Responsible AI Algorithm Design
2h 26mIntermediate2024-10-18
Authors
Isil Berkun
Data Scientist at Intel Corp.
Course details
As AI technologies advance rapidly, embedding ethical practices into AI design practices is not just a necessity but an imperative to prevent biases and ensure trust in AI. This course equips you with the skills required to create systems that are ethically aligned, fair, and transparent, preventing biases and fostering trust in AI technology. Join instructor Isil Berkun as she shows you what it takes to master the ethical principles necessary to build and deploy AI systems responsibly. Along the way, discover critical topics such as bias mitigation, transparency, and privacy, culminating in hands-on challenges that translate ethical concepts into actionable AI development practices.
Learning objectives
Understand the fundamental importance of responsible AI in the development process.
Mitigate the risks associated with AI deployment.
Explore how AI governance and global policy shapes responsible AI practices.
Discover best practices and strategies for effective AI policy implementation for AI projects.
Build technical skills for designing AI systems alongside ethical considerations.
Learn methods and design features for enhancing transparency and accountability of AI systems.
Examine real-world examples of AI and apply the principles and methods for integrating human-centric design into AI development in a hands-on project.
Integrate ethical considerations into AI development, ensuring fairness, transparency, and accountability, with a focus on theoretical frameworks and ethical guidelines rather than specific software tools.
Learning objectives
Understand the fundamental importance of responsible AI in the development process.
Mitigate the risks associated with AI deployment.
Explore how AI governance and global policy shapes responsible AI practices.
Discover best practices and strategies for effective AI policy implementation for AI projects.
Build technical skills for designing AI systems alongside ethical considerations.
Learn methods and design features for enhancing transparency and accountability of AI systems.
Examine real-world examples of AI and apply the principles and methods for integrating human-centric design into AI development in a hands-on project.
Integrate ethical considerations into AI development, ensuring fairness, transparency, and accountability, with a focus on theoretical frameworks and ethical guidelines rather than specific software tools.
Skills covered
Responsible AIArtificial Intelligence (AI)One-Off
Concepts
0. Introduction
- 01 - Welcome to responsible AI
- 02 - What to expect from this course
- 03 - Going over Codespaces
1. Introduction to Responsible AI
- 04 - Defining responsible AI
- 05 - The pillars of responsible AI
- 06 - Challenge - Ethical dilemma analysis
- 07 - Solution - Frameworks for ethical decision-making in AI
2. Risk and Regulation in AI
- 08 - Risks in AI deployment
- 09 - AI governance and policy
- 10 - Challenge - AI policy implementation plan
- 11 - Solution - AI policy implementation best practices
3. Designing Ethical AI Systems
- 12 - Technical foundations for ethical AI
- 13 - Creating transparent and accountable AI
- 14 - Challenge - Design a transparent AI feature
- 15 - Solution - Techniques for building transparent AI
4. Best Practices for Responsible AI
- 16 - Building ethical AI with a human-centric approach
- 17 - AI that works for humanity
- 18 - Challenge - Human-centric AI design exercise
- 19 - Solution - Integrating human-centric design in AI
Conclusion
- 20 - Next steps