Ethics and Governance in the Age of Generative AI
Explore ethical challenges and governance strategies for responsible AI development and deployment. with a specific focus on generative AI
Explore ethical challenges and governance strategies for responsible AI development and deployment. with a specific focus on generative AI
This course delves into the ethical and technical dimensions of developing and deploying AI models, with a specific focus on generative AI. It examines the ethical and societal considerations of emerging technologies, exploring the unique challenges posed by generative AI. The curriculum covers the mechanics of generative AI, technical strategies for bias reduction, and the interplay between responsible AI (RAI) principles and the generative AI lifecycle. Students will learn about bias and fairness metrics at each stage of AI development, and navigate the landscape of RAI strategy and governance specific to generative AI. By the end of the course, participants will have a nuanced understanding of the ethical and technical intricacies shaping the development and deployment of AI models, particularly generative AI, and be equipped to critically evaluate the impact of these technologies on society.
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What you'll learn
Critically evaluate the ethical dimensions of emerging technologies and their impact on society
Understand the history, benefits, and potential misuses of generative AI
Grasp the technical foundations of generative AI, including neural networks and deep learning models
Apply Responsible AI (RAI) principles to generative AI development and deployment
Evaluate and mitigate bias in AI models using various metrics and benchmarks
Design and implement RAI workflows in the AI development lifecycle
Skills you'll gain
This course includes:
1 Hours PreRecorded video
24 assignments
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FullTime access
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There are 6 modules in this course
This course provides a comprehensive exploration of ethics and governance in the age of generative AI. It begins by examining the ethical dimensions of emerging technologies, with a focus on the unique challenges posed by generative AI. Students will learn about the recent history and evolution of generative AI, its benefits, uses, and potential misuses. The course then delves into the technical foundations of generative AI, covering neural networks and deep learning models. A significant portion of the curriculum is dedicated to Responsible AI (RAI) principles and their application to generative AI, including bias and fairness metrics, RAI workflows, and strategies for integrating RAI into the AI development lifecycle. The course concludes with a module on RAI strategy and governance, preparing students to implement ethical frameworks in real-world AI development and deployment scenarios.
Ethics of Emerging Technologies
Module 1 · 4 Hours to complete
Generative AI: An Emerging Challenge
Module 2 · 3 Hours to complete
How Does Generative AI Work?
Module 3 · 3 Hours to complete
RAI & Generative AI Bias & Fairness Metrics
Module 4 · 4 Hours to complete
RAI & Generative AI: Workflows
Module 5 · 7 Hours to complete
RAI Strategy & Governance
Module 6 · 2 Hours to complete
Fee Structure
Payment options
Financial Aid
Instructor
Director of Responsible AI Practice
Dr. Cansu Canca, Director of Responsible AI Practice at the Institute for Experiential AI and a Research Associate Professor at Northeastern University's Department of Philosophy and Religion, specializes in applied ethics with a focus on artificial intelligence. As the founder of AI Ethics Lab, she developed the Puzzle-solving in Ethics (PiE) Model to integrate ethical considerations into AI innovation, which underpins the EAI's Responsible AI framework. Her consultancy work includes collaborations with the United Nations Centre for AI & Robotics and INTERPOL, where she helps create guidelines for responsible AI in law enforcement. Dr. Canca actively participates in various ethics advisory and editorial boards, including the World Economic Forum’s AI Governance Alliance, and is the founding editor of AI & Ethics (Springer Nature). With a background in bioethics, she has held positions at prestigious institutions such as Harvard and the World Health Organization. Recognized as one of Boston's 30 Influential Women Advancing AI and among the 100 Brilliant Women in AI Ethics, Dr. Canca continues to lead discussions on AI ethics globally.
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