New Jersey Department of Education

Artificial Intelligence (AI)

Artificial intelligence, or AI, is expected to have a transformative impact on the future of education globally. Educators and students will require enhanced skills to identify and navigate the use of these AI systems. Educators need to prepare students for changing workplaces, including teaching them how to use emerging technologies.

This webpage provides an overview of foundational AI terms and concepts, high-level discussion questions regarding AI in education to consider at the Local Education Agency (LEA) leadership and classroom educator levels, resources to learn more about AI, resources for educators to teach their students about AI, as well as links to further research and reports regarding AI. 

Foundational AI Terms and Concepts

Term/Concept Definition Example
Artificial Intelligence Artificial Intelligence, or AI, refers to the development of computer systems that can perform tasks that typically require human intelligence, such as recognizing patterns, making decisions, and learning from experience. Examples of AI include facial recognition, autonomous vehicles, text prediction, digital voice assistants, and many other applications.
Machine Learning Machine learning is a type of artificial intelligence that involves training algorithms to make predictions or decisions based on data. Examples of AI systems that use machine learning are facial recognition, product and entertainment recommendations, email spam filtering, and predictive text.
Deep Learning Deep learning is a subset of machine learning that involves training multiple layers of interconnected nodes in an artificial neural network on large datasets to identify complex patterns and relationships in the data. Examples of AI systems that use deep learning are self-driving cars, medical diagnosis applications, chatbots, and customer service bots.
Data and Training Data Within the context of AI, “data” are units of information about people or objects that are used by AI systems. “Training data” refers to large amounts of data that has been labeled/coded and is used to teach AI models or machine learning algorithms to make the most appropriate decisions to the best of its abilities. In an AI system for a self-driving car, the training data will include images and videos labeled to identify cars versus street signs versus people.
Generative AI A type of narrow or weak AI that can generate new content, such as text or images, in response to a prompt. Examples of generative AI systems include AI chatbots such as OpenAI’s ChatGPT and Google’s Gemini, Github’s programming AI system Copilot, and art creator Midjourney.


AI System Classifications

Classification Definition Example
Weak or Narrow AI AI systems that are designed to perform specific tasks or solve specific problems, rather than having a broad range of intelligence. Examples of weak or narrow AI systems include digital voice assistants, predictive analytics, chatbots, and delivery bots.
Strong or General AI Strong AI, also known as artificial general intelligence (AGI) or general AI, is a type of theoretical AI system that would have intelligence and decision-making skills equal to humans. It would have a self-aware consciousness that could solve problems, learn, plan, and adapt independently. There are currently no AI systems that can match human intelligence, but there are some instances of Strong AI systems in the form of research projects or hypothetical scenarios.



  • TeachAI Webpage
    The TeachAI initiative, of which the New Jersey Department of Education is a participant, provides best practice guidelines for policymakers, education leaders, classroom educators, parents, and companies offering valuable insights on incorporating AI in primary and secondary education curriculum standards, courses, tools, assessments, and professional learning.
  •'s "How AI Works" Resources
    This page provides a series of short videos and accompanying in-classroom lessons that introduce students to how artificial intelligence works and why it matters.
  •  International Society for Technology in Education (ISTE)'s AI Exploration for Educators
    This page includes links to The Hands-On AI Projects for the Classroom guides from ISTE and General Motors that provide elementary, secondary, elective and computer science teachers with innovative curricular resources about AI across various grade levels and subject areas.
  • MIT Responsible AI for Social Empowerment (MIT RAISE) AI Literacy Units
    Massachusetts Institute of Technology's RAISE initiative developed a wide range of learning units for K-12 AI Literacy. 
  • Stanford Graduate School of Education's Classroom-Ready Resources About AI for Teaching (CRAFT)
    CRAFT is a collection of co-designed free AI Literacy resources about AI for high school teachers, to help students explore, understand, question, and critique AI. CRAFT intentionally pursues a multidisciplinary approach so educators with a variety of discipline backgrounds can teach about AI.
  • Google's Quick Draw Application and Quick Draw Dataset Explorer
    An application that recognizes your drawings using AI. Quick Draw also provides the full datasets used by the AI algorithm, which is a powerful example of how training data is used for AI systems. These datasets can also be explored.
  • Google's Teachable Machine
    Use the camera or microphone on your device to train a machine through AI to see or hear something and predict what it is. This is a good application to use as an introduction to machine learning.
  • Stable Diffusion
    A text-to-image generator that creates photo-realistic images given any text prompt. Review Stable Diffusion’s prompts search engine to explore millions of AI-generated images created with individual and unique prompts.
  • OpenAI's ChatGPT 3.5
    A chatbot that generates text in response to user-created prompts in a conversational format. The free version, 3.5, can be accessed with registration. This version is only trained on data from up to 2021.


The resources provided on this webpage are for informational purposes only. All resources must meet the New Jersey Department of Education’s (NJDOE) accessibility guidelines. Currently, the NJDOE aims to conform to Level AA of the Web Content Accessibility Guidelines (WCAG 2.1). However, the NJDOE does not guarantee that linked external sites conform to Level AA of the WCAG 2.1. Neither the Department of Education nor its officers, employees or agents specifically endorse, recommend or favor these resources or the organizations that created them. Please note that the Department of Education has not reviewed or approved the materials related to the programs.

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