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.
What you'll learn
Critically evaluate the ethical dimensions of emerging technologies and their impact on society
Skills you'll gain
Details to know
Add to your LinkedIn profile
September 2024
24 assignments
See how employees at top companies are mastering in-demand skills
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 6 modules in this course
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.
What's included
6 videos4 readings5 assignments2 discussion prompts
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.
What's included
3 videos7 readings4 assignments1 discussion prompt
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.
What's included
5 videos3 readings5 assignments1 discussion prompt
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.
What's included
5 videos4 readings4 assignments1 discussion prompt
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.
What's included
3 videos3 readings3 assignments1 peer review
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.
What's included
2 videos3 readings3 assignments1 discussion prompt
Instructor
Offered by
Recommended if you're interested in Machine Learning
University of Virginia Darden School Foundation
Why people choose Coursera for their career
New to Machine Learning? Start here.
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.