Ethical AI Project

Assignment created by David Hicks (School of Education), using prompts with ChatGPT

Other Assignments In This Series

This assignment is the fourth week of a five-week series on generative AI.

Rationale

This assignment challenges students to apply their knowledge of AI and ethics by designing an AI-based project that addresses a real-world problem responsibly.

Objectives

  • Design an AI-based project addressing a specific problem.
  • Incorporate ethical considerations.
  • Present and defend the project.

Activities

  1. Readings and Video:
  2. Discussion Questions: Use these questions in small group discussions or online forums to explore the readings before students begin their projects.
    • Across the readings and video, several key ethical principles are repeated (such as fairness, transparency, and accountability). How are these principles defined or emphasized differently across the sources?
    • What tensions or trade-offs between ethical goals (like innovation vs. privacy, or safety vs. autonomy) emerge across the materials? Which of these trade-offs feels most relevant to your project?
    • How do the different sources frame the role of human responsibility in AI development and deployment? Are there disagreements or differences in tone or emphasis?
    • Which ethical challenges (from the 16 challenges, curated readings, or video) do you believe are most urgent today, and which are most likely to impact your own project? Why?
    • Several sources mention the importance of understanding stakeholders. How do the readings and video suggest we identify and respond to the needs of diverse stakeholders when designing AI systems?
    • After synthesizing the frameworks, examples, and theories presented, what would you propose as a working definition of “ethical AI design”? How might that definition guide your upcoming project decisions?
  3. Project Proposal:
    1. Identify a real-world problem that can be addressed with AI.
    2. Research existing AI solutions and their limitations.
    3. Develop a proposal outlining your AI solution, including ethical considerations.
      Example Proposal Excerpt:

      Project: AI for Personalized Learning in Education

      Problem: Standardized education often fails to address individual student needs.

      Solution: Develop an AI system that creates personalized learning plans based on student performance data.

      Ethical Considerations: Ensure data privacy and mitigate bias in AI-generated plans.

    4. Submit the proposal for review.
    5. Assessment: Proposals will be reviewed for feasibility, creativity, and ethics.
  4. Project Development:
    1. Form teams to develop the project.
    2. Follow a project plan, assigning tasks and deadlines.
    3. Regularly meet to discuss progress and address challenges.
    4. Conduct user testing or simulations to validate your AI solution.
    5. Assessment: Progress will be monitored through regular updates and peer feedback.
    6. Example Progress Report:

      Week 2: Developed initial AI model for personalized learning plans.
      Week 4: Conducted user testing with a small group of students.
      Week 6: Refined AI model based on feedback and addressed identified biases.

  5. Final Presentation and Report:
    1. Prepare a presentation summarizing your project, including the problem, solution, ethical considerations, and results.
    2. Present your project to the class, followed by a Q&A session.
    3. Submit a detailed report documenting your project and findings.
    4. Assessment: Evaluated on project design, ethics, effectiveness, and presentation skills.
    5. Example Presentation Slide:

      Slide 1: Introduction to AI for Personalized Learning
      Slide 2: Identified Problem and Objectives
      Slide 3: AI Solution and Implementation
      Slide 4: Ethical Considerations and Mitigation Strategies
      Slide 5: Results and Future Directions

Final Report Example

AI for Personalized Learning in Education

Introduction

Personalized learning is a transformative approach to education, tailoring instruction to meet individual student needs. This project explores the development of an AI system designed to create personalized learning plans based on student performance data, with a focus on ethical considerations.

Problem Statement

Standardized education often fails to address the diverse needs of students, leading to gaps in understanding and engagement. An AI-driven personalized learning system can adapt content and teaching strategies to suit each student’s unique learning style and pace.

AI Solution

The proposed AI system utilizes machine learning algorithms to analyze student data, including assessment results, learning preferences, and progress over time. Based on this analysis, the AI generates personalized learning plans that recommend specific resources, activities, and interventions tailored to each student’s needs.

Implementation

The development process involves several key steps:

  1. Data Collection: Gather comprehensive data on student performance and learning preferences.
  2. Model Training: Train machine learning models using this data to identify patterns and predict optimal learning strategies.
  3. Personalization: Develop algorithms to generate individualized learning plans based on model predictions.
  4. User Testing: Conduct user testing with a diverse group of students to validate the effectiveness of the personalized plans.
  5. Refinement: Continuously refine the AI system based on feedback and performance metrics.
Ethical Considerations

Ensuring data privacy and addressing bias are critical to the success of this project. Measures include:

  • Data Privacy: Implementing robust encryption and access controls to protect student data.
  • Bias Mitigation: Regularly auditing the AI models for biases and updating training data to reflect diverse student populations.
  • Transparency: Providing clear explanations of AI-generated recommendations to educators and students, fostering trust and understanding.
Results

Initial user testing demonstrated significant improvements in student engagement and comprehension. Personalized learning plans helped students better grasp difficult concepts and stay motivated. Feedback from educators highlighted the system’s potential to support differentiated instruction and targeted interventions.

Conclusion

The AI-driven personalized learning system shows promise in addressing the limitations of standardized education. By focusing on data privacy, bias mitigation, and transparency, the project ensures ethical considerations are integral to its design and implementation. Future work will involve expanding the dataset, refining algorithms, and exploring integration with existing educational platforms.

Assessment Rubric

Table 1. Assessment Rubric
Criteria Excellent Good Fair Poor
Project Proposal Highly original and clearly addresses a real-world problem with thoughtful ethical integration Clear and relevant proposal with some ethical consideration Basic problem identified; ethical issues minimally addressed Vague or unfocused; ethics not addressed
Project Development Comprehensive plan and excellent team collaboration; regular updates with significant progress Good teamwork and steady progress with occasional updates Limited progress or unclear updates Poor organization; little evidence of progress
Ethical Integration Ethical issues fully considered with clear strategies for privacy, bias mitigation, and transparency Most major ethical issues addressed Some ethical issues identified but not fully explored Little or no attention to ethical concerns
Final Presentation & Report Clear, engaging, and well-supported by data and visuals; excellent handling of questions Clear presentation and good supporting material Basic content covered; lacks polish or support Unclear or incomplete presentation and report

 

Last Updated on July 7, 2025