Introduction to Generative AI in Assessments
1. What is AI?
Artificial intelligence (AI) is the theory and development of computer systems capable of performing tasks that normally required human intelligence, such as interpreting language, recognizing patterns from large amounts of data, and making decisions. Some of the names given to AI, based on the way in which it is designed and what it can do, include neural networks, natural language processing, computer vision, speech recognition, machine learning, and deep learning.
While we tend to think of it as a product of the 21st century, it has been around since the middle of the 20th century. Chances are good that you interact with AI every day. Examples of AI include:
- Asking your Smartphone to unlock your phone by recognizing your face;
- Navigating to your destination using apps like Google Map or Waze to find the quickest route;
- Getting more posts in your social media feeds that match those with which you previously interacted (that you liked or commented on);
- Getting a notification from your bank that there has been unusual activity in your account;
- Obtaining a recommendation from an online store (or music or video streaming platform) based on your previous purchases;
- Interacting with a customer service chatbot;
- Feeding your text through a grammar software that suggests better ways to write your text;
- Using Google Translate to translate text from one language into another;
- Using a voice-to-text app on a smartphone;
- Using a personal assistant like Siri, Alex, or Cortana.
AI has been around in education for decades, usually embedded as part of the student management system or the learning management system. These sorts of AI monitored student engagements with their platforms and analyzed large amounts of data to predict which student was likely to succeed or withdraw from a course (and therefore which ones might benefit from additional support), and how to optimize and personalize learning.