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Course Outline

Introduction to AI Ethics

  • The critical role of ethical considerations in artificial intelligence
  • Historical background and contemporary ethical discourse
  • Core ethical principles governing AI deployment

Ethical Challenges Associated with Large Language Models

  • Privacy safeguards and data protection requirements
  • Ensuring transparency, accountability, and mitigation of bias in LLMs
  • Consequences of LLM integration on workforce dynamics and societal structures

Implementation of Ethical Frameworks for LLMs

  • Structured approaches to ethical decision-making in AI systems
  • Case analyses: Addressing ethical dilemmas in LLM deployment
  • Establishing standards for responsible LLM utilization

Strategies for Responsible LLM Deployment

  • Best practices for developing accountable AI solutions
  • Facilitating engagement with stakeholders and diverse viewpoints
  • Fostering an organizational culture committed to ethical AI governance

Practical Exercise: Ethical Evaluation of LLM Applications

  • Evaluation of real-world scenarios involving LLM technologies
  • Assessment of ethical implications and development of appropriate responses
  • Reporting findings and providing actionable recommendations

Summary and Future Actions

Requirements

  • Foundational knowledge of artificial intelligence and machine learning principles
  • Proficiency in applying ethical decision-making frameworks
  • Understanding of large language models and their broader societal impact

Target Audience

  • AI specialists and ethics practitioners
  • Data scientists and engineering personnel
  • Policymakers and stakeholders involved in AI governance, for government and public sector initiatives
 7 Hours

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