Unit 5: Ethics and Bias

Lesson 5: Responsible AI and Ethical Decision-Making (1 hour)

Lesson content from Unit 5: Ethics and Bias

Lesson 5: Responsible AI and Ethical Decision-Making (1 hour)

Learning Objectives

  • Understand principles of responsible AI development
  • Identify ethical dilemmas in AI
  • Practice ethical decision-making
  • Discuss how to be responsible AI users and creators

Materials Needed

  • Ethical dilemma scenarios
  • Responsible AI frameworks
  • Case studies
  • Student notebooks
  • Discussion materials

Time Breakdown

  • Review economic impacts (5 min)
  • Principles of responsible AI (15 min)
  • Ethical dilemmas and case studies (20 min)
  • Being responsible users and creators (15 min)
  • Wrap-up and unit review (5 min)

Activities

1. Review Economic Impacts (5 min)

  • How does AI affect jobs?
  • What are the concerns and opportunities?
  • Bridge: "Today we'll explore how to develop and use AI responsibly"

2. Principles of Responsible AI (15 min)

Key Principles:

1. Fairness:

  • Treat all people fairly
  • Avoid discrimination
  • Ensure equal opportunity
  • Test for bias

2. Transparency:

  • Clear about how AI works
  • Explainable decisions
  • Users understand what's happening
  • Open about limitations

3. Accountability:

  • Who is responsible for AI decisions?
  • Clear lines of responsibility
  • Mechanisms for recourse
  • Consequences for harm

4. Privacy:

  • Protect user data
  • Minimize data collection
  • Get informed consent
  • Allow user control

5. Safety and Security:

  • Systems work reliably
  • Protected from attacks
  • Safe for users
  • Fail gracefully

6. Human-Centered:

  • Benefit humans
  • Respect human rights
  • Augment human capabilities
  • Human oversight

7. Social and Environmental Well-Being:

  • Consider societal impact
  • Benefit society
  • Minimize environmental impact
  • Sustainable development

Putting Principles into Practice:

  • Consider principles during development
  • Test systems against principles
  • Monitor for violations
  • Iterate and improve

Challenges:

  • Principles can conflict
  • Requires trade-offs
  • No perfect solutions
  • Ongoing process

3. Ethical Dilemmas and Case Studies (20 min)

Activity: Ethical Dilemma Scenarios

Students work in groups to analyze ethical dilemmas:

Scenario 1: Autonomous Vehicles

  • Self-driving car must choose: Hit pedestrian or crash into wall (killing passenger)
  • Who should decide? How? What values matter?
  • Discuss: Different perspectives, no easy answers

Scenario 2: Predictive Policing

  • AI predicts where crime will occur
  • Police allocate resources based on predictions
  • But: Predictions might be biased, reinforce stereotypes
  • Discuss: Benefits vs. harms, alternatives

Scenario 3: Healthcare AI

  • AI diagnoses diseases, recommends treatments
  • More accurate than doctors in some cases
  • But: Black box, hard to explain, errors have high stakes
  • Discuss: When to use? How to ensure safety?

Scenario 4: Social Media Algorithms

  • Algorithms maximize engagement (more time on platform)
  • But: This might promote harmful content, polarize users
  • Platform profits, but society might be harmed
  • Discuss: Responsibility, regulation, alternatives

Scenario 5: AI in Hiring

  • AI screens job applicants, faster and cheaper
  • But: Might be biased, reduces human judgment
  • Some applicants might be unfairly excluded
  • Discuss: When is it acceptable? How to ensure fairness?

For Each Scenario:

  1. Identify stakeholders (who is affected?)
  2. Identify benefits and harms
  3. Identify ethical principles involved
  4. Discuss different perspectives
  5. Propose solutions or compromises
  6. Present to class

Key Learning:

  • Ethical dilemmas have no perfect answers
  • Multiple valid perspectives
  • Requires careful consideration
  • Trade-offs are inevitable

4. Being Responsible Users and Creators (15 min)

As AI Users:

1. Be Critical:

  • Question AI decisions
  • Don't blindly trust
  • Understand limitations
  • Verify important information

2. Be Aware:

  • Understand what data you're sharing
  • Read privacy policies (when possible)
  • Know how AI affects you
  • Stay informed

3. Advocate:

  • Demand transparency
  • Support fair AI
  • Report problems
  • Use your voice

4. Use Responsibly:

  • Don't use AI to harm others
  • Respect others' privacy
  • Consider consequences
  • Follow ethical guidelines

As Future AI Creators:

1. Consider Ethics from Start:

  • Design with ethics in mind
  • Not an afterthought
  • Build in fairness, transparency
  • Test for bias

2. Diverse Teams:

  • Include diverse perspectives
  • Different backgrounds, experiences
  • Helps identify bias, consider different needs
  • Better solutions

3. Test Thoroughly:

  • Test with diverse users
  • Test for bias
  • Test edge cases
  • Monitor after deployment

4. Be Transparent:

  • Explain how systems work
  • Be honest about limitations
  • Allow user control
  • Provide explanations

5. Take Responsibility:

  • Acknowledge mistakes
  • Fix problems
  • Learn from failures
  • Continuously improve

Discussion:

  • What can you do as a user?
  • If you create AI, what will you do differently?
  • How can we build better AI?

5. Wrap-Up and Unit Review (5 min)

Unit 5 Summary:

  • Ethics: How we should use AI responsibly
  • Bias: Can appear in AI, needs to be addressed
  • Privacy: Important right, AI raises concerns
  • Jobs: AI affects employment in complex ways
  • Responsibility: We all have role to play

Key Takeaways:

  • AI has powerful benefits but also risks
  • Ethics matter in AI development and use
  • We need to address bias, privacy, and other concerns
  • We all have responsibility as users and creators
  • There are no easy answers, but discussion and action are important

Final Reflection:

  • What ethical concerns matter most to you?
  • How will you use AI responsibly?
  • What would you do differently if creating AI?

Preview Unit 6: Hands-On Projects - We'll put everything together and create our own AI projects!

Unit 5 Assessment Rubric

Formative Assessment (Throughout Unit)

  • Participation in discussions: 25%
  • Case study analysis: 30%
  • Reflection journal entries: 25%
  • Homework assignments: 20%

End-of-Unit Assessment

Unit Quiz (20 questions, open-note):

  • Ethics and bias (5 questions)
  • Fairness and detection (5 questions)
  • Privacy and surveillance (5 questions)
  • Jobs and economy (5 questions)

Ethical Analysis Essay (2-3 pages):

  • Choose an AI application or technology
  • Analyze: Ethical concerns, who is affected, potential solutions
  • Apply principles of responsible AI
  • Reflect on your own responsibilities

Rubric for Ethical Analysis Essay

Criteria Excellent (4) Good (3) Satisfactory (2) Needs Improvement (1)
Understanding Shows deep understanding of ethical concepts Shows good understanding Shows basic understanding Shows limited understanding
Analysis Thorough, nuanced analysis of ethical issues Good analysis Basic analysis Limited analysis
Application Effectively applies ethical principles Applies principles adequately Basic application Limited application
Reflection Thoughtful reflection on responsibilities Good reflection Basic reflection Limited reflection
Communication Clear, well-organized writing Clear writing Adequate writing Unclear or disorganized

Unit 5 Resources

Required Reading/Watching

  • Age-appropriate articles on AI ethics
  • Case studies of AI bias
  • Examples of responsible AI practices

Recommended Exploration

  • AI Ethics resources and frameworks
  • Bias detection tools and demos
  • Privacy and surveillance case studies

Teacher Notes

  • These are sensitive topics - create safe space for discussion
  • Emphasize multiple perspectives, no easy answers
  • Encourage respectful debate
  • Be prepared for strong opinions
  • Focus on critical thinking, not right answers
  • Connect to students' own experiences

Unit 5 Extension Activities (Optional)

For Advanced Students

  • Research specific bias incidents in detail
  • Analyze ethical frameworks and theories
  • Research policy and regulation proposals
  • Explore technical solutions to bias
  • Research specific companies' AI ethics policies

For Students Needing More Support

  • Focus on concrete examples
  • Use simpler scenarios
  • Provide more structure for discussions
  • Use visual aids and examples
  • Focus on understanding concepts rather than complex analysis

Next Unit Preview

Unit 6: Hands-On Projects will give you the opportunity to create your own AI applications! We'll use no-code and low-code tools to build projects that solve real problems. Get ready to be creative and put everything you've learned into practice!