Ethics 102

Introduction to Generative AI Ethics


Dr. Garcia

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Course Overview

Introduction to Generative AI Ethics

Lesson 1: Understanding Generative AI

  • Objective: Provide an overview of what Generative AI is, including its definition, types, and applications.
  • Content: Introduction to Generative AI, its history, how it works, and examples of its use in various fields such as art, music, and content creation.

Lesson 2: Ethical Principles in AI

  • Objective: Introduce the foundational ethical principles relevant to AI.
  • Content: Discussion on ethical principles such as beneficence, non-maleficence, autonomy, justice, and explicability, and how they apply to AI technologies.

Lesson 3: Privacy Concerns and Data Protection

  • Objective: Explore the privacy implications of Generative AI and strategies for data protection.
  • Content: Examination of how Generative AI uses data, potential privacy risks, data anonymization techniques, and regulations like GDPR.

Lesson 4: Bias and Fairness in Generative AI

  • Objective: Understand the issues of bias and fairness in Generative AI models.
  • Content: Analysis of how biases can be introduced in training data, the impact of biased AI, and methods to mitigate bias and ensure fairness.

Lesson 5: Accountability and Transparency

  • Objective: Discuss the importance of accountability and transparency in the development and deployment of Generative AI.
  • Content: Overview of accountability frameworks, the need for transparent AI systems, and best practices for maintaining transparency.

Lesson 6: The Social Impact of Generative AI

  • Objective: Assess the societal implications of Generative AI technologies.
  • Content: Exploration of how Generative AI affects jobs, social interactions, media consumption, and public opinion, including both positive

and negative impacts.

Lesson 7: Intellectual Property and Ownership

  • Objective: Examine issues related to intellectual property and ownership in the context of Generative AI.
  • Content: Discussion on who owns the outputs of Generative AI, the challenges of copyright and patents, and legal precedents.

Lesson 8: Ethical Use Cases and Best Practices

  • Objective: Identify and evaluate ethical use cases and best practices for deploying Generative AI.
  • Content: Case studies of ethical and unethical uses of Generative AI, guidelines for ethical deployment, and industry best practices.

Lesson 9: Regulatory and Policy Considerations

  • Objective: Review existing and proposed regulations and policies governing Generative AI.
  • Content: Overview of international and national regulations, the role of policy in shaping AI development, and future regulatory trends.

Lesson 10: The Future of Generative AI Ethics

  • Objective: Speculate on the future ethical challenges and opportunities in Generative AI.
  • Content: Discussion on emerging trends in Generative AI, potential future ethical dilemmas, and strategies for fostering ethical innovation in AI technologies.
  • This course requires enrollment in Ethics 101
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  • Last Update May 21, 2024