AI and Math — A Guide for Parents

  • You can build a personal digital assistant like Alexa who can answer questions and play music for you.
  • You can detect objects in images. Self driving cars use this to help navigate.
  • You can detect fraud. Financial companies use this to detect whether a credit card has been stolen.
  • Some math is needed to understand whether or not an AI is performing well. For example, if you have an AI that is predicting whether an image is a Cat or a Dog, and it has been tested with 50 examples, getting 40 of them right is an Accuracy score of 80%, which is well above what would have happened if an AI had guessed randomly — which would have gotten 50%. Metrics like this can be understood by students with basic knowledge of Algebra, Averages and similar math. More advanced metrics typically require an entry level class in Algebra to appreciate.
  • The datasets themselves have patterns that can be understood even without an AI. For example, if a dataset has prices of houses, basic statistics can be used to understand what the average, median house prices are. More statistics can show us what the distribution of house prices are, if some are outliers etc. These are important for AI because an understanding of data helps the human better appreciate the patterns in the data that they are asking the AI to learn from. The math required to appreciate these kinds of insights are Statistics and Data Representation.
  • The algorithms (or techniques) that make up the AI learning itself are heavily math based. These include methods to digest the data and create models, find the most critical features (attributes) of the data to create Decision Trees, etc. For these functions, AI draws heavily from the math fields of Probability, Statistics, Calculus and Algebra.



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Nisha Talagala

Nisha Talagala

I am a software engineer by training and an expert in artificial intelligence. I am also a mom! I teach coding and tech to kids from grades 4-12.