AI in Academia: What is AI?

Welcome

AI is here, and it's not going away. This guide was created by librarians at SUNY Schenectady to help our community explore the use of artificial intelligence (AI) in teaching, learning, and research. Whether you're new to AI or looking to deepen your understanding, you'll find resources to:  

• Learn what AI is, and how it works.
• Discover AI tools that can enhance your productivity and creativity.
• Explore ethical considerations for using AI responsibly.  
• Stay updated on the latest developments in AI for education and research.  

Since AI is a rapidly developing field, expect regular updates to this guide.

AI Vocabulary

AI Agent:  
An AI agent is a computer program or system designed to perform tasks autonomously by perceiving its environment, processing information, and taking actions to achieve specific goals. It uses artificial intelligence techniques to make decisions or perform actions based on the data it receives. AI agents can execute commands and control devices.

Algorithm:
A set of rules or instructions the AI follows to solve problems.  

Artificial Intelligence (AI):
Machines or systems that mimic human intelligence to perform tasks like learning, problem-solving, and decision-making.

Bias:
Systematic errors in AI outcomes caused by biased training data or flawed algorithms.  

Chatbot:
A program designed to simulate conversation with users, often for customer service or information retrieval.  

Deep Learning:
A type of machine learning using artificial neural networks to analyze and learn from large amounts of data.  

Generative AI:
AI that can create new content, such as text, images, or music, based on what it has learned.  

Large Language Model (LLM):
A type of AI, like ChatGPT, trained on massive amounts of text data to generate human-like text.  

Machine Learning (ML):
A subset of AI where machines learn from data to improve their performance over time without being explicitly programmed.

Neural Network:
A system of algorithms inspired by the human brain, used to recognize patterns and process data.  

Prompt Engineering:
The process of designing effective prompts to guide AI in producing desired outputs.  

Singularity:
A theoretical future where AI surpasses human intelligence, leading to unpredictable changes.  

Training Data:
The data used to teach AI systems to recognize patterns and make decisions.