Building Responsible | Ethical AI Systems-Risk of GEN AI

Course Overview:

This course provides an in-depth exploration of Artificial Intelligence (AI), fostering a critical understanding of both its transformative potential and associated ethical risks. It emphasizes responsible AI development while preparing participants to engage with AI technologies in a thoughtful and informed manner.

Course Objectives:

• Acquire a solid foundation in Artificial Intelligence (AI) concepts and real-world applications.

• Explore the capabilities of large language models (LLMs) such as ChatGPT and Google Gemini, gaining insights into their functionalities and inherent limitations.

• Identify and critically evaluate the risks associated with AI, including bias, security vulnerabilities, and societal implications.

• Develop a comprehensive framework for implementing responsible AI practices, with a strong emphasis on ethical considerations and mitigation strategies.

• Learn how to connect with an API to evaluate and test for toxicity using ResponsibleAI tools, ensuring that AI systems meet ethical and safety standards.

Course Content:

Introduction to AI:

• Demystifying foundational AI concepts, including machine learning, deep learning, and natural language processing.

• Understanding AI’s pervasive influence across industries and sectors.

Unveiling Large Language Models (LLMs):

• Exploring the functionalities of LLMs such as ChatGPT and Google Gemini, focusing on their applications in text generation, translation, and code creation.

• Discussing the limitations and challenges of LLMs, particularly in specialized or nuanced contexts.

Navigating AI Risks:

• Identifying potential biases embedded within AI algorithms and understanding their broader downstream impacts.

• Examining security vulnerabilities, data privacy concerns, and ethical challenges in AI deployments.

• Analyzing the societal implications of AI, including labor market disruption and ethical dilemmas in decision-making.

Building Responsible AI:

• Exploring strategies to mitigate AI risks and promote fairness, transparency, and accountability in AI systems.

• Learning how to test AI systems for toxicity using ResponsibleAI's API, with a focus on ensuring ethical AI usage and minimizing harmful outputs.

Target Audience:

This course is designed for:

• Individuals with a general interest in the potential and challenges of AI.

• Professionals seeking to deepen their understanding of the ethical risks surrounding AI development and deployment.

• Developers and programmers interested in integrating responsible AI practices, particularly in addressing toxicity and bias in AI models.

Learning Outcomes:

By the end of this course, participants will have the skills and knowledge to navigate the evolving landscape of AI responsibly. They will also be equipped to test AI models for toxicity through APIs, ensuring ethical and responsible AI deployment.