AI Terminology & Definitions

Terminology

• Application Programming Interfaces (APIs)
  Mechanisms that enable two software components to communicate with each other using a set of definitions and protocols. (APIs are useful shortcuts to tasks you can often replicate using longer and careful prompting.)

• Artificial Intelligence (AI)
  Artificial intelligence (AI) is the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.

• Chatbot
  A program that communicates with humans through text that simulates human language. (CNET, 8/28/23)

• Generative AI (GenAI)
  Generative AI is the branch of AI that enables machines to learn patterns from vast datasets and then to autonomously produce new content based on those patterns. (IEEE Spectrum, 2/14/24)

• Generative Pretrained Transformer (GPT)
  GPT models allow applications to create human-like text and content (images, music, and more), and answer questions in a conversational manner. 

• Hallucination
  An incorrect response from AI. Can include generative AI producing answers that are incorrect but stated with confidence as if correct. The reasons for this aren't entirely known. (CNET, 8/28/23)

• Large Language Model (LLM)
  A large language model (LLM) is a deep learning algorithm that can recognize, summarize, translate, predict and generate text and other forms of content based on knowledge gained from massive datasets.

• Natural Language Processing (NLP)
  Natural language processing (NLP) refers to the branch of computer science—and more specifically, the branch of artificial intelligence or AI—concerned with giving computers the ability to understand text and spoken words in much the same way human beings can.

• Prompt
  The suggestion or question you enter into an AI chatbot to get a response. (CNET, 8/28/23)

• Prompt chaining
  The ability of AI to use information from previous interactions to color future responses. (CNET, 8/28/23)

• Structured Prompting
  A way to turn AI into a tool that does a single task well in a way that is repeatable and adapts to its user. (Ethan Mollick, 11/1/23).

Resources

Understanding AI Literacy. (n.d.). Teaching Commons. Stanford University. This module introduces a framework that identifies and organizes skills and knowledge that you can use to navigate the challenges and opportunities of generative AI technology in education in more thoughtful ways. After completing this module, you should be able to:

• Describe the skills and knowledge within each of the four domains of this framework

• Apply the AI literacy framework to a real-life educational context

• Identify and commit to actions that can improve your or students’ AI literacy