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Learn it your way
A short class with Sarah and her students. The other ways are under More.
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Today, we will discuss how we can use AI to solve real-world problems. Can anyone tell me what they think an AI project might involve?
I think it could be about building models that recognize things, like faces or sounds.
Yes, or even categorizing information based on AI predictions!
Exactly! Projects can range from simple models to complex systems that address challenges like pollution. Let's dive into a specific example, shall we?
One of the projects is to create an AI model. Has anyone heard of Teachable Machine by Google?
I think I've used it for some fun experiments, but what exactly can it do?
Great question! Teachable Machine allows you to train a model with images, sounds, or poses. Let's remember it with the acronym T-MAP — Teachable Machine Activates Projects.
That's a handy memory aid! What data types can we use?
You can use images, sounds, or text. Each type offers a different learning experience. It helps us understand datasets and how machines learn. Who can recall the steps to create a model?
First, we choose the data type, then collect our samples, train the model and finally test it!
Perfect! Let's keep that process clear with the mnemonic C-T-T-P — Collect, Train, Test, Present.
Now, let's pivot to our second project about solving problems tied to Sustainable Development Goals, or SDGs. Can anyone list a few problems we could tackle?
Pollution is a big one! We see it everywhere.
What about water wastage? That’s a big issue too!
Excellent! Let's remember these problems with the acronym P-W-E-T — Pollution, Water wastage, Energy consumption, Traffic congestion. What steps should we take to address a chosen issue?
We need to identify who is affected, what the problem is, where it's happening, and why it matters!
Yes! This is part of creating a 4Ws canvas. Understanding these elements is crucial for finding effective AI solutions.
Once we've identified the problem, we need to collect data. What tools do you think we can use for data visualization?
Excel is a great tool for that!
What about Google Sheets? It's easy and online!
Exactly! Both are excellent for recording and visualizing data. Let’s summarize this step with the acronym D-R-V — Data Record, Visualize.
This helps to see patterns, right?
Absolutely! Finding patterns is crucial to understanding our AI-enabled solution.
Finally, after building your solution, it’s time to present your findings. Why do you think sharing our projects is important?
It helps us communicate our ideas clearly to others!
And we can get feedback to improve on our projects.
Exactly! Presentation is key in communicating solutions and learning experiences effectively. To emphasize, let’s remember P-C (Present and Communicate).
I can’t wait to share what we’ve learned through these projects!
A system that mimics human intelligence for learning from data.
A global agenda for solving pressing world problems.
A methodological approach to dissecting problems.
A technique to present data clearly and understandably.
To learn from AI's might, just train it just right!
Once there was a young coder who built AI models to solve the problems of their town, turning ideas into reality through learning and creativity.
Remember C-T-T-P for creating a model: Collect, Train, Test, Present.
P-W-E-T: Pollution, Water wastage, Energy consumption, Traffic congestion for SDG-related projects.
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AI Model
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Sustainable Development Goals (SDGs)
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Data Visualization
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Teachable Machine
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A computational model that simulates human intelligence processes such as learning, reasoning, and self-correction.
A set of 17 global goals established by the United Nations to address various global challenges including poverty, inequality, climate change, environmental degradation, and peace and justice.
A framework that helps analyze a problem by answering the questions 'Who', 'What', 'Where', and 'Why'.
The graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.
This section presents project ideas that leverage artificial intelligence to solve real-world problems, encouraging students to apply their knowledge of AI in practical scenarios.
In this section, students are introduced to various project ideas that involve building AI models and finding solutions to problems related to Sustainable Development Goals (SDGs). The projects foster creativity, critical thinking, and the application of AI tools, helping students to understand both technology and sustainability.
In this part of Chapter 22, students are encouraged to explore application-based projects related to Artificial Intelligence (AI). The two primary projects outlined are focused on creating an AI model and solving real-world issues linked to Sustainable Development Goals (SDGs). The projects not only serve to apply theoretical knowledge but also emphasize creativity, critical thinking, and problem-solving. The suggested tools include Teachable Machine by Google and Machine Learning for Kids, both designed for ease of use in building AI models. The projects culminate in the creation of solutions that address pressing global challenges, such as pollution and resource wastage. Furthermore, students are encouraged to document their learning journey in a portfolio that reflects their experiences and insights into the role of AI in society.