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Ethics and Governance in the Age of Generative AI

Offered By: Northeastern University via Coursera

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Generative AI Courses Artificial Intelligence Courses Deep Learning Courses Neural Networks Courses Ethics Courses Responsible AI Courses Fairness in AI Courses AI Governance Courses

Course Description

Overview

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This course is best suited for individuals who are looking to expand their understanding of generative AI and best practices for the responsible, ethical incorporation of generative AI tools in the flow of work. This course explores the ethical and technical dimensions of developing and deploying AI models with a focused lens on generative AI. It examines the ethical and societal considerations of emerging technologies and unique challenges posed by generative AI. This course details the mechanics of genAI, and technical strategies to reduce bias. It explores the RAI principles, strategy, and governance surrounding generative AI. By the end of this course you will have a developed understanding of the nuances of the ethical and technical intricacies shaping the development and deployment of AI models, with a particular focus on generative AI.

Syllabus

  • Ethics of Emerging Technologies
    • Welcome to your course, Ethics and Governance in the Age of Generative AI. You will begin by exploring the ethical and technical dimensions of developing and deploying AI models, with a focused lens on generative AI. Next, you will move into the ethical and societal considerations of emerging technologies, where you will reflect on the unique ethical challenges posed by generative AI. Transitioning next into the mechanics of genAI, you will uncover its workings and explore technical strategies for bias reduction. From there, you will examine the interplay between responsible AI (RAI) principles and the genAI lifecycle, scrutinizing bias and fairness metrics at each stage. Lastly, you will navigate the landscape of RAI strategy and governance specific to generative AI. By the end of your time in this course, you will have developed an understanding of the nuances of the ethical and technical intricacies shaping the development and deployment of AI models, with a particular focus on generative AI.
  • Generative AI: An Emerging Challenge
    • In this module, you will begin exploring a specific type of artificial intelligence - generative AI. You will explore the recent history and evolution of generative AI - where it began to where it is currently in society. You will learn about the benefits, uses, and the misuses of this type of AI technology. As you learn about generative AI keep in mind what you have learned thus far about emerging technologies and ethical considerations for adoption.
  • How Does Generative AI Work?
    • In this module you will explore the basic technical foundations of generative AI and how it differs from predictive AI models. You will learn about neural networks and deep learning models which will then prepare you to develop a grasp on how generative AI works from a technical perspective. Once you have this foundational knowledge, you will then reflect on the current state of AI, how it is being used in industry, and potential challenges associated with this technology.
  • RAI & Generative AI Bias & Fairness Metrics
    • This module begins our exploration of RAI and generative AI, beginning first with learning about the scope of RAI and how it applies specifically to generative AI. Next, you will explore the metrics and benchmarking used to evaluate training data. This module focuses on bias within data and algorithmic fairness. By the end of your time in this module, you will be able to list and understand various other metrics used to evaluate the quality of generative AI models and assess the fairness and ethical considerations of each.
  • RAI & Generative AI: Workflows
    • So far you have learned about what generative AI is and some of the fairness issues that you might encounter, as well as metrics you can use to evaluate your models. In this module we’ll talk about the actual model development lifecycle and how responsible AI practices might fit into it. You will explore different benchmarks and assessment tools and examine different RAI workflows. By the end of this module, you will have a better understanding about the development lifecycle and how to approach design more responsibly.
  • RAI Strategy & Governance
    • In this module you will be introduced to emerging technologies and the impact they have on technological change in society. You will be introduced to the ethics of these technologies and reflect on the myths and misconceptions surrounding them as well as the limitations to the development of these technologies.

Taught by

Cansu Canca

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