Computer Science
Grade 8
20 min
AI Ethics: Considering the Impact of AI
Discuss ethical considerations related to AI, such as bias and fairness. Brainstorming ethical guidelines for AI development.
What you'll learn
- Identify at least three different examples of how AI is used in everyday life and explain whether each example is generally helpful or potentially harmful.
- Explain, in their own words, what 'bias' means in the context of AI and provide an example of how biased data can lead to unfair outcomes.
- Analyze a given scenario involving an AI system and identify at least one potential ethical concern related to fairness, privacy, or bias.
- Propose one way to improve a given AI system or application to make it more fair and ethical, justifying their reasoning with at least one specific example.
Tutorial Preview
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Introduction & Learning Objectives
Learning Objectives
Define AI ethics and explain its importance.
Identify at least three potential positive impacts of AI on society.
Identify at least three potential negative impacts of AI on society.
Explain the concept of bias in AI systems and its implications.
Discuss the importance of fairness, transparency, and accountability in AI development.
Propose simple ethical considerations for a given AI application.
Recognize the role of human responsibility in guiding AI's development and use.
Imagine a self-driving car making a split-second decision to avoid an accident 🚗. Who decides what's 'right' in that moment, and who is responsible if something goes wrong? 🤔
In this lesson, we'll explore the ethical considerations surrounding Artificial...
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Key Concepts & Vocabulary
TermDefinitionExample
AI EthicsThe set of moral principles and values that guide the design, development, and use of Artificial Intelligence to ensure it benefits humanity and avoids harm.Considering if an AI system used for hiring is fair to all applicants, regardless of their background.
Bias (in AI)When an AI system makes unfair or inaccurate predictions or decisions because its training data was not representative or contained existing societal prejudices.An AI trained only on images of light-skinned faces might struggle to accurately recognize dark-skinned faces, showing a bias in its performance.
Fairness (in AI)Ensuring that AI systems treat all individuals and groups equitably, without discrimination or prejudice, and provide similar opportunities or outcomes.An AI system for appr...
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Core Syntax & Patterns
The 'Human-in-the-Loop' Principle
AI systems should be designed to augment human capabilities and judgment, not entirely replace them, especially in critical decision-making processes.
This rule emphasizes that humans should maintain oversight and control over AI, particularly when decisions have significant consequences for people's lives. It's about collaboration, not full automation.
Data Fairness Principle
AI systems must be trained on diverse, representative, and unbiased data to prevent the perpetuation or amplification of existing societal biases.
To ensure AI is fair, we must carefully select and clean the data used to train it. If the data is biased, the AI will learn and repeat those biases, leading to unfair outcomes.
Transparency and Expla...
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Challenging
A school wants to use an AI to predict which students are at risk of dropping out to offer them help. Which of the following ethical frameworks is the most complete and responsible approach, based on the tutorial?
A.The AI should be a 'black box' to protect the privacy of the algorithm, and its predictions should be automatically sent to parents.
B.The AI must be transparent, its predictions reviewed by a human counselor (Human-in-the-Loop), the student data kept private, and the school is accountable for how the information is used.
C.The AI should be trained only on academic grades to ensure fairness, and the students with the lowest scores are automatically enrolled in extra classes.
D.The AI's main goal is efficiency, so it should operate without human oversight to identify at-risk students as quickly as possible.
Challenging
Compare the two worked examples: the AI Hiring Tool and the Personalized News Feed. Which system poses a greater risk of violating the 'Data Fairness Principle' directly, and which poses a greater risk of creating long-term societal division?
A.Hiring Tool (Data Fairness); News Feed (Societal Division).
B.News Feed (Data Fairness); Hiring Tool (Societal Division).
C.Both pose equal risks in both categories.
D.Neither poses a significant risk if designed correctly.
Challenging
A common pitfall is thinking AI is always 'smart' or 'right'. Construct the best argument against replacing a human judge entirely with an AI, even if the AI is 99% accurate, using the principles of Accountability and Transparency.
A.An AI judge would be too expensive to build and maintain.
B.An AI judge could be hacked, which is the only real risk.
C.Even if accurate, an AI judge lacks true understanding and empathy. It cannot be held morally accountable for a life-altering decision, and if its reasoning is a 'black box,' its decisions cannot be truly understood or challenged, violating transparency.
D.Human judges are better because they have more life experience, and no AI can ever match that.
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AI Ethics: Considering the Impact of AI is a Grade 8 Computer Science lesson on ExcelOS.
What will I learn in AI Ethics: Considering the Impact of AI?
You'll be able to: Identify at least three different examples of how AI is used in everyday life and explain whether each example is generally helpful or potentially harmful; Explain, in their own words, what 'bias' means in the context of AI and….
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How many practice questions are included with AI Ethics: Considering the Impact of AI?
This lesson includes 25 practice questions across multiple difficulty levels, each with instant feedback and explanations.