What am I learning?

This two-week course offers you an introductory overview of the use of creative AI within the creative industries.

There are many creative tasks that either take too long to manually code, or would be impossible without the intervention of technology. Creative AI, that is the use of computer algorithms to perform tasks in the world of creative arts, has changed that.

From creating amazing synths controlled by gesture, to seeing the ‘thoughts’ of computers, this course will explore how specific types of AI and machine learning are changing the creative industries, both in terms of how we consume creative work, and also how we make it.

Each week of this course is centred around learning outcomes: statements which express what it is you will be better able to do by the end of the course.

Week 1 covers the following learning outcomes:

• Describe how the creative industries are using AI and machine learning at a basic level.
• Compare different types of machine learning and AI approaches that are used in the creative industries.
• Debate the potential of AI to create new media.

Week 2 covers the following learning outcomes:

• Summarise deep learning and its application to creative industries.
• Explain how AI systems are developed.
• Identify the skills required to work in creative AI.

You can revisit steps as you progress through the course so that you feel confident you’re meeting the learning outcomes. As you are working through the steps and activities, you might want to refer back to this step to check your progress.

Accessing this course

You can access this course using a variety of devices, including smartphones, tablets, and laptop or desktop computers. However, in the second week you will need a computer to access some of the more practical content of the course fully using the Wekinator tool. You can find further detail on using the tool in the Downloads section.

What is AI?

But what exactly is AI, and how does it differ from machine learning? You will see the terms AI and machine learning used interchangeably in many places. Although they are related to each other, they are not the same thing.

The Encyclopedia Britannica describes AI as “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.” It then describes machine learning as a “discipline concerned with the implementation of computer software that can learn autonomously.’’

A simple way to distinguish between the two is to think of AI as the possible result of machine learning. A system might work in such a way that it would appear intelligent to a person using it. This would be an example of AI. The actual code that makes the system appear intelligent may be a machine learning algorithm. Machine learning describes the ability for a specific piece of software to become more efficient by analysing data.

This course will give you an insight into the types of AI and machine learning that are being used creatively, and what these techniques are being used to create.

We will look at some specific examples of work and hear from the artists themselves as they describe their practice.

Together we’ll discuss the position of creative AI, the potential of its techniques, and think about how it might affect our future relationship with creative media.

Mick Grierson

Mick will be your Lead Educator and will guide you through the course. He is Research Leader at the UCL Creative Computing Institute, and will be your lead educator on this course. His research explores new approaches to the creation of sounds, images, video and interactions through signal processing, machine learning and information retrieval techniques. As well as his academic role, Mick is also an audiovisual artist and creative coder.

You can find out more about Mick from his FutureLearn profile, and choose to ‘Follow’ him to keep up to date with his responses and advice on the course.

Learning together

For the next two weeks, you won’t be learning on your own. You’ll be studying alongside many learners from around the world.

Use the Comments sections and Discussion steps throughout the course to ask your fellow learners questions and share problems you are stuck on. Developing a collaborative learning environment will lead to a successful and enjoyable course. You can read more about how to get the most from this course in the notes in the See also section.