AI / Machine Learning
In today's world of automation and a society that almost literally cannot function without technology, Artificial Intelligence and Machine Learning (AI/ML) have become part of everyone's lives. From Netflix and Youtube, to e-commerce platforms like Amazon and Walmart, AI/ML is everywhere. Educate yourself or leverage our course curriculum to teach others.
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AI/Machine Learning Support
Future of Work Initiative has created a curriculum that can be adapted for your classroom. We start with a one-time workshop where are staff gets your class going, then you use the curriculum to continue. This is a project-based learning program that engages students in learning how Artificial Intelligence and Machine Learning (AI/ML) influences their everyday lives and impacts the future for them as students, professionals, customers, and civilians. Students will also be introduced to the ethical dilemmas and biases of machine learning. They will gain insight into how the improper use of AI/ML affects the most vulnerable and marginalized groups in our society.
This curriculum can be designed for all age groups. Teachers can incorporate this platform into their current curricula.
How does AI differ from Machine Learning?
AI is a broad concept to create intelligent machines that can simulate human thinking capability and behavior, whereas, machine learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly.
What is Machine Learning?
Machine learning is a system where rather than a computer programmer deciding the best way to sort, organize, classify or use information – a computer program develops its own set of instructions based on information that users feed it.
How does facial recognition work?
Facial recognition can identify people by measuring dozens of distinguishable features on the face. The software reads the geometry, creates a "faceprint," compares it with those on a watchlist, and finally a computer ranks the likely matches.
Are machine learning algorithms bias?
Image recognition systems that use biased machine learning data sets will inadvertantly magnify that bias. Researchers are examining ways to reduce the effects.