Education
Our Vision
Educational outreach activities play a crucial role in maximizing the impact of AI teaching and trustworthy AI. These activities aim to extend the reach of these programs beyond their immediate participants and engage a wider audience.
Our capacity building initiative for TAIMS (Trustworthy AI in Medical Systems) is focused on expanding involvement and engaging a wide range of participants—including women, educators, and students at the K–12 level—in the fields of AI and machine learning. To this effort, Vibhuti Gupta, Ph.D., and his student Destiny Pounds developed nine-lesson trustworthy AI teaching modules that introduces educators to different aspects of trustworthy AI with detailed explanations, examples and hands-on exercises.
About the Teaching Modules
We developed nine modules that include detailed explanations, examples and hands-on exercises. Each module includes a:
- Pre-recorded video,
- A PDF of the slide deck from that video, and,
- A use-case slice that demonstrates the real-world application of the concept learned and a scenario question to think the solution based on your learnings.
A transitional video helps reinforce key concepts before moving on to the next module. Some hands-on modules require prior programming experience, ideally in Python, while others only involve using tools to evaluate and improve the quality and fairness of datasets.
Please review the Trustworthy AI Modules for K-12 Educators Manual for helpful instructions before staring the modules.
Hands-On Exercises
You can also try the optional exercises at the links below. These exercises are related to the content in Module 3, so we recommend having at least completed that module. Available on Google Collab, you can do a walkthrough of the notebooks and see a demonstration of the concepts covered in Module 3.
Aggregated slides of modules and use cases
If you prefer, you can also access PDFS with all of the module slides and use-cases at these links.
An introduction to the Trustworthy AI Teaching Modules
Module 1: Intro to Ethical and Trustworthy AI
Module 2: Trustworthy AI: Ethics
Module 3: Trustworthy AI: Fairness
Module 4: Trustworthy AI: Privacy
Module 5: Trustworthy AI: Security
Module 6: Trustworthy AI: Robustness
Module 6 to 7 Transitional Video
Module 7: Trustworthy AI: Safety
Module 8: Trustworthy AI: Explainability
Module 9: Trustworthy AI: Accountability
Trustworthy AI Conclusion Module
Please complete this brief survey after finishing all modules.
Educational initiatives
Educational outreach activities play a crucial role in maximizing the impact of AI teaching and trustworthy AI. These activities aim to extend the reach of these programs beyond their immediate participants and engage a wider audience.
Multiple education and outreach activities will be organized as part of capacity building in trustworthy AI in medical systems. Educational activities consist of seminar series on trustworthy AI in medical systems and developing a new course on trustworthy AI for the biomedical data science and data science Ph.D. programs.
Outreach activities include trustworthy AI teaching modules for high school educators and summer academies for K-12 students.
AI in Education: Benefits, Risks and Best Practices
Session One
Vibhuti Gupta, Ph.D.
Assistant Professor, Computer Science and Data Science
Meharry School of Applied Computational Science
Dr. Gupta provides an overview of AI in education, covering its benefits and risks, and provides a hands-on demo of AI tools.
Session Two
Vibhuti Gupta, Ph.D.
Assistant Professor, Computer Science and Data Science
Meharry School of Applied Computational Science
Dr. Gupta provides an overview of AI in education. He covers its benefits and risks, prompt engineering, and provides a hands-on demo of AI tools.