AI - AI ethics - course launch - ethical ai - ethics of artificial intelligence

Ethical AI course launch: learn to approach and apply ethical AI.

Artificial intelligence (AI) is an emerging technology that touches all of us in one way or another. From self-driving cars to Netflix show recommendations, we all interact with AI on a daily basis. The impact that AI will make on the world is only growing bigger. In fact, the AI market is expected to grow at an extremely fast rate, at least 120% each year!

With new technology, especially something that touches so much of our everyday lives, it’s important to consider it from an ethical perspective. This is why Udacity is excited to introduce the newest addition to our School of Artificial Intelligence: the Ethical AI course.

What is ethical artificial intelligence?

Artificial intelligence is a developed computer system that can make decisions like a human can. They take in data — visual data, audio, or other input — and make an intelligent choice. When it comes to AI, the ethical implications have vast consequences. It might not matter so much if there is bias in your Spotify song recommendation algorithm, but when it comes to self-driving cars, a small bit of bias can mean life or death to a passenger or pedestrian.

The people who specialize in ethical AI, have to ask difficult questions, like “Is this an acceptable use of AI?” and “How much power should this AI have?” Additionally, people who work in ethical AI have to examine current AI frameworks and models to determine if there is bias. Everything from the data scientist who collected the data to the environment the AI was run in can introduce bias. It’s the job of someone in ethical AI to find that bias and correct it.

With dedicated people working exclusively in the ethics of artificial intelligence, we can try to get ahead of challenging ethical scenarios that AI might introduce. The field of ethics within AI is still new to the scene, and there are far too few people with the needed skills in AI ethics.

Ethical AI course details.

The Ethical AI Course will prepare students to articulate ethical AI concepts and their associated urgency, importance, and risk. Graduates will be able to apply ethical AI concepts at an organizational level, as well as identify and evaluate bias in AI workflows. This knowledge can be used by graduates of the Ethical AI Course to limit bias and build AI models for enhanced fairness.

Ethical AI course prerequisites & requirements.

To get the most out of this course, there are a few prerequisites, as well as hardware and software requirements. Anyone looking to enroll in the Ethical AI Course should be able to:

  • Identify and articulate popular use cases of AI systems in society, such as autonomous vehicles and smart voice assistants
  • Create a machine learning model (linear or logistic regression model, naive Bayes classifier, or neural network using the scikit-learn framework)
  • Perform basic data parsing and visualization activities 
  • Use pandas data frames and visualization libraries, such as matplotlib
  • Know how to code with Python 3.7.6 or higher
  • Understand fundamental concepts of AI lifecycle phases, as well as the inputs and outputs of a typical AI system

In order to run demo material and projects locally, students must use a computer running a 64-bit operating system with at least 8GB of RAM. Additionally, it is necessary to have administrator account permissions sufficient to install programs on the computer, including Anaconda with Python 3.7 or higher, as well as supporting packages. Most modern Windows, OS X, and Linux computers should meet this requirement.

Ethical AI course & project.

In as little as 1 month (at around 5 hours a week), students who enroll in the Ethical AI Course will learn how to utilize artificial intelligence in an ethical way. From an organizational perspective, students will learn about the impact of bias and fairness on decision-making with AI, including how to identify biases and harms from AI solutions. Students will also learn how to identify and measure AI bias and fairness, and implement mitigation strategies to improve fairness in AI models and solutions.

At the end of the Ethical AI course, students will complete a project titled “AI Ethics for Budget Prediction.” Students will design an AI model for budget prediction and apply ethical AI considerations. After the first phase of the project, students will conduct harm quantification by measuring bias and fairness. Students will then apply bias mitigation skills to remediate harm, then construct a model card that articulates the ethical implications, quantitative analysis, and business consequences of the use case.

Learn from top AI experts.

To develop this program’s world-class curriculum, we collaborated with professionals from top-rated tech companies, like Intel. This collaborator contributed guidance and feedback to focus the program on the most in-demand skills. The instructor has extensive experience in AI architecture, ethics in AI, and teaching. 

Ria Cheruvu, AI Ethics Lead Architect at Intel

In addition to working as Intel NEX AI Ethics Lead Architect, Ria is an emerging industry speaker who holds a master’s degree in data science from Harvard University. Previously, she was a Teaching Fellow for Harvard’s 2021 Data Science graduate curriculum and a Lead Instructor for Eduonix’s ML Deployment course.

Enroll in the Ethical AI course today.

If you’re an engineer or product manager specializing in machine learning or artificial intelligence, this is the perfect course for you. You will be able to build on top of your AI/ML understanding to add a critical ethical component to your skillset.

Learn how to approach and apply ethical AI across disciplines. Register for the Ethical AI course today.


Jennifer Shalamanov
Jennifer Shalamanov
Jennifer is a content writer at Udacity with over 10 years of content creation and marketing communications experience in the tech, e-commerce and online learning spaces. When she’s not working to inform, engage and inspire readers, she’s probably drinking too many lattes and scouring fashion blogs.