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AI in Everyday Life
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AI in Everyday Life
Open with the idea that many students already use AI without always noticing it. This helps connect the lesson to familiar experiences before moving into definitions and mechanisms.
Learning goal
I can explain what AI is, describe key advantages and disadvantages in everyday life, and explain simply how ChatGPT produces answers and why AI can have a significant environmental impact.
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What comes to mind when you hear AI in everyday life?
Use this as a prior-knowledge activation. Expect words such as phones, ChatGPT, robots, recommendations, speed, privacy, or homework. Briefly connect student ideas to the lesson goals.
What is AI?
Artificial intelligence (AI) is technology that carries out tasks that normally need human thinking
It can recognise patterns, sort information, make predictions, or respond to language
AI does not think like a person, even when it seems intelligent
Keep the definition broad and practical. Students do not need advanced technical categories; they need a clear idea that AI imitates parts of human decision-making or language use.
AI and generative AI
Not all AI does the same job.
Some AI systems classify or recommend
Some AI systems detect patterns in images, sound, or text
Generative AI creates new content, such as text, images, music, or code
ChatGPT is an example of generative AI because it produces new text
Stress the difference between selecting from existing options and generating new output. That contrast prepares students for the later explanation of ChatGPT.
AI in daily life
Film and music recommendations
Suggested products in online shops
Spam filters in email
Face recognition on phones
These examples help students see that AI is already built into ordinary digital services, not only special robots or chatbots.
Everyday examples
Helping users
Chatbots reply in written language
They are used by banks, shops, schools, and travel companies
Many combine stored information with AI-generated replies
Talking systems
Navigation apps predict the fastest route
Translation tools convert text between languages
Customer service systems answer common questions
If useful, point out that one app can use several types of AI at the same time, such as prediction, language processing, and recommendation.
Why people use AI
It can save time on routine tasks
It often gives results very quickly
It can process large amounts of information
It makes digital services feel more personal or convenient
This slide closes the first content block by linking the definition of AI to the reason it spreads so quickly in everyday life.
What makes generative AI different from some other AI systems?
It creates new content
It stores phone contacts
It only follows routes
It blocks spam emails
Checks the contrast between AI that classifies or recommends and AI that generates text, images, music, or code.
AI in daily life
AI is technology that carries out tasks that normally need human thinking. In everyday life, it can give recommendations, predict routes in navigation apps, and answer questions through chatbots.
The blanks focus on key examples from slides 4 to 6: recommendation systems, navigation, and chatbots.
Advantages of AI
Convenience: tasks can be done with fewer steps
Speed: AI can respond in seconds
Accuracy: some systems reduce human error in repeated tasks
AI can be available at any time of day
Accuracy should be presented carefully: AI can be accurate in narrow, repeated tasks, but this does not mean it is always correct.
Benefits in real situations
Navigation apps can avoid traffic and save fuel
Translation tools can support travel, work, and study
Customer service bots can answer simple questions at busy times
Recommendation systems can help users find content faster
Keep the examples concrete so students connect abstract advantages to situations they know.
Disadvantages of AI
Privacy: systems may collect large amounts of personal data
Bias: results can be unfair if the training data is unbalanced
Dependency: people may rely on AI too much
Bias often needs a short spoken example, such as a system performing better for one group than another because of uneven training data.
Wider concerns
Some jobs may change or disappear when tasks are automated
AI can produce convincing mistakes very quickly
Users may trust answers without checking the source
Avoid saying that all jobs will disappear. A better framing is that AI changes work by automating certain tasks and creating pressure on some roles.
AI: gains and trade-offs
What must be watched
Faster responses
Easier access to services
Support with routine work
What AI improves
Personal data use
Unfair or inaccurate output
Over-reliance and job pressure
This comparison slide helps students hold both sides together instead of seeing AI as only good or only bad.
Which is a disadvantage of AI mentioned in this lesson?
Faster replies
Personalisation
Bias in results
Routine support
Distractors come from the advantages slides. The correct answer checks whether students can separate benefits from risks.
Which AI risk worries you most in daily life?
Privacy
Bias
Dependency
Job pressure
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When is AI helpful, but still risky?
Expected elements: AI can save time or improve access, but students should mention one trade-off such as privacy, bias, over-reliance, or job pressure. Invite short, concrete examples from daily life.
What happens in ChatGPT? Ask ai!
Ask ChatGPT these questions one by one:
What happens after I type a question to you?
How do you decide what answer to give me?
Does this mean your answer is always correct?
Students often assume ChatGPT 'knows' facts in a human way or always looks things up live. Clarify that the key idea here is trained pattern use.
What does this tell you about how ai works?
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Training on large amounts of text
ChatGPT is trained on very large amounts of text
During training, it learns patterns in grammar, meaning, and word order
It becomes good at predicting what text is likely to come next
This is pattern recognition on a huge scale
You can compare training to seeing many examples of language rather than memorising one fixed answer sheet.
How does ChatGPT mainly produce an answer?
By live web searching
By copying one text
By asking a person
By predicting words
The main idea is next-word prediction based on patterns learned during training, not human understanding or guaranteed live searching.
How ChatGPT works
When a user types a prompt, ChatGPT uses patterns learned during training. It predicts the next likely word and builds the answer step by step. The reply is generated, not human-style understanding.
This exercise mirrors the wording of slides 12 to 15 and reinforces the mechanism clearly.
Why AI uses so much energy
AI runs on powerful computers in data centres
These machines use large amounts of electricity
They also create heat, so cooling systems are needed
Link this slide back to ChatGPT: generating answers may feel simple for the user, but the computing work happens elsewhere in large server systems.
Data centres, cooling, emissions
Electricity use in data centres does not only power the AI model. It also powers storage, networking, and cooling. If that electricity comes from fossil fuels, the energy use is linked to carbon emissions.
Students may not immediately connect digital actions to physical infrastructure. Make the hidden physical system visible here.
A simple comparison
AI queries
Sending a short message
Opening a simple web page
Playing a saved song
Complex language processing
Powerful servers working in real time
Often higher energy use per task
Everyday digital activities
This comparison should stay qualitative: everyday digital tasks are often lighter, while AI queries can trigger heavier processing behind the scenes.
Why can AI be linked to carbon emissions?
It uses paper files
It needs fossil electricity
It deletes old apps
It prints long answers
Students should connect data centres, electricity use, cooling, and fossil-fuel energy to carbon emissions.
AI and energy use
AI runs on powerful computers in data centres. These systems use electricity and also need cooling because they create heat. If the energy comes from fossil fuels, it is linked to carbon emissions.
Checks the physical infrastructure behind AI, which is often hidden from students.
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What is one thing you learned today about AI?
Reflection only. Invite students to name one clear idea from the lesson, such as a definition, an example, a risk, how ChatGPT predicts words, or why AI uses energy.
Glossary
artificial intelligence - technology that carries out tasks that normally need human thinking
generative AI - AI that creates new content such as text or images
recommendation system - a system that suggests films, music, products, or other content
chatbot - a program that communicates with users in written or spoken language
prompt - the text or instruction a user gives to an AI system
pattern recognition - finding repeated structures or relationships in data
training data - large amounts of information used to train an AI model
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Glossary
prediction - selecting the most likely next result based on patterns
data centre - a building with many computers that store and process digital information
cooling - systems that remove heat from computers and servers
carbon emissions - gases released into the air, often through energy use from fossil fuels
bias - unfair patterns in results that affect some people more than others
privacy - control over personal information and how it is used
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