SELS Dialogues Journal Volume 3 Issue 1
A diverse collection of articles, each offering a unique perspective and contributing to the ever-expanding landscape of knowledge and creativity.
A diverse collection of articles, each offering a unique perspective and contributing to the ever-expanding landscape of knowledge and creativity.
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Educational Technology<br />
What is AI<br />
by Tinghan Li and Dr. Richard Williamson<br />
ChatGPT, Siri, Alexa, Tesla autopilot. These words<br />
are now commonplace, and even kids know what<br />
they are. We know these programs as AI, or artificial<br />
intelligence. Ever since ChatGPT was released, the<br />
world has been abuzz about AI and what it could mean<br />
for our future. However, it has also resulted in the<br />
term “AI” being thrown around rather loosely. While<br />
modern chatbots and assistants are most definitely AI,<br />
there are many other things that would be considered<br />
artificial intelligence such as a program that creates a<br />
line of best fit on a cartesian plane. This will come as a<br />
surprise to most as anyone that has worked with graphs<br />
or spreadsheets will tell you this is one of the most<br />
basic of functions. My goal is to clear up some common<br />
misconceptions and to provide a formal definition of AI<br />
and machine learning.<br />
Let us start with a clear definition of the word<br />
“intelligence” itself. The Oxford dictionary states that<br />
intelligence means “something that is able to vary its<br />
state or action in response to varying situations, varying<br />
requirements, and past experience”. This encompasses<br />
humans, animals, and now, programs like ChatGPT.<br />
However, while we often think of smart and intelligent<br />
programs, AI includes much more than that. Artificial<br />
intelligence is what it sounds like, anything that can<br />
simulate intelligence is considered AI. In other words, it<br />
can perform the basic human functions of recognizing,<br />
predicting, and/or deciding. A simple example of AI<br />
would be old programs that identified whether or not a<br />
message was offensive. It would search for curse words,<br />
negative language, or common phrases that indicated<br />
anger or disrespect. These followed a set of rules, and<br />
were only as good as the programmer that made them.<br />
They also had no way to “learn” from the messages that<br />
they saw previously, and no way of understanding jokes,<br />
or slangs unless it was coded into them.<br />
A subset of AI is machine learning. This is where you<br />
will find the majority of the AI that we now interact with<br />
day to day. Machine learning is AI that can be trained<br />
on data, and then used to complete certain tasks. For<br />
example, YouTube’s recommendation algorithm learns<br />
from content you watched to make more accurate<br />
predictions about what you want to watch. At first it just<br />
guesses, or recommends what is popular. However, as it<br />
gets to know you, it gets better and better. One way the<br />
machine learning AIs do this is with a neural network.<br />
Think of it as a digital imitation of our brains. The<br />
neurons in our brain get stronger through using them<br />
more.. So, if you practice hockey often, your brain will<br />
strengthen neurons that relate to hockey. The neurons<br />
that relate to fine motor skills involved will likely also be<br />
strengthened so you can shoot the puck, or skate better.<br />
<strong>SELS</strong> DIALOGUES | 6
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