AI Applications and Their Impact
FoundationArtificial intelligence mimics human intelligence — recognising images, hearing speech, translating and generating content. It eases life and aids medicine, yet can err, carry bias and be misused. Use AI by verifying content, protecting privacy and crediting help honestly, with critical thinking — AI is a tool; judgement stays human.
- AI mimics human learning, recognition and generation, with machine learning finding patterns in vast data.
- Applications span daily life and industries: voice assistants, face recognition, medical aid, farm drones and learning apps.
- AI errs and carries bias, and deepfakes can pass as real — never trust blindly.
文體小知識：科技評介文章介紹新科技的原理和應用，同時分析利弊，教人以批判眼光看待科技。
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1Artificial intelligence (AI) is technology that mimics human intelligence: learning, reasoning, recognising and generating. Machine learning is its core method — computers find patterns in huge data, such as learning to tell cats from dogs after millions of labelled photos. Applications surround us: a phone's voice assistant hears 'what is tomorrow's weather' and answers; face recognition unlocks the phone; translation apps convert languages instantly; map apps suggest the fastest route from live traffic; video platforms recommend shows by viewing habits.
2Every industry is adopting AI. In medicine, AI scans vast numbers of X-rays and lab results, flagging possible lesions within seconds for doctors to review, reducing oversights. In transport, systems forecast congestion and self-driving technology is on trial. In farming, drones monitor fields and spot pests and disease. In education, learning apps adjust question difficulty to each student's pace. In the arts, AI generates images, scores and text as a creative assistant.
3Yet AI has clear limits and risks. First, it errs — mistaking objects or fabricating facts in a confident tone. Second, it carries bias: if training data lacks certain groups or is inaccurate, its judgments turn unfair or wrong. Third, AI-generated content can pass as real — deepfakes swap faces into false videos and invent 'news' that is hard to distinguish. Fourth, over-reliance dulls our own thinking and writing. Besides, training AI demands huge data collection, so privacy risks deserve attention.
4Responsible use of AI follows a few principles. Verify content — check AI answers against books or official sites, especially names, dates and figures. Protect privacy — never type your address or passwords into AI. Credit honestly — tell your teacher which parts of homework AI helped with; never present AI content as your own work. Respect copyright — the rules on using AI-generated images and text are still developing. Remember: AI generates fast, but judgment and responsibility belong to people — use it to assist learning, not to replace it.
1Summary 重點摘要
Artificial intelligence mimics human intelligence — recognising images, hearing speech, translating and generating content. It eases life and aids medicine, yet can err, carry bias and be misused. Use AI by verifying content, protecting privacy and crediting help honestly, with critical thinking — AI is a tool; judgement stays human.
2Vocabulary cards Vocabulary
Computer technology imitating human learning, reasoning, recognition and generation.
The method by which computers find patterns in vast data and improve themselves.
A program that hears spoken commands and answers, such as a phone assistant.
Technology matching facial features to verify identity, for unlocking and checks.
AI technology faking a person's face and voice to create false videos.
Unfair or inaccurate AI judgments caused by incomplete or false training data.
Text, images, music or video created by AI itself.
The raw text, photos and numbers AI needs to learn from.
The habit of not believing blindly — checking evidence and analysing from many angles.
3Step by step Steps
- Step 1: See how AI learnsExample: shown millions of labelled cat and dog photos, a computer picks out patterns such as whisker length and ear shape and gradually learns to tell them apart — this method is machine learning. AI is not born clever; it gains its skills through repeated practice on huge amounts of data. The more and better the training data, the more accurate the AI's judgement usually becomes.
- Step 2: Meet everyday AIExample: a voice assistant hears 'will it rain tomorrow', turns the sound into text, understands the question, then checks the weather data and answers — mimicking human listening, thinking and speaking in a few steps. Everyday AI also includes translation apps, automatic photo sorting and online shopping recommendations. Knowing how these applications work helps us use them wisely instead of depending on them blindly.
- Step 3: Learn how AI aids medicineExample: AI scans tens of thousands of X-rays and flags possible lesions within seconds for doctors to review, making checks faster and less likely to miss anything. AI also helps prepare medicines and predict how an illness may develop. Remember that AI is only an assistant — the final diagnosis and treatment decisions rest with the doctor. When technology and professional judgement work together, patients receive the safest care.
- Step 4: Know where bias comes fromExample: if the face photos in the training data show mainly one skin tone, the system will recognise other tones less accurately, treating some people unfairly. AI itself holds no views; the bias usually comes from the data that people supply. Designers must therefore choose and balance the training data carefully, and we who use AI should watch whether its results are fair and reasonable.
- Step 5: Guard against deepfakesExample: a video of a celebrity 'saying' something may actually be made with deepfake face-swapping technology, and even the voice can be imitated. When watching clips, notice whether the lips match the words and whether the lighting and shadows look natural, and verify with official channels. Technology can forge what we see and hear; with a little extra alertness, deepfake content will not fool us easily.
- Step 6: Verify AI answersExample: when AI gives a historical date, check the textbook or a museum website first and use it only after confirming it is correct. AI sometimes writes things that sound reasonable but are actually invented — a phenomenon nicknamed 'AI hallucination'. Treat AI as a starting point rather than the finish line, and always verify important facts with reliable sources, so mistakes never sneak into your homework.
- Step 7: Use AI honestlyExample: after using AI to research an assignment, note in the report which part AI helped with, and write your own understanding and opinions in your own words. Submitting AI-generated content as if it were your own work is dishonest. AI should be a study assistant, not a ghostwriter; using it honestly lets us enjoy the benefits of technology while keeping our good name and our true skills.
4Diagrams Diagrams
5Worked example Example
Example: Lok had an AI chatbot generate a book report and handed it straight in; the teacher found a factual error. Analyse what he did wrong and give the right steps to complete the report with AI.
- Wrong one: submitting AI-generated content as his own work breaches honesty; he should tell the teacher what AI helped with.
- Wrong two: no verification — AI can fabricate plausible-sounding facts; check against books or official websites.
- Right step one: read the book himself, list the outline and views, and use AI only to spot gaps and polish wording.
- Right step two: after querying AI, verify each author, date and claim one by one.
- Right step three: write in his own words, attach real references, and note which parts AI assisted.
- Answer: Handing in AI content as his own is dishonest and error-prone; the right way is to read and think himself, use AI as helper only, verify everything, and write and credit honestly.
6Common mistakes Mistakes
7Quick check Quick check
Q1What is artificial intelligence?
Q2How does machine learning work?
Q3Name two uses of AI in medicine or transport.
Q4Why can AI be biased?
Q5What principles should guide the use of AI?
8Recap Recap
- AI mimics human learning, recognition and generation, with machine learning finding patterns in vast data.
- Applications span daily life and industries: voice assistants, face recognition, medical aid, farm drones and learning apps.
- AI errs and carries bias, and deepfakes can pass as real — never trust blindly.
- Use AI by verifying content, protecting privacy, crediting honestly and respecting copyright.
- AI is a tool for learning; creativity, judgment and responsibility always belong to people.