Page 109 - Ai V2.0 Flipbook C8
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GLOSSARY
Artificial Intelligence: AI is the design of machines to think and act in ways similar to
humans.
AI Bias: This refers to AI making wrong or unfair decisions, even if it wasn’t intended to.
AI Ethics: Refers to the values and principles guiding what is right and wrong in
developing and using AI technologies.
AI Project Cycle: A clear, repeatable sequence of steps for building an artificial
intelligence solution—from identifying a problem to improving the finished system.
Computer Vision: Helps computers "see" and "understand" what is in pictures or videos.
Data Acquisition: The foundation of a successful AI project, where data is collected for
use in developing AI models.
Evaluation: One of the most critical stages of an AI project, where the model is assessed
for performance.
Ethics: The moral behavior of humans in given circumstances within their social life.
Natural Language Processing (NLP): Enables computers to understand human
language—both spoken and written.
Problem Scoping: The first and most important step in the AI project cycle, where the
problem to be solved is defined.
Project: A specific piece of work with a clear goal, such as planning a class fair or
building a model volcano.
Statistical Data: Data that AI uses to learn by finding patterns in large sets of information.
Systems Thinking: An approach to problem-solving that views problems as part of a
larger, interconnected system.
System Map: A diagram that shows the key elements of a system and the arrows of
influence between them.
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