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Unit 1-AI Reflection, Project Cycle and Ethics
School Revise · Class 9 Artificial Intelligence · Unit 1
AI Reflection, Project Cycle and Ethics
Code 417, Class 9. AI is smart machines that help solve problems. Here we learn what AI is, how an AI project is built, and how to use AI fairly.
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What this unit is about
Artificial Intelligence (AI) is making machines do tasks that usually need human intelligence. This unit looks at what AI is, its domains, the AI project cycle, and ethics.
1. What is AI and its domains
AI helps machines see, understand language and make decisions. It works in three domains: Data (learning from numbers), Computer Vision (understanding images), and Natural Language Processing (understanding text and speech).
2. The AI Project Cycle
An AI project follows steps: Problem Scoping (define the problem), Data Acquisition (collect data), Data Exploration (study it), Modelling (train the AI), Evaluation (check it) and Deployment (use it).
3. AI ethics
AI must be fair and safe. Bias happens when AI is unfair because its data was unfair. We protect privacy, use AI honestly, and think about how it affects people.
Practise with the interactive
Explore the idea by tapping. The interactive opens right here in the lesson.
Practice set A, multiple choice
1. AI stands for …
Artificial Intelligence.
2. The domain that understands images is …
Computer Vision.
3. The first step of the AI project cycle is …
Problem Scoping.
4. When AI is unfair due to unfair data it shows …
bias.
Practice set B, short answer
1. What is Artificial Intelligence?
Making machines do tasks that usually need human intelligence.
2. Name the three domains of AI.
Data, Computer Vision and Natural Language Processing.
3. Name the steps of the AI project cycle.
Problem Scoping, Data Acquisition, Data Exploration, Modelling, Evaluation and Deployment.
Quick summary
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AI makes machines do tasks that usually need human intelligence. Its three domains are Data, Computer Vision and Natural Language Processing. The AI project cycle has steps: Problem Scoping, Data Acquisition, Data Exploration, Modelling, Evaluation and Deployment. AI must be fair and safe: bias comes from unfair data, so we protect privacy and use AI honestly. |
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These free Class 9 Artificial Intelligence (Code 417) notes explain AI reflection, the three domains of AI, the AI project cycle, and AI ethics and bias with clear examples and practice, for CBSE students across India and the Gulf including the UAE, Saudi Arabia, Qatar, Oman, Kuwait and Bahrain.
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