Generative AI Series: Ethical Considerations In AI

Description:

In this training session, participants will explore the critical ethical dimensions of AI, gaining insights into the potential pitfalls and responsible practices.

Session Description:

In this training session, participants will explore the critical ethical dimensions of AI, gaining insights into the potential pitfalls and responsible practices. The course will commence with an examination of bias and fairness in AI systems, addressing the challenges associated with algorithmic discrimination. Participants will then delve into the importance of explainability and interpretability in AI models, understanding how to ensure transparency and accountability in automated decision-making. The session will conclude by exploring privacy and security concerns in AI applications, providing participants with a holistic perspective on the ethical considerations integral to the responsible development and deployment of AI technologies.

Course Code: BDT325

Duration: Half Day

Learning Objectives:

After this course, participants will have the opportunity to:

• Develop an awareness of bias in AI systems.
• Understand the importance of explainability and interpretability in AI models
• Gain insights into the privacy concerns associated with AI applications
• Learn best practices for safeguarding personal information within AI systems.

• Participants should have a fundamental understanding of key concepts related to artificial intelligence. A basic awareness of data privacy principles and regulations will be helpful. Participants should come with an interest in exploring the ethical and societal implications of AI.

• Course is designed for  a diverse audience, including professionals, decision-makers, and individuals with varying levels of technical expertise. The focus is on ethical considerations and principles rather than delving into technical details of AI algorithms.

• Course is designed for  a diverse audience, including professionals, decision-makers, and individuals with varying levels of technical expertise. The focus is on ethical considerations and principles rather than delving into technical details of AI algorithms.

Course Outline:

• Understanding the concept of bias in AI
• Exploring strategies to identify and mitigate bias in machine learning models.
• The importance of transparent AI models for accountability.
• Examining the implications of AI on individual privacy.
• Best practices for safeguarding personal information in AI systems.
• Strategies for enhancing the cybersecurity of AI systems.
• Analyzing real-world cases highlighting ethical challenges in AI development and deployment.