Lecture Notes: Introduction to AI

Overview

• This is the last class in the introductory series on AI.
• It covers the definition, philosophy, and science of AI.
• Includes perspectives on techniques, algorithms, and the AI mindset.
• Emphasizes the distinct aspects of AI thinking compared to general computer science.

Defining AI

• AI is a controversial and multifaceted topic with various perspectives and definitions.
• Common themes include intelligent thought and the replication of human behaviors in machines.

Philosophical Angle

• AI isn’t just about technology; it's about understanding intelligent thought and reasoning.
• Definitions of AI often grapple with what constitutes "intelligence."

Science of AI

• AI compared with disciplines like physics (laws of the universe) and biology (evolution, function).
• Focus on creating models of intelligent thought and integrating them into machines.

Controversy in AI

• Defining AI is challenging due to varied perspectives on what constitutes intelligence.
• Intelligence is hard to define even among humans and can be subjective.

Examples of Intelligence

• Perception of the World: Identifying faces, objects, etc.
• Reasoning: Proving theorems, diagnosing diseases.
• Planning: Deciding actions, making plans.
• Learning and Adaptation: Recommending movies, adapting to traffic patterns.
• Understanding: Comprehending text, speech, vision.

Limitations in Defining Intelligence

• Traditional IQ tests are contentious and possibly unreliable measures of intelligence.

Human-Centric vs Non-Human Intelligence

• Intelligence is not restricted to human activity.
• Examples of intelligent non-human behavior (e.g., dolphins, dogs).

Modern AI Goals

• AI goals have evolved; defeating humans in tasks (e.g., chess) no longer considered a primary marker of AI.
• Best performing systems often involve human-AI collaboration.

Definitions from AI Textbooks

• Automation of activities associated with human thinking: Decision making, problem solving, learning.
• Study of mental faculties through computational models.
• Making computers do things currently better performed by humans.
• The branch of CS concerned with the automation of intelligent behavior.

Dimensions of AI Definitions

• Human-like vs Rational: AI systems aim to either replicate human behavior or perform tasks rationally better than humans.
• Thought vs Actions: AI can be about thinking like humans, acting like humans, thinking rationally, or acting rationally.

Class Discussion

• Mixed opinions on which definition best fits AI.
• Acting like humans and acting rationally were popular choices.
• Influences like the Turing Test were highlighted.

Conclusion

• AI is a broad and complex field with evolving definitions and goals.
• The debate on what constitutes true AI remains open and multi-faceted.