STEAM in AI is a transformative Data + AI Ethics Intensive that helps High School Students learn fundamentals of Data and AI Ethics, stand out in College Applications through experiential storytelling and prepare for Jobs of the Future
Developed by former Stanford and UC Berkeley Adjunct Professor, MIT Mentor $100K Entrepreneurship Competition, Data and AI Ethics thought leader from Silicon Valley who is invited to speak about the Ethics of Generative AI to audiences such as the U.S. Department of Defense and the California Department of Education.
STEAM in AI provides College Prep, Data Science, Data Analytics, Research, AI model building, Career Mentoring and Experiential Learning to High School Students with a strong foundation of Data + AI Ethics!!
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Hear from STEAM in AI Graduates
Through STEAM in AI, I got to explore the fundamentals of software engineering. It helped me learn about different areas of coding, such as learning about AI, data sciences, and machine learning. This taught me what I could expect in the future.
I was originally thinking about pursuing mechanical or electrical engineering but now I’m interested in computer sciences.
Chloe Feng, Rising High School Senior
How do you think the STEAM in AI College Prep Program helped you in your Path to College?
It showed me different ethical ways to use AI and opening up my eyes to different potential issues and code wise it opened a lot of paths for to learn and explore. My interest in careers was already computer science, STEAM in AI Data + AI Ethics Intensive enforced it though.
Alexa Torres, STEAM in AI Data + AI Ethics Intensive Graduate
STEAM in AI Student Projects
Project 1: Social Media Sentiment & Image Analysis for Improving Professional Outlooks
The main goal of this project was to develop an AI-based tool that teenagers and young adults could use to analyze how potential employers would view their social media activity and to improve their professional outlook by highlighting problematic posts.
Project 2: Analyzing Building Architecture with Computer Vision
The objective of the project was to apply Computer Vision Machine Learning tools in Artificial Intelligence to analyze and classify Buildings based on their architectural features.
Project 3: Building an AI Model for Depolarization
The objective of this project was to develop an AI model using LLM (Language and Learning Models) techniques to address depolarization. The model aimed to analyze and understand polarizing language patterns, detect potential sources of polarization, and suggest strategies for promoting dialogue and understanding.
Project 4: Building an ML Classification Model for Knee MRI to help doctors with diagnosis
The objective of this project was to build a Machine Learning Classification Model to predict if a Knee had an ACL or Meniscal Tear based on an MRI image. This model could be used for an app to give a second opinion to a doctor as they evaluate a patient's Knee MRI to help prevent misdiagnosing.
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Our Network of Mentors
Hear from one of our Mentors
STEAM in AI is a transformative Program, where students are empowered to explore the fascinating world of AI while emphasizing the critical aspect of ethics.
STEAM in AI believes in mentor-led experiential learning. This program connects middle, high school and college students with expert mentors who are either PhD students or professionals in the Data and AI industry. This unique opportunity ensures that students receive firsthand guidance from those who are actively shaping the field.
The duration of this Program developed by Shilpi Agarwal, Founder and CEO of DataEthics4All Foundation, former Stanford, UC Berkeley Faculty, MIT Mentor is 10 Weeks.
Students meet with their Mentor every week for 2 hours for a total of 20 hours in a small cohort.
Mentor to Student ratio per cohort is 1:5. The Program is 100% Virtual.
We have 3 Tracks to choose from: Fundamental, Master and Full-Immersion.
Students have an opportunity to learn the fundamentals of data science, basics of coding, ethical consideration in Data and Artificial Intelligence, build an AI Model and work on a group research paper depending upon the track they choose.
At the end of 10 Weeks, Students will have an opportunity to submit an AI Project on Github and have their name as a contributor to the Research Paper. They will also earn a Certificate of Completion.
U.S. Students may apply for a need-based Scholarship.
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Through STEAM in AI College Prep, Career Mentoring and Experiential Learning
Our Mission is to Raise the next generation of Ethics 1st Data and AI Champions
STEAM in AI is a Program brought by DataEthics4All Foundation
What is STEAM in AI?The traditional definition of STEAM means Science, Technology, Engineering, Arts and Math. DataEthics4All Foundation's definition of STEAM also includes Sociology, Technical Education, Ethics, Analytics and Mentoring! Today, there exist many new linear as well as non-linear STEAM career paths that we'd like our students to be aware of and be able to take advantage of by choosing a career in STEAM whether or not Math, Science or Coding are their biggest passions. AI is going to be used in every Industry in the future from healthcare to construction and everything in between. DataEthics4All Foundation believes that combining the traditional with this new definition of STEAM will bring the much needed STEAM in AIᵀᴹ!!
We've taken into consideration these 10 important pillars of Artificial Intelligence
When developing our STEAM in AI College Prep, Research and Build Experiential Learning Program
Science and TechnologyScience and Tech are the foundations of Artificial Intelligence. AI is built on mathematical models and algorithms that enable machines to learn and make decisions. It also requires a thorough understanding of the underlying scientific principles, such as data structures, computational statistics, and probability.
EngineeringEngineering is also vital in AI, as it involves designing and developing intelligent systems. Engineers are responsible for building the software and hardware infrastructure that supports AI, including the development of new AI-based applications.
ArtArt and design play a crucial role in AI as well. With the growing importance of human-computer interaction, it is essential to create user-friendly interfaces that people can easily understand and interact with. Art and design also help in creating visually appealing representations of data that can be understood by non-technical stakeholders.
MathematicsMathematics is at the core of AI, and many of the algorithms used in AI require advanced mathematical knowledge. Linear algebra, calculus, and probability theory are just some of the mathematical concepts that are essential in AI.
SociologySociology is the study of human behavior and social relationships, and it plays a vital role in AI. AI systems are designed to interact with people, and understanding human behavior and social relationships is critical in creating AI that is effective and meets the needs of users. By incorporating sociological principles in AI development, we can create systems that are more responsive to social and cultural contexts, making them more useful and acceptable to users.
Technical EducationTechnical education provides students with the knowledge and skills necessary to develop and implement AI systems. Technical education helps students understand the underlying principles and technologies that are essential in AI development, such as computer programming, data analysis, and machine learning. Technical education also helps students learn how to apply these principles in real-world situations, making them better equipped to solve real-world problems using AI.
EthicsEthics is critical in AI development because AI systems can have significant impacts on society. Ethical considerations, such as privacy, fairness, and accountability, need to be taken into account when developing and implementing AI systems. Incorporating ethics into AI development ensures that AI systems are developed responsibly and do not cause harm to individuals or society.
AnalyticsAnalytics involves the use of data analysis to gain insights into complex systems. Analytics is critical in AI development because it helps us understand patterns and trends in data, which is essential in developing effective AI systems. By analyzing data, we can develop algorithms and models that are more accurate and reliable, making AI systems more effective.
MentoringMentoring is essential in STEAM in AI because it provides students with the guidance and support they need to develop their skills and knowledge in AI. Mentors can provide students with insights into real-world applications of AI and help them develop practical skills that can be used in AI development. Mentoring also helps students develop critical thinking skills and learn how to work effectively in interdisciplinary teams, which is essential in AI development.
Integrating these 10 important Pillars is essential because it allows us to develop a holistic approach to AI development
Truly bringing the STEAM in AIBy incorporating these disciplines into AI development, we can create systems that are more effective, responsive to users' needs, and developed responsibly.
Register for Winter 2023
How to get started?Easy 4 Step Process
Apply to join as a Student
Get invited to an Interview
If you're a good fit for the Program, we'll invite you to complete the Registration.
We'll find the perfect Mentor and Cohort for you.