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CBSE Class 10 · Artificial Intelligence · board exam 2027

Chapter 1: Revisiting AI Project Cycle & Ethical Frameworks for AI — notes

The chapter’s 6 parts in the book’s order — the first idea of each and the points Medha Ma’am writes on the board — and the summary at the end. The full lesson and a check question for each part are in the app.

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  1. 1. Revisiting the AI Project Cycle

    Okay, so let's first remember what the AI Project Cycle is.

    • • AI Project Cycle = cyclical process to complete an AI project
    • • 6 Stages: Problem Scoping
    • • Data Acquisition
    • • Data Exploration
    • • Modelling
    • • Evaluation
    • • Deployment

  2. 2. Domains of AI

    Okay, so — AI gets intelligent through training.

    • • 3 Domains of AI (based on data fed in):
    • • 1. Statistical Data - collects, maintains, derives meaning from data
    • • Example: Price comparison websites
    • • 2. Computer Vision (CV) - analyses visual information
    • • Example: Agricultural monitoring with drones
    • • 3. Natural Language Processing (NLP) - human-computer language interaction

  3. 3. What are Ethical Frameworks and Why We Need Them

    Okay, so, let's think about what ethics means.

    • • Ethics = values/morals separating right from wrong
    • • Frameworks = step-by-step guidance for solving problems
    • • Ethical Frameworks = ensure choices do not cause unintended harm
    • • Needed because: AI is a decision-making tool, can be biased
    • • Factors influencing decisions: culture, religion, intuition & values, bias

  4. 4. Types of Ethical Frameworks

    Okay, so — ethical frameworks for AI come in two main types.

    • • 2 Types of Ethical Frameworks:
    • • 1. Sector-based - tailored to specific industries (e.g. Bioethics for healthcare)
    • • 2. Value-based - focus on ethical principles & values
    • • i. Rights-based - protects human rights & dignity
    • • ii. Utility-based - maximizes overall good/benefit
    • • iii. Virtue-based - focuses on character, honesty, integrity

  5. 5. Bioethics and its Principles

    Okay, so let's explore bioethics.

    • • Bioethics = ethical framework for healthcare & life sciences
    • • 4 Principles of Bioethics:
    • • 1. Respect for Autonomy
    • • 2. Do not harm (Non-maleficence)
    • • 3. Maximum benefit for all (Beneficence)
    • • 4. Give Justice
    • • Maleficence = intentionally causing harm

  6. 6. Case Study: Applying Bioethics to AI

    Okay, so let's see how these four bioethics principles can actually fix a real problem.

    • • Case: AI algorithm for high-risk patients
    • • Problem: trained on healthcare EXPENSE data, not actual illness
    • • Result: Western region patients under-classified as low risk
    • • Fix using Bioethics:
    • • - Autonomy: make data & working accessible to patients
    • • - Do not harm: equitable training data for all groups
    • • - Max benefit: use unbiased data, benefit all regions
    • • - Justice: address social structures like racism

Summary

Okay, so let's look back at everything we covered today. We started with the AI Project Cycle, all 6 stages, from Problem Scoping right up to Deployment. We also went over the three domains of AI — Statistical Data, Computer Vision, and Natural Language Processing — along with real examples for each. Then we moved to ethics and frameworks. Ethical frameworks for AI help make sure our choices don't cause unintended harm, and this matters a lot since AI is often used as a decision-making tool, one that can carry bias. We looked at two types of ethical frameworks — sector-based, like Bioethics, and value-based, which splits further into rights-based, utility-based, and virtue-based frameworks. After that, we studied Bioethics closely, with its four principles — Respect for Autonomy, Do not harm, Maximum benefit, and Justice. And finally, we saw a case study of a biased healthcare AI algorithm, and how using these four bioethics principles could have avoided its harmful outcome. So, thinking back — which of these four bioethics principles do you think gets ignored most often in real AI systems?

Ask Medha · Medha Ma’am — CBSE Class 10 Artificial Intelligence, Chapter 1. Written from the textbook, checked twice.

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From the chapter’s own textbook text, part by part, in the book’s own terms; a second, independent model then checked every part against the book. The full lesson, a check question for each part and the practice are in the Ask Medha app.

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