The initiative empowers both educators and young people by offering a comprehensive suite of resources for teachers and an exciting AI-themed challenge that makes AI and machine learning accessible to learners aged up to 18.
The eight lessons
What is AI?: Learners delve into the current landscape of artificial intelligence and its role in our world. They explore the differences between rule-based and data-driven programming approaches and consider the societal benefits and challenges associated with AI.
How computers learn: This lesson introduces learners to machine learning, with a focus on the various approaches used to create machine learning models. The concept of classification, a specific application of machine learning, is explored in detail.
Bias in, bias out: Learners create their own machine learning model to classify images, and uncover the impact of limited datasets and bias in machine learning.
Decision trees: An in-depth look at decision trees as a specific machine learning model. Learners experience firsthand the concept of data-driven models and how different training datasets result in diverse ML models.
Solving problems with ML models: Learners are introduced to the AI project lifecycle. They take a human-focused approach to create and train a machine learning model, followed by rigorous testing to determine its accuracy.
Model cards and careers: Learners create model cards to explain their machine learning models. Additionally, students explore a variety of AI-related career paths and gain insights from professionals in AI research, including DeepMind.
Large language models (LLMs) – PSHE: This lesson is a sequence of activities designed to educate students about the development of large language models (LLMs). The activities will give students the opportunity to explore the purpose and functionality of LLMs, while also examining the critical aspect of trustworthiness in their output.
Ecosystems – Biology: In this lesson, your students will explore the impact of environmental changes on the organisms in an ecosystem, in this case the Serengeti National Park in Tanzania. They will consider the problems of measuring biodiversity in order to maintain it, and have a go at the task in question themselves. They will learn about artificial intelligence (AI) and consider the benefits that AI applications are bringing to conservation in the Serengeti. There is scope for a wider look at societal attitudes to AI, alongside a realistic analysis of the potential benefits and drawbacks AI might bring to society. The lesson concludes with students discovering uses of AI in science as well as looking at careers in AI.
Experience AI Challenge
The Experience AI team also runs the Experience AI Challenge, a programme where young people are encouraged to design and build their own AI applications.
Key information
- Starts on 08 January 2024
- Free to take part
- Designed for beginners, based on the tools Scratch and Machine Learning for Kids
- Official submissions can be made by UK-based young people aged up to 18
- Young people and their mentors outside the UK are welcome to use the challenge resources and make AI projects
- Tailored resources for young people and mentors to support them to take part
- Teachers can currently register their interest and they’ll be sent a reminder email on the launch day
Make an AI project
For the Experience AI Challenge, young people will learn how to make a machine learning (ML) classifier that organises data — such as audio, text, or images — into different groupings that they choose. Then they will use their new skills to create a project of their own. Examples of projects they could make include:
- An instrument classifier to identify the type of musical instrument being played in pieces of music
- A sentiment analyzer for book reviews: Classify the text in book reviews as positive, negative, or neutral
- A photo classifier to identify what kind of food is shown in a photograph
The Experience AI Challenge is organised into three stages:
Explore and discover: This stage aims to spark curiosity and provide an introduction to AI and ML. Participants explore how these technologies are reshaping industries such as healthcare and entertainment.
Get hands-on: In the second stage, young creators choose a data type and embark on a guided project. They learn to create a training dataset, train an ML model, and develop a Scratch application as a user interface for their model.
Design and create: In the final stage, participants apply their knowledge to create their own ML projects, addressing problems they are passionate about. Projects are submitted online, and expert feedback is provided.
Getting ready for the challenge!
To participate in the Experience AI Challenge, educators can register their interest and receive a reminder email on the launch day. In the meantime, why not encourage the young creators you work with to brainstorm ideas for their AI projects?
Experience AI is not only bridging the knowledge gap by offering educators comprehensive resources for teaching AI, but also providing young creators with the tools and guidance they need to become active participants in the world of artificial intelligence. As AI continues to shape our future, Experience AI is empowering the next generation to understand, innovate, and create with this transformative technology.
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