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Course Outline
Foundations of Ethics in AI
- The significance of ethics within the AI domain
- Historical background and contemporary ethical debates
- Core ethical principles guiding AI deployment
Challenges of LLMs from an Ethical Perspective
- Privacy issues and data protection standards
- Issues of transparency, accountability, and bias in LLMs
- Societal and employment impacts resulting from LLM adoption
Implementing Ethical Frameworks for LLMs
- Models for ethical decision-making in AI contexts
- Case studies exploring ethical dilemmas in LLM applications
- Establishing guidelines for the ethical use of LLMs
Approaches for Ethical LLM Implementation
- Best practices for responsible AI engineering
- Incorporating stakeholder feedback and diverse viewpoints
- Fostering an organizational culture of ethical AI
Practical Lab: Ethical Evaluation of LLM Scenarios
- Examining real-world examples involving LLMs
- Reviewing ethical consequences and developing mitigation strategies
- Sharing insights and proposing recommendations
Recap and Future Directions
Requirements
- Fundamental knowledge of AI and machine learning concepts
- Practical experience with ethical decision-making models
- Basic familiarity with LLMs and their broader societal effects
Target Audience
- AI specialists and ethicists
- Data scientists and software engineers
- Policy makers and stakeholders involved in AI governance
7 Hours
