CCE · Primary 6 · Ethical Dilemmas in Public Policy · Semester 2

Artificial Intelligence and Ethical Considerations

Exploring the emerging ethical dilemmas posed by artificial intelligence, such as algorithmic bias, job displacement, and autonomous decision-making.

• MOE Syllabus Outcomes
• MOE: Cyber Wellness - P6
• MOE: Moral Reasoning - P6

About This Topic

Artificial Intelligence and Ethical Considerations guides Primary 6 students through the ethical dilemmas of AI, such as algorithmic bias, job displacement, and autonomous decision-making. Aligned with MOE Cyber Wellness and Moral Reasoning standards, this topic prompts students to explain ethical challenges in AI development, analyze bias in systems trained on skewed data, and predict impacts on employment and human choices. Real-world examples, like facial recognition errors affecting certain groups, help students see how bias leads to unfair outcomes in society.

This content builds moral reasoning by encouraging analysis of public policy issues. Students weigh benefits of AI efficiency against risks of reduced human oversight or economic shifts, fostering skills in prediction and balanced debate. Connections to Singapore's Smart Nation initiative make discussions relevant, as students consider local contexts like AI in healthcare or transport.

Active learning benefits this topic greatly because ethical concepts are abstract and future-oriented. Role-plays of AI dilemmas, group debates on bias cases, and scenario simulations allow students to experience trade-offs firsthand, building empathy, critical thinking, and confident articulation of viewpoints.

Key Questions

1. Explain the ethical challenges associated with the development and deployment of artificial intelligence.
2. Analyze the potential for algorithmic bias in AI systems and its societal impact.
3. Predict the future implications of AI on employment and human decision-making.

Learning Objectives

• Explain the ethical challenges associated with the development and deployment of artificial intelligence.
• Analyze the potential for algorithmic bias in AI systems and its societal impact.
• Evaluate the implications of AI on employment and human decision-making.
• Propose ethical guidelines for the responsible use of AI in specific contexts.

Before You Start

Introduction to Technology and Society

Why: Students need a basic understanding of how technology impacts daily life and society to grasp the broader implications of AI.

Understanding Fairness and Justice

Why: Prior exposure to concepts of fairness and justice is essential for students to analyze ethical dilemmas and algorithmic bias.

Key Vocabulary

Artificial Intelligence (AI)	Computer systems designed to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making.
Algorithmic Bias	Systematic and repeatable errors in a computer system that create unfair outcomes, such as favoring one arbitrary group of users over others.
Job Displacement	The situation where workers lose their jobs because their tasks are taken over by technology, such as AI and automation.
Autonomous Decision-Making	The ability of an AI system to make choices and take actions independently, without direct human intervention.
Data Privacy	The protection of personal information from unauthorized access, use, or disclosure, which is a key concern with AI systems that process large amounts of data.

Watch Out for These Misconceptions

Common Misconception

AI is always neutral and fair.

What to Teach Instead

AI reflects biases in its training data, leading to unfair decisions like misidentifying faces from certain ethnic groups. Active discussions of real cases help students spot patterns in data sources. Group analysis reveals how human inputs shape AI outputs, correcting the myth through evidence sharing.

Common Misconception

AI will eliminate all human jobs.

What to Teach Instead

AI automates routine tasks but creates new roles in AI maintenance and creative fields. Simulations of job scenarios show displacement alongside opportunities. Student debates balance fears with innovations, building nuanced views via peer perspectives.

Common Misconception

Ethics only apply to humans, not machines.

What to Teach Instead

AI decisions impact lives, so ethical design is crucial for accountability. Role-plays demonstrate consequences of unchecked AI choices. Collaborative ethical audits teach students to apply moral reasoning to technology.

Active Learning Ideas

Debate Circles: AI Bias Pros and Cons

Divide class into groups to research one pro and one con of AI bias examples, such as hiring algorithms. Groups present arguments in a circle debate, with peers asking clarifying questions. Conclude with a class vote on mitigation strategies.

45 min·Small Groups

Role-Play: Job Displacement Scenarios

Pairs act out scenes where AI replaces a job, like a robot chef or self-driving taxi. One student plays the affected worker, the other the policymaker proposing solutions. Switch roles and discuss ethical responses as a class.

30 min·Pairs

Case Study Stations: Real AI Ethics

Set up stations with cases like biased loan approvals or autonomous car dilemmas. Small groups rotate, note ethical issues, and propose fixes on worksheets. Share findings in a whole-class gallery walk.

50 min·Small Groups

Future Prediction Think Tank

In small groups, students brainstorm AI's 10-year impact on jobs in Singapore, using prompt cards for categories like education and retail. Groups create posters with predictions and ethical safeguards, then pitch to the class.

40 min·Small Groups

Real-World Connections

• In Singapore, AI is being explored for use in healthcare, such as diagnostic tools to help doctors identify diseases faster. Students can consider the ethical implications if an AI diagnostic tool is biased against certain patient demographics.
• Autonomous vehicles are being tested globally, including in Singapore. Students can analyze the ethical dilemmas faced by self-driving cars in unavoidable accident scenarios, like deciding who to protect.
• AI-powered hiring tools are used by some companies to screen job applications. Students can investigate how algorithmic bias in these tools might unfairly disadvantage certain job seekers based on their background.

Assessment Ideas

Discussion Prompt

Present students with a scenario: 'An AI system is developed to help judges decide on bail. It is trained on past cases where certain communities were disproportionately denied bail. What are the ethical concerns here?' Facilitate a class discussion using these guiding questions: What is the potential bias? Who might be unfairly affected? How could this bias be addressed?

Quick Check

Ask students to write down one example of AI they encounter or hear about. Then, have them identify one potential ethical challenge related to that specific AI example. For instance, 'AI in social media feeds' could have the challenge of 'manipulating user emotions'.

Exit Ticket

Provide students with a statement: 'AI will create more jobs than it destroys.' Ask them to write 'Agree' or 'Disagree' and then provide one reason for their choice, referencing either job displacement or the creation of new roles related to AI.

Frequently Asked Questions

How can active learning help teach AI ethics to Primary 6 students?

Active learning makes AI ethics engaging by turning abstract ideas into experiences. Role-plays of bias scenarios let students feel impacts on 'victims,' while debates build argumentation skills. Case study stations encourage evidence-based analysis, helping students connect ethics to real Singapore contexts like Smart Nation projects. This approach boosts retention and moral reasoning over lectures.

What are examples of algorithmic bias for kids?

Algorithmic bias happens when AI favors certain groups due to flawed training data. For example, facial recognition might fail on darker skin tones if mostly trained on light-skinned faces, or hiring tools could overlook women if past data shows male dominance. Students can explore these via simplified videos and group discussions to grasp societal effects.

How does AI affect jobs in Singapore?

AI may displace routine jobs like data entry but create demand for skills in programming and AI ethics. Singapore's SkillsFuture initiative prepares workers through reskilling. Classroom predictions help students see balanced views: automation in MRT systems frees humans for oversight roles, emphasizing adaptability.

What ethical challenges come with autonomous AI decisions?

Autonomous AI, like self-driving cars choosing crash paths, raises dilemmas on prioritizing lives. Developers must code ethical rules, but biases can skew outcomes. Students debate frameworks like utilitarianism versus individual rights, linking to MOE moral reasoning for thoughtful public policy views.