Code of Conscience: Ethical Decision-Making and AI Governance in the Digital Age

Duration: 6–8 Weeks (or Self-Paced)
Level: Intermediate
Format: Video Lessons, Case Studies, Reflective Journals, Ethical Scenarios, Discussions, Capstone Policy Project
Tools Used: Ethical decision-making frameworks, algorithm audit checklists, AI policy templates, stakeholder analysis grids

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Course Objective

To equip learners with the principles, tools, and frameworks needed to make ethically sound decisions in real-world settings—particularly where artificial intelligence and emerging technologies are involved.

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Module 1: Introduction to Ethics and Moral Reasoning

Topics Covered:

• What is Ethics? Morality vs Legality

• Types of Ethics: Normative, Applied, Descriptive

• Classical Ethical Theories: Utilitarianism, Deontology, Virtue Ethics

• The Ethics of Decision-Making in Leadership and Technology

• Ethical Dilemmas and Gray Zones

Learning Outcome:
Build foundational knowledge of ethical frameworks and how they apply to personal and professional decision-making.

Activities:

• Analyze a classic ethical dilemma using multiple ethical theories

• Reflect on a difficult decision you’ve made and how it aligns with ethical principles

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Module 2: Ethical Decision-Making in Practice

Topics Covered:

• Models of Ethical Decision-Making (PLUS Model, Tucker Model, Ethical Triangle)

• Identifying Stakeholders and Consequences

• Bias, Blind Spots, and Rationalization

• Organizational Ethics and Accountability

• Case Studies from Business, Law, and Medicine

Learning Outcome:
Develop a systematic approach to making thoughtful and transparent ethical decisions.

Activities:

• Apply the PLUS Model to a workplace dilemma

• Map stakeholders in a controversial organizational decision

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Module 3: Foundations of AI and Ethical Risk

Topics Covered:

• What is Artificial Intelligence? Overview of AI Systems

• Machine Learning, Neural Networks, and Data-Driven Automation

• Risks in AI Development: Bias, Discrimination, Opaqueness

• The Ethics of Automation, Surveillance, and Deepfakes

• Societal and Cultural Implications of AI Use

Learning Outcome:
Understand the ethical challenges inherent in the development and deployment of AI technologies.

Activities:

• Identify and explain three ethical risks in an AI system you use regularly

• Watch and critique a documentary on AI ethics

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Module 4: Fairness, Accountability, and Transparency in AI (FAT)

Topics Covered:

• Definitions and Tensions of Fairness

• Auditing Algorithms for Bias and Discrimination

• Explainable AI (XAI) and the Right to Explanation

• Who is Accountable? Developers, Users, Companies

• Transparency in Data Collection, Consent, and Use

Learning Outcome:
Evaluate AI systems for fairness and propose strategies for responsible algorithm design.

Activities:

• Analyze a real-world algorithmic bias case (e.g., COMPAS, hiring AI, facial recognition)

• Draft a fairness and accountability checklist for an AI tool

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Module 5: Privacy, Consent, and Data Ethics

Topics Covered:

• The Value of Privacy in the Digital Age

• Informed Consent and Data Ownership

• Surveillance, Tracking, and Behavioral Targeting

• Data Ethics in Research and Consumer Technology

• Laws and Regulations: GDPR, CCPA, HIPAA

Learning Outcome:
Understand ethical and legal responsibilities regarding personal data and digital identity.

Activities:

• Conduct a data privacy audit of a social media platform

• Develop a data consent form for an AI application

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Module 6: Global Perspectives and Inclusive AI

Topics Covered:

• Cultural Ethics and Global Variations

• Ethics of Inclusion and Accessibility in AI Design

• Digital Colonialism and Global AI Power Dynamics

• Technology’s Impact on Marginalized Communities

• Ethics in Language Models and Translation Tools

Learning Outcome:
Recognize the global impact of AI and ensure cultural inclusivity in ethical decisions.

Activities:

• Compare AI ethical standards in different regions (EU, US, China, Africa)

• Reflect on how AI could positively or negatively affect your local community

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Module 7: Regulation, Governance, and the Future of Ethical AI

Topics Covered:

• Role of Policy, Law, and Regulation in AI Ethics

• Self-Governance vs External Regulation

• Global Initiatives: UNESCO, OECD, EU AI Act, US Blueprint for AI Bill of Rights

• Ethics Boards, Audits, and Accountability Structures

• The Future of Work, Creativity, and Decision-Making with AI

Learning Outcome:
Evaluate and propose frameworks for ethically managing AI in organizations and society.

Activities:

• Write a brief policy recommendation on a proposed AI regulation

• Simulate an ethics committee reviewing a controversial AI product

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Module 8: Capstone – Build an Ethical AI Policy Framework

Project Description:
Create a comprehensive ethical framework or policy guideline for an organization or product, including:

• Ethical values and guiding principles

• Risk and stakeholder analysis

• Bias prevention strategy

• Transparency and accountability mechanisms

• Monitoring, audit, and feedback systems

Final Deliverables:

• 6–10 Page Ethical Policy Document or Presentation

• Stakeholder map and ethical decision model diagram

• Recorded reflection or summary video (3–5 minutes)

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Bonus Resources

• AI Ethics Glossary

• Ethical Audit Toolkit for AI Projects

• Algorithmic Accountability Templates

• List of Top Research Papers and Books on AI Ethics

• Downloadable Ethical Decision-Making Models

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Teaching Methodology

• Real-world ethical dilemma analysis

• Video lectures featuring expert insights

• Interactive reflection and discussion prompts

• Group-based scenario planning

• Capstone project aligned with practical applications

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Target Audience

• AI/ML Developers and Engineers

• Data Scientists and Analysts

• Policymakers and Legal Professionals

• Educators, Ethicists, and Researchers

• Students in technology, law, humanities, or business

• Anyone seeking to understand the ethical future of digital technologies