be more efficient or to improve how they engage with customers.

The Human Technology Institute's research reveals that almost every Australian business relies on multiple AI systems today. You may only be aware of a fraction of the AI applications that your employees use at work, often without any official sign-off from management or IT. Some of these AI systems are valuable and low-risk, for example, AI-powered navigation systems. But others can introduce a range of risks and challenges, from cyber security concerns to the threat of physical harm.

As AI becomes an essential part of doing business, every business leader needs to cultivate what we call a minimum viable understanding around AI. And this starts with understanding how AI systems work and why managing them carefully is critical to your organisation's success.

AI is challenging to define, partly because our understanding of AI changes over time. When the field of AI began in the 1950s, AI systems tried to mimic how humans made decisions. These became known as expert systems.

Thanks to massive increases in data and computing power, the last decade has seen the rise of machine learning. This is where digital systems apply algorithms to large historical data sets to learn deep patterns. This allows them to make predictions when applied to new situations.

Most recently, generative AI has changed the way we think about the possibilities of AI systems. Applications like ChatGPT and DALL-E rely on models trained on huge amounts of data to produce fluent text, novel images and even video from simple text prompts.

It's critical to remember that all AI systems are based on maths, not magic. Machine learning is underpinned by statistics, linear algebra, probability theory and calculus. While impressive AI systems are powered by complex algorithms and vast amounts of computing power, these systems do not possess common sense, interpersonal skills or a true understanding of the world. They can and do fail in many different ways.

As a business leader, you can think of AI as being a very broad collective term for digital computer systems that have three characteristics.

First, AI systems do impressive things. AI systems combine algorithms and data to do things we have traditionally expected only of humans, such as predicting outcomes, classifying complex information, optimising processes or generating content. Many of the largest large language models are also remarkably flexible, able to do many of these tasks through the same interface.

Second, AI systems tend not to be explicitly programmed. Neural networks in particular work by learning from data, often finding patterns and relationships that would be impossible for a human being to discern. They are therefore deeply influenced by the data on which they are trained, which can result in errors and biased outputs.

Third, AI systems tend to be unpredictable and opaque. They produce different outputs depending on how they have been trained and the input they are given. It takes special effort to understand how and why they come to a particular conclusion or decision.

All of this means that AI systems are more than just another IT application for your business. They offer huge promise, but also require special attention to manage safely and responsibly.

This video series is designed to give you a crash course in human-centred AI. In the videos that follow, we will cover why AI is so transformative, why governance matters and how you can ensure that AI is used responsibly in your business.

One way to identify potential harms is to conduct an “impact assessment.” To avoid the harms you’ve identified – and thereby manage the related risks to your business – you need to put in place appropriate controls.

Obligations and responsibilities of AI deployers

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Transcript

What is AI? Artificial intelligence is core to how businesses operate today. It's the technology powering your phone, targeting your customers on social media and helping you recruit. Whether you know it or not, your organisation relies on multiple AI systems every day. They might employ AI to help them be more efficient or to improve how they engage with customers.

The Human Technology Institute's research reveals that almost every Australian business relies on multiple AI systems today. You may only be aware of a fraction of the AI applications that your employees use at work, often without any official sign-off from management or IT. Some of these AI systems are valuable and low-risk, for example, AI-powered navigation systems. But others can introduce a range of risks and challenges, from cyber security concerns to the threat of physical harm.

As AI becomes an essential part of doing business, every business leader needs to cultivate what we call a minimum viable understanding around AI. And this starts with understanding how AI systems work and why managing them carefully is critical to your organisation's success.

AI is challenging to define, partly because our understanding of AI changes over time. When the field of AI began in the 1950s, AI systems tried to mimic how humans made decisions. These became known as expert systems. Thanks to massive increases in data and computing power, the last decade has seen the rise of machine learning. This is where digital systems apply algorithms to large historical data sets to learn deep patterns. This allows them to make predictions when applied to new situations.

Most recently, generative AI has changed the way we think about the possibilities of AI systems. Applications like ChatGPT and DALL·E rely on models trained on huge amounts of data to produce fluent text, novel images and even video from simple text prompts.

It's critical to remember that all AI systems are based on maths, not magic. Machine learning is underpinned by statistics, linear algebra, probability theory and calculus. While impressive AI systems are powered by complex algorithms and vast amounts of computing power, these systems do not possess common sense, interpersonal skills or a true understanding of the world. They can and do fail in many different ways.

As a business leader, you can think of AI as being a very broad collective term for digital computer systems that have three characteristics.

First, AI systems do impressive things. AI systems combine algorithms and data to do things we have traditionally expected only of humans, such as predicting outcomes, classifying complex information, optimising processes or generating content. Many of the largest large language models are also remarkably flexible, able to do many of these tasks through the same interface.

Second, AI systems tend not to be explicitly programmed. Neural networks in particular work by learning from data, often finding patterns and relationships that would be impossible for a human being to discern. They are therefore deeply influenced by the data on which they are trained, which can result in errors and biased outputs.

Third, AI systems tend to be unpredictable and opaque. They produce different outputs depending on how they have been trained and the input they are given. It takes special effort to understand how and why they come to a particular conclusion or decision.

All of this means that AI systems are more than just another IT application for your business. They offer huge promise, but also require special attention to manage safely and responsibly.

This video series is designed to give you a crash course in human-centred AI. In the videos that follow, we will cover why AI is so transformative, why governance matters and how you can ensure that AI is used responsibly in your business.

If you are involved in procuring or implementing AI systems, you need to understand what AI systems are operating in your organisation and how they create value, as well as your ethical, legal and regulatory obligations under Australian and international law.

Procuring AI

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Transcript

What is AI? Artificial intelligence is core to how businesses operate today. It's the technology powering your phone, targeting your customers on social media and helping you recruit. Whether you know it or not, your organisation relies on multiple AI systems every day. They might employ AI to help them be more efficient or to improve how they engage with customers. The Human Technology Institute's research reveals that almost every Australian business relies on multiple AI systems today.

You may only be aware of a fraction of the AI applications that your employees use at work, often without any official sign-off from management or IT. Some of these AI systems are valuable and low-risk. For example, AI-powered navigation systems. But others can introduce a range of risks and challenges, from cyber security concerns to the threat of physical harm.

As AI becomes an essential part of doing business, every business leader needs to cultivate what we call a minimum viable understanding around AI. And this starts with understanding how AI systems work and why managing them carefully is critical to your organisation's success.

AI is challenging to define, partly because our understanding of AI changes over time. When the field of AI began in the 1950s, AI systems tried to mimic how humans made decisions. These became known as expert systems. Thanks to massive increases in data and computing power, the last decade has seen the rise of machine learning. This is where digital systems apply algorithms to large historical data sets to learn deep patterns. This allows them to make predictions when applied to new situations.

Most recently, generative AI has changed the way we think about the possibilities of AI systems. Applications like ChatGPT and DALL·E rely on models trained on huge amounts of data to produce fluent text, novel images and even video from simple text prompts.

It's critical to remember that all AI systems are based on maths, not magic. Machine learning is underpinned by statistics, linear algebra, probability theory and calculus. While impressive AI systems are powered by complex algorithms and vast amounts of computing power, these systems do not possess common sense, interpersonal skills or a true understanding of the world. They can and do fail in many different ways.

As a business leader, you can think of AI as being a very broad collective term for digital computer systems that have three characteristics. First, AI systems do impressive things. AI systems combine algorithms and data to do things we have traditionally expected only of humans, such as predicting outcomes, classifying complex information, optimising processes or generating content. Many of the largest large language models are also remarkably flexible, able to do many of these tasks through the same interface.

Second, AI systems tend not to be explicitly programmed. Neural networks in particular work by learning from data, often finding patterns and relationships that would be impossible for a human being to discern. They are therefore deeply influenced by the data on which they are trained, which can result in errors and biased outputs.

Third, AI systems tend to be unpredictable and opaque. They produce different outputs depending on how they have been trained and the input they are given. It takes special effort to understand how and why they come to a particular conclusion or decision.

All of this means that AI systems are more than just another IT application for your business. They offer huge promise, but also require special attention to manage safely and responsibly.

This video series is designed to give you a crash course in human-centred AI. In the videos that follow, we will cover why AI is so transformative, why governance matters and how you can ensure that AI is used responsibly in your business.

With more organisations opting to buy, rather than build their own AI systems and given the nature of AI systems, new procurement strategies are required. What do executives need to know to plan, source and manage procurement of AI systems in today’s evolving technology landscape?

What does good governance of AI systems look like?

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Transcript

What is AI? Artificial intelligence is core to how businesses operate today. It's the technology powering your phone, targeting your customers on social media and helping you recruit. Whether you know it or not, your organisation relies on multiple AI systems every day. They might employ AI to help them be more efficient or to improve how they engage with customers.

The Human Technology Institute's research reveals that almost every Australian business relies on multiple AI systems today. You may only be aware of a fraction of the AI applications that your employees use at work, often without any official sign-off from management or IT. Some of these AI systems are valuable and low-risk. For example, AI-powered navigation systems. But others can introduce a range of risks and challenges, from cyber security concerns to the threat of physical harm.

As AI becomes an essential part of doing business, every business leader needs to cultivate what we call a minimum viable understanding around AI. And this starts with understanding how AI systems work and why managing them carefully is critical to your organisation's success.

AI is challenging to define, partly because our understanding of AI changes over time. When the field of AI began in the 1950s, AI systems tried to mimic how humans made decisions. These became known as expert systems. Thanks to massive increases in data and computing power, the last decade has seen the rise of machine learning. This is where digital systems apply algorithms to large historical data sets to learn deep patterns. This allows them to make predictions when applied to new situations.

Most recently, generative AI has changed the way we think about the possibilities of AI systems. Applications like ChatGPT and DALL-E rely on models trained on huge amounts of data to produce fluent text, novel images and even video from simple text prompts.

It's critical to remember that all AI systems are based on maths, not magic. Machine learning is underpinned by statistics, linear algebra, probability theory and calculus. While impressive AI systems are powered by complex algorithms and vast amounts of computing power, these systems do not possess common sense, interpersonal skills or a true understanding of the world. They can and do fail in many different ways.

As a business leader, you can think of AI as being a very broad collective term for digital computer systems that have three characteristics.

First, AI systems do impressive things. AI systems combine algorithms and data to do things we have traditionally expected only of humans, such as predicting outcomes, classifying complex information, optimising processes or generating content. Many of the largest large language models are also remarkably flexible, able to do many of these tasks through the same interface.

Second, AI systems tend not to be explicitly programmed. Neural networks in particular work by learning from data, often finding patterns and relationships that would be impossible for a human being to discern. They are therefore deeply influenced by the data on which they are trained, which can result in errors and biased outputs.

Third, AI systems tend to be unpredictable and opaque. They produce different outputs depending on how they have been trained and the input they are given. It takes special effort to understand how and why they come to a particular conclusion or decision.

All of this means that AI systems are more than just another IT application for your business. They offer huge promise, but also require special attention to manage safely and responsibly.

This video series is designed to give you a crash course in human-centred AI. In the videos that follow, we will cover why AI is so transformative, why governance matters and how you can ensure that AI is used responsibly in your business.

Governance is the set of rules, systems and structures that help organisations make good decisions and maintain accountability to their stakeholders. Given that AI systems can offer both huge benefits and potential risks to your business, AI governance should be a key topic for your board and a priority for you and your executive leadership team. This video describes how to apply best practice principles of AI governance in your business.

Why are trustworthy AI systems important?

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Transcript

What is AI? Artificial intelligence is core to how businesses operate today. It's the technology powering your phone, targeting your customers on social media and helping you recruit. Whether you know it or not, your organisation relies on multiple AI systems every day. They might employ AI to help them be more efficient or to improve how they engage with customers.

The Human Technology Institute's research reveals that almost every Australian business relies on multiple AI systems today. You may only be aware of a fraction of the AI applications that your employees use at work, often without any official sign-off from management or IT.

Some of these AI systems are valuable and low-risk. For example, AI-powered navigation systems. But others can introduce a range of risks and challenges, from cyber security concerns to the threat of physical harm.

As AI becomes an essential part of doing business, every business leader needs to cultivate what we call a minimum viable understanding around AI. And this starts with understanding how AI systems work and why managing them carefully is critical to your organisation's success.

AI is challenging to define, partly because our understanding of AI changes over time. When the field of AI began in the 1950s, AI systems tried to mimic how humans made decisions. These became known as expert systems.

Thanks to massive increases in data and computing power, the last decade has seen the rise of machine learning. This is where digital systems apply algorithms to large historical data sets to learn deep patterns. This allows them to make predictions when applied to new situations.

Most recently, generative AI has changed the way we think about the possibilities of AI systems. Applications like ChatGPT and DALL·E rely on models trained on huge amounts of data to produce fluent text, novel images and even video from simple text prompts.

It's critical to remember that all AI systems are based on maths, not magic. Machine learning is underpinned by statistics, linear algebra, probability theory and calculus.

While impressive AI systems are powered by complex algorithms and vast amounts of computing power, these systems do not possess common sense, interpersonal skills or a true understanding of the world. They can and do fail in many different ways.

As a business leader, you can think of AI as being a very broad collective term for digital computer systems that have three characteristics.

First, AI systems do impressive things. AI systems combine algorithms and data to do things we have traditionally expected only of humans, such as predicting outcomes, classifying complex information, optimising processes or generating content. Many of the largest large language models are also remarkably flexible, able to do many of these tasks through the same interface.

Second, AI systems tend not to be explicitly programmed. Neural networks in particular work by learning from data, often finding patterns and relationships that would be impossible for a human being to discern. They are therefore deeply influenced by the data on which they are trained, which can result in errors and biased outputs.

Third, AI systems tend to be unpredictable and opaque. They produce different outputs depending on how they have been trained and the input they are given. It takes special effort to understand how and why they come to a particular conclusion or decision.

All of this means that AI systems are more than just another IT application for your business. They offer huge promise, but also require special attention to manage safely and responsibly.

This video series is designed to give you a crash course in human-centred AI. In the videos that follow, we will cover why AI is so transformative, why governance matters and how you can ensure that AI is used responsibly in your business.

As an AI becomes increasingly important to how your organisation operates, if you want your customers to trust your business, they'll need to trust how and when you use AI. Key characteristics of trustworthy AI systems are that they're reliable, safe, secure and resilient, accountable and transparent, explainable and interpretable, privacy enhanced and air.