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Artificial Intelligence (AI) Guide

What is Generative AI?

What is Generative AI?

Generative AI is a type of artificial intelligence that creates new content, such as text, images, or music based on learned data. It works by learning patterns from large amounts of existing data and then using that knowledge to produce original outputs that mimic human creativity.

What are Large Language Models?

What are Large Language Models?

A large language model is a type of artificial intelligence that can understand and generate human language. It learns from analyzing a vast amount of text data, recognizing patterns and structures in the language. This allows it to generate responses, answer questions, write stories, and perform other language-related tasks in a way that mimics human conversation and writing.

What Tasks Does Generative AI Excel At?

What Tasks Does Generative AI Excel at?

  • Summarizing long texts or articles. AI excels at translating complex quantitative findings into clear, everyday language, making research accessible to a broader audience.
  • Generating keywords for searching databases
  • Refining and receiving critiques on your own writing
  • Brainstorming ideas
  • Creating outlines
  • Feedback on grammar
  • Analyzing excel files

What are Some Concerns with Generative AI?

What are some concerns with Generative AI?

  • Library databases and Google Scholar are superior for locating articles. AI can generate hallucinate citations and lacks access to as many sources.
  • There is a lack of transparency regarding the internal workings of AI, and the sources of AI are not disclosed.
  • While using AI to refine one's writing is ethically permissible, using AI to compose entire works raises concerns.

What does thoughtful use of AI look like in practice?*

  • Use AI to explore ideas that you might not have previously considered
  • Critically evaluate the outputs of AI-generated content
  • Refine and personalize AI outputs to reflect your voice and thought processes
  • Understand when AI is helpful and when human thinking is better
  • Be aware of AI's limitations and biases
  • Take responsibility for the final product, regardless of the tools used

*This question and the subsequent practices were adapted from Carlo Iacono's blogpost, "Agency, AI and the Future of Learning".

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