Understand why AI ethics is critical in modern technology and business. -Explore ethical dilemmas in AI development and deployment. -Learn key ethical principles: fairness, accountability, transparency, and explainability. -Discuss real-world ethical failures in AI and their consequences.
1-Introduction to AI Ethics and Responsible AI
Understand why AI ethics is critical in modern technology and business.
-Explore ethical dilemmas in AI development and deployment.
-Learn key ethical principles: fairness, accountability, transparency, and explainability.
-Discuss real-world ethical failures in AI and their consequences.
0/1
2-Privacy and Data Protection in AI Systems
-Understand the impact of AI on personal privacy and data security.
-Explore legal frameworks such as GDPR and AI-related data regulations.
-Learn how AI processes and stores personal information.
-Develop strategies for ensuring ethical data collection and usage.
0/1
3-AI Bias and Fairness
-Learn how bias enters AI models and its impact on decision-making.
-Explore techniques for detecting and mitigating bias in AI algorithms.
-Understand the societal consequences of biased AI systems.
-Discuss best practices for promoting fairness in AI applications.
AI and their consequences.
Privacy and Data Protection in AI Systems
Understand the impact of AI on personal privacy and data security.
Explore legal frameworks such as GDPR and AI-related data regulations.
Learn how AI processes and stores personal information.
Develop strategies for ensuring ethical data collection and usage.
AI Bias and Fairness
Learn how bias enters AI models and its impact on decision-making.
Explore techniques for detecting and mitigating bias in AI algorithms.
Understand the societal consequences of biased AI systems.
Discuss best practices for promoting fairness in AI applications.
0/1
4-Transparency and Explainability in AI
-Understand the importance of AI transparency for trust and adoption.
-Learn techniques for making AI decision-making explainable to users.
-Explore challenges in building interpretable AI models.
-Discuss strategies for improving AI transparency in business applications.
0/1
5-Accountability and Governance in AI
-Learn who is responsible for AI-related decisions and their consequences.
-Explore the role of AI ethics committees and governance frameworks.
-Understand ethical considerations in AI automation and human oversight.
-Develop strategies for ensuring corporate and regulatory accountability in AI use.
0/1
6-Implementing Ethical AI Practices in Organizations
-Explore frameworks for integrating ethical principles into AI development.
-Learn how to balance innovation with ethical constraints.
-Develop guidelines for responsible AI deployment in business environments.
-Create an AI ethics action plan tailored to organizational needs
0/1