What are AI and Machine Learning?

Overview

Teaching: 30 min
Exercises: 15 min

Questions

• What is the difference between Artificial Intelligence and Machine Learning?

• What is the data science life cycle?

• What are some of the ethical considerations with using machine learning?

Objectives

• First learning objective. (FIXME)

What are AI and Machine Learning?

We use these 2 terms interchangeably a lot, but there are actually subtle differences.

Artificial Intelligence Definition

When a computer is able to make decisions that mimic how a human would.

AI Example: Clippy

AI Example: SPAM filter

Machine Learning Definition

A subset of AI, where decision rules are formulated from data examples.

Machine Learning is a subset of AI

(Add a new Venn Diagram here)

Clippy and SPAM filter revisited

Activity:

• What abilities would an AI-only (not using Machine Learning) thermostat have, versus a “smart” thermostat like a Nest?
• Can you think of another example of hardware or software that can be considered AI, but not necessarily based on machine learning?

What is a Machine Learning model?

Use a grading or job application rubric as example

How is a Machine Learning model built?

• First, identify the prediction to make, and how to measure its correctness.
• Examine the example data, and try to identify “features”. Domain expertise is important here.
• Either randomly subset part of the data for testing, or identify a new set of data for that.
• Train a model. Depending on the algorithm, go through an iterative process of adjusting weights to maximize your measure of correctness.
• Try it out. Do the predictions make sense? Look at near-misses. Can features be added or removed to reduce confusion?
• Loop back as needed.

Key Points

• First key point. Brief Answer to questions. (FIXME)