What you will learn?
Principles of AI Safety: Understand the core concepts and importance of safety in AI development, including reliability, robustness, and ethical considerations.
Risk Identification: Learn to identify and assess potential risks associated with AI systems, such as bias, security vulnerabilities, and unintended consequences.
Mitigation Strategies: Explore techniques and best practices for mitigating AI risks, including model validation, robustness testing, and bias correction.
Ethical and Social Implications: Examine the broader ethical and societal impacts of AI, including privacy concerns, fairness, and the implications of AI decision-making.
Adversarial Attacks: Gain insights into common adversarial threats and attacks on AI systems, and learn strategies to defend against them.
Regulatory and Compliance Issues: Understand current regulations and standards for AI safety, and learn how to ensure compliance with relevant guidelines and frameworks.
About this course
"AI Safety" is a specialized course focused on understanding and addressing the risks and challenges associated with artificial intelligence systems. This course explores the fundamental principles of AI safety, including strategies for ensuring robust and ethical AI development. Participants will examine potential safety concerns such as algorithmic bias, adversarial attacks, and the broader impact of AI on society. Through case studies, theoretical discussions, and practical exercises, learners will acquire the knowledge and skills necessary to design and implement safe and responsible AI systems.
Requirements
Prerequisites: Basic knowledge of AI and machine learning concepts is recommended, though not required. Familiarity with programming and statistics can be helpful.
Materials Needed: A computer with internet access and access to online course materials. Specific tools or software required for practical exercises will be detailed at the start of the course.
Software Requirements: Participants should have a web browser and may need to install specific tools or libraries for hands-on activities, with guidance provided as necessary.
Course Structure: The course includes lectures, case studies, and practical exercises designed to apply AI safety concepts. Active participation and engagement in discussions and activities are essential.
Assignments: Regular assignments and projects will focus on identifying and mitigating AI risks, with feedback provided to support learning and practical application of safety principles.
