Course: AI Ethics, Inclusion & Society

Within this module we have discussed some concerning or problematic aspects of AI. Although certain fears are valid, there are many positive educational opportunities that come from AI.   Within some …

AI bias is defined as systems that, “produce biased results that reflect and perpetuate human biases within a society, including historical and current social inequality” (IBM, 2023). We have discusses …

Each of these four key ingredients for modern, post 2017 AI, from the previous video on large language models (LLMs) will be addressed individually below.  1) Large amounts of data: …

Definition: “the ability to read, write and otherwise deal with information using the technologies and formats of the time” (Shear & Knobel, 2008).   In the era of “smart”, fast technology, …

While watching this video segment, make note of how the four following components come together to allow for massive AI capability expansion: Large amounts of data Suitable algorithm/mathematical function Extensive …

As you have already seen, throughout this section curated interview clips with Professor Martin Hendry are available to view. You are encouraged to engage with this content in parallel with …

In this section, we are going to take a deep dive into Large Language Models (LLMs). We will explore their auto-complete nature, and the term “hallucinations” often used to describe …

In this section, we will explore the history of AI in three sections. We will begin by looking at the initial applications of AI systems. Then, we will move to …

Before we progress through this course, we need to develop a working definition for artificial intelligence.  So how do we define artificial intelligence (AI)?The term “artificial intelligence” was first coined …

The existential relates to our existence. When we consider artificial intelligence and our existence, we encounter the question of how the development and use of AI affects our existence. Existential …