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AI ethics grad level course content planning - Coggle Diagram
AI ethics grad level course content planning
Foundations
Ethics
Philosophical groundings
Classic & modern ethical theories
Principles
Professional vs. AI ethics
AI
GOFAI
Machine learning
Robotics
Design
Engineering Design & Values/ethics
Processes & practices
Principles
Responsible innovation
Value-sensitive design
Toolkits & guidelines
Governance mechanisms
Technical approaches
Fairness/bias
Explainabaility & transparency
Privacy & security
Concepts
Values
Fairness
Bias
Transparency
Explainability
Responsibility
Governance
Accountability
Privacy
Human rights
Dignity
Autonomy
Environmental sustainability
Agency
Principles
Privacy-by-design
Values-by-design
Human-centred design
Technical stewardship
Sociotechnical systems
System
Stakeholders
Virtue
Data
Cross-border flow
Surveillance
Policy
Goals
Students should be able to think through ethics issues that arise with their own projects and be able to assess other AI projects and their AI ethics issues
Students should be able to identify a set of values that are important to an AI project and be able to apply creative solutions to implement the values or have ideas on how the values can be implemented
Students should have a hands-on experience in having worked on an AI ethics project