Ethical-Frameworks-in-AI-Navigating-the-Moral-Landscape.pptx

Ethical frameworks for AI. Includes its types and also a case study on Bioethical framework

1. Ethical Frameworks in AI: Navigating the Moral Landscape This presentation explores ethical frameworks in AI. It provides a roadmap for navigating the moral landscape. We will examine key principles, challenges, and real-world applications. by Suketha Prabhu

2. Defining AI Ethics: Key Principles and Challenges Key Principles Fairness and non-discrimination Transparency and explainability Accountability and responsibility Challenges Bias in data and algorithms Lack of clear regulatory frameworks Ethical dilemmas in autonomous systems

3. Why Ethical Frameworks for AI? 1 Mitigating Risks Preventing unintended consequences and biases. 2 Building Trust Enhancing public confidence in AI systems. 3 Guiding Development Providing ethical guidelines for AI innovation.

4. Deontology: Rules, Rights, and Responsibilities Moral Duties Focus on adherence to moral rules. Human Rights Protecting fundamental human rights in AI. Responsibilities Defining responsibilities of AI developers.

5. Types of Ethical Frameworks Sector-Based Specific to industries like healthcare and finance. Value-Based Centered on core values such as fairness and transparency.

6. Sector-Based Frameworks Healthcare Patient privacy and data security. Finance Algorithmic trading and loan decisions. Transportation Autonomous vehicles and safety standards.

7. Value-Based Frameworks Fairness Ensuring equitable outcomes and non-discrimination. Transparency Making AI systems understandable and explainable. Accountability Establishing responsibility for AI decisions.

8. Value-Based Classification Rights-Based 1 Utility-Based 2 Virtue-Based 3

9. Detailed Study of Value-Based Approaches 1 Rights-Based Protecting individual rights and freedoms. 2 Utility-Based Maximizing overall well-being and happiness. 3 Virtue-Based Cultivating virtuous character traits in AI.

10. Case Studies & Discussion 1 Bias Detection Identifying and mitigating bias in facial recognition systems. 2 Autonomous Vehicles Ethical decision-making in accident scenarios. 3 AI in Hiring Ensuring fairness in AI-driven recruitment processes.