13.11.Key Terms

Chapter 13 

Algorithms: which are a set of rules or processes to solve a specific problem or task. (13.3)

Artificial Intelligence: The ability of a computer or machine to think and learn, and mimic human behaviour. (13.1)

Augmented reality (AR): Enhances one’s view of the real world with layers of digital information added to it. With AR there is no created scenario; instead, an actual event is being altered in real time. (13.7)

Autonomous Technologies: Autonomous robots and vehicles that work by combining software, sensors, and location technologies. Devices that can operate themselves. (13.6)

Chat-bots: are computer programs that use AI and natural language processing (NLP) to understand customer questions and automate responses to them, simulating human conversation. (13.4)

Collaborative Technology: To share data with each other for mutual benefit. Some of this sharing can be done passively and other data can be reported actively. (13.8)

Deep Learning (DL): A subset of Machine Learning – Deep Learning refers to when computers are able to solve more complex problems without human intervention.(13.5)

Emerging technology: includes new technology and technology that is continuously evolving. (13.1)

Expert Systems (ES): Designed to emulate the human ability to make decisions in specific contexts, and have had a large impact in the world of AI. (13.6)

Extended Reality or XR: XR is an umbrella term that covers all forms and combinations of real and virtual environments. This includes: augmented reality (AR), virtual reality (VR) and a combination of the two or mixed reality (MR).(13.7)

Intelligent Agents: Process the inputs it receives, and makes decisions/ takes action based on that information. (13.6)

Internet of Things: The idea of physical objects being connected to the Internet, embedded with electronics, software, sensors, and network connectivity, which enables these objects to collect and exchange data. (13.8)

Loop: a part of software code that allows a command to run again and again. (13.3)

Machine Learning (ML):  is a technique that is used by an AI system to analyze data, find patterns and make decisions automatically or with minimal human support.(13.5)

Nanobot: Is a robot whose components are on the scale of about a nanometer, which is one-billionth of a meter. While still an emerging field, it is showing promise for applications in the medical field.(13.6)

Natural Language Processing (NLP): Allows computers to extract meaning from human language. Natural Language Processing’s goal by design is to read, decipher, and comprehend human language.(13.6)

Reinforcement Learning: A form of Machine Learning in which a machine is given unlabelled data and must find its own connections through analysis, clustering, and identifying patterns. (13.5)

Robots: Are automated machines that can execute specific tasks with very little or no human intervention and are able to accomplish tasks with both speed and precision. (13.6)

Supervised Learning: A form of Machine Learning in which data is labeled and categorized into groups by humans and algorithms are used to classify data based on labels. (13.5)

Unsupervised Learning: The trial and error-based Machine Learning method in which a machine learns from mistakes and improves upon them. (13.5)

Virtual Reality (VR): Computer interaction in which a real or imagined environment is simulated. This allows users to both interact with and alter that reality within the environment. (13.7)

Wearable Technology: A category of technology devices that can be worn by a consumer and often include tracking information related to health and fitness. (13.8)


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Information Systems for Business and Beyond Copyright © 2022 by Shauna Roch; James Fowler; Barbara Smith; and David Bourgeois is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.

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