Introduction to Artificial Intelligence

What could the term "Artificial Intelligence" possibly mean, if anything? Is it worth studying?

Definitions

There are hundreds of definitions of artificial intelligence. Most contain a bias as to whether the writer of the definition sees AI as dealing with thinking versus acting, and whether they see it as trying to model humans or capturing intelligence (rationality) abstractly.

  Humanly Rationally
Thinking Thinking humanly: Cognitive modeling. Systems should solve problems the same way humans do. Thinking rationally: Using logic. Need to worry about modeling uncertainty and dealing with complexity.
Acting Acting humanly: The Turing Test approach. Acting rationally: The study of rational agents, that is, agents that maximize the expected value of their performance measure given what they currently know.

Here are definitions put forth by various experts (who know that the general population’s misunderstanding that the term is limited to chatbots and agents using generative AI is unfortunately widespread):

Eight more can be found here. And a handful more here.

Concerns

AI has both scientific (nature of intelligence) and engineering (design and production of intelligent agents) aspects. There’s another aspect dealing with the ways humans use AI systems.

AI Science: The Nature of Intelligence

AI researchers study the nature of intelligence. They don’t (necessarily) try to build androids because:

  1. It was the study of the principles of aerodynamics, not the attempt to make mechanical birds, that enabled human flight.
  2. We already know how to make new humans anyway.

Intelligence involves sensing, thinking, and acting.

SENSING THINKING ACTING
Translation of sensory inputs (percepts) into a conceptual representation Manipulation of the conceptual representation Translation of intent into (physical) actions (reflexive or deliberative)
  • Computer Vision
  • Speech Recognition
  • Language Understanding
  • Knowledge Representation
  • Problem Solving/Planning
  • Learning (making improvements based on the results of past actions)
  • Robotics
  • Speech and Language Synthesis

AI Engineering: Intelligent Agents

An agent is something that senses and acts.

AI Fluency

AI fluency is the ability to understand, evaluate, and apply AI tools in various workflows, interacting with systems in ways that are efficient, ethical, and safe.

You can get an introduction to AI fluency in this short article. Also, check out the 4D AI Fluency Framework. Anthropic defines the four D’s like this:

Delegation

Thoughtfully deciding when and how to delegate tasks to AI systems.

Discernment

Evaluating the accuracy, quality, and appropriateness of AI outputs and behaviors.

Description

Clearly and precisely describing goals when prompting.

Diligence

Taking responsibility for the outcomes of AI-assisted decisions and actions.

Or take this course from Anthropic.

So how is AI fluency doing these days? Read this report.

Areas of Study

In no particular order, nor with any thought of completeness, here are a few:

Influences

From Section 1.2 of Russell and Norvig:

Brief History

Highlights:

More history:

Applications

Today AI is in:

See Also