Understand basics of AI and generative AI (GenAI)

What is Artificial Intelligence?

You might have heard about or used generative artificial intelligence-based tools like ChatGPT, Google Gemini, or Microsoft Co-Pilot - but what is artificial intelligence and generative AI (Gen AI)?

While AI can be hard to define, here are a glossary of important AI terms that you should know. Below is an interactive flashcard set to strengthen your comprehension.

  • AI prompts: inputs or questions given to AI models to generate responses or actions, often used in language models.
  • Artificial General Intelligence (AGI): a concept that suggests a more advanced version of AI than we know today, one that can perform tasks much better than humans while also teaching and advancing its own capabilities. 
  • Artificial Intelligence (AI): the use of technology to simulate human intelligence, either in computer programs or robotics. A field in computer science that aims to build systems that can perform human tasks.
  • Deep Learning: a method of AI, and a subfield of machine learning, that uses multiple parameters to recognize complex patterns in pictures, sound and text. The process is inspired by the human brain and uses artificial neural networks to create patterns.
  • Ethical considerations: An awareness of the ethical implications of AI and issues related to privacy, data usage, fairness, misuse and other safety issues. 
  • Generative AI (GenAI):  a content-generating technology that uses AI to create text, video, computer code or images. The AI is fed large amounts of training data, finds patterns to generate its own novel responses, which can mimic human-like language.  
  • Hallucination: an incorrect response from AI. Can include generative AI producing answers that are incorrect but stated with confidence as if correct.
  • Phantom/Ghost Citation: fictitious references generated by AI models like ChatGPT. A form of "hallucination," which is prevalent in AI-generated content Links to an external site. and poses significant challenges in research Links to an external site., law Links to an external site., and other fields Links to an external site..
  • Machine Learning (ML): A component in AI that allows computers to learn and make better predictive outcomes without explicit programming. Can be coupled with training sets to generate new content. 

Part of the glossary of terms adapted from CNET. Links to an external site. 

Explore different types of AI

While some AI-based tools might come to your mind right away, there are a lot of different tools out there with a lot of different uses. As you evaluate how to use these tools responsibly in your academic work, it is useful to keep the breadth of potential uses in mind. It’s important to consider their ethical implications and the specific expectations of your instructor. If you prefer to avoid AI-generated responses when researching, you can use strategies like adding “-ai” to your Google search.

Below are some potential applications of generative AI. The list of AI-based tools is rapidly expanding. Check out this resource for a list of interesting tools you might be able to use for different purposes

Important note: Academic integrity is critical, and avoiding plagiarism means NOT submitting work that is not your own or using AI-generated content without proper attribution. Some AI tools, particularly paraphrasing software (e.g., Grammarly or QuillBot), may inadvertently lead to plagiarism. Make sure to check the following pages on ethical use and citating AI-generated content.

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