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Artificial Intelligence Literacy: Basics

Constantly updated guide to the right use of AI generated content in the study and research

What is AI

The prompt to ChatGPT "What AI is" returned response:

AI stands for Artificial Intelligence. It refers to the simulation of human intelligence in machines that are programmed to think and learn like humans and mimic their actions. AI involves the development of algorithms and systems that can perform tasks that would typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.

Below are the main concepts related to AI which are on everyone's lips. AI becomes synonymous with machine learning or GPT. Good to know the difference in terms.

Artificial Intelligence (AI)

AI - the use of computers to model the behavioral aspects of human reasoning and learning. (The Columbia Encyclopedia)

In other words: the computer performs the intellectual task as a human does. Examples: search suggestions and recommendations, spam detection, image recognition, machine translation.

AI covers a wide variety of specific approaches and algorithms (see below)

File:Arrow-down.svg - Wikimedia Commons

Machine learning

ML is one of the algorithms under the umbrella of AI

Machines/computers learn to do rather than being programmed to do. They learn from data and big data.

File:Arrow-down.svg - Wikimedia Commons

Deep Learning

Is a subfield of machine learning

 Machines learn using neural networks for data analysis and process which is a simulation of human brain.

The algorithms used: Natural Language Processing (NLP), Image and Video Recognition, and Audio Transcription. 

File:Arrow-down.svg - Wikimedia Commons

Generative AI

Deep learning model that generates text, image, video etc. Examples: ChatGPT, Dall-E

Good at data analysis and coding.

Weakness - accuracy and "hallucination" (refer to/generate data or information which doesn't exist); data security and privacy are questioned.

AI in a Snap - Intro for Novices

GenAI in a Nutshell - Guide for Beginners

Potential Application

Pro

Cons

Idea generation Integrity and ethical concerns
Search Bias
Summary and synthesis Lack of context understanding
Data analysis and visualization Accuracy
Grammar and spelling checking Data privacy
Citation generation Missing purpose of learning and developing creativity
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