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    COMP2121

    Artificial Intelligence

    Progress0 / 19 done
    Topics19
    1An Introduction to Artificial Intelligence and its applications towards Knowledge Based Systems2Introduction to Reasoning and Knowledge Representation
    3Informed searching4Uninformed searching5Heuristics in Problem Solving6Local searching algorithms7Minimax algorithm8Alpha-beta pruning9Game-playing in AI
    10General Problem Solver11ELIZA12Student13Macsyma14Learning from examples15Artificial Neural Networks (ANN)16Natural Language Processing17Recent trends and applications of AI algorithms18Python programming for AI19Implementation of AI techniques in Python
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    Topic 11 of 19
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    Case Study: ELIZA

    ELIZA is an early natural language processing (NLP) program developed in 1966 by Joseph Weizenbaum at MIT.

    📘 Case Study: ELIZA


    1. What is ELIZA?

    ELIZA is an early natural language processing (NLP) program developed in 1966 by Joseph Weizenbaum at MIT.

    🎯 Its goal was to simulate a human-like conversation, particularly mimicking a Rogerian psychotherapist.

    ELIZA is considered the first chatbot in AI history.


    2. Purpose of ELIZA

    • Explore human-computer interaction using natural language.
    • Demonstrate that simple pattern matching could produce the illusion of understanding.
    • Study how people emotionally react to machines that appear to understand them.

    3. How ELIZA Works

    ELIZA uses pattern matching and substitution techniques:

    1. Analyzes user input using predefined rules.
    2. Matches input against keyword patterns.
    3. Applies a transformation rule to generate a response.

    💬 Example: User: "I am feeling sad." ELIZA: "Why are you feeling sad?"

    ELIZA does not understand the meaning — it simply mirrors the input in a clever way.


    4. The DOCTOR Script

    The most well-known script used in ELIZA is called DOCTOR, where ELIZA pretends to be a psychotherapist.

    • This script works well because therapists often respond with open-ended, reflective questions.
    • ELIZA's responses encouraged users to continue talking, creating the illusion of a meaningful conversation.

    5. Example Interaction

    User: I am unhappy.
    ELIZA: I'm sorry to hear you are unhappy.
    User: I need help.
    ELIZA: What kind of help do you need?
    

    6. Impact of ELIZA

    Contribution Explanation
    Early NLP system First system to simulate dialogue using language rules
    Inspired chatbot development Basis for future systems like Siri, Alexa, and ChatGPT
    Human reaction Many users felt it truly “understood” them, surprising even its creator
    Raised ethical questions About emotional dependence on machines

    7. Limitations of ELIZA

    Limitation Explanation
    No true understanding Only reacts based on keywords and templates
    Fails with complex input Can’t handle logic, ambiguity, or context
    Easily breaks With out-of-pattern or unrelated responses

    ✅ Summary

    Feature Detail
    Name ELIZA
    Creator Joseph Weizenbaum
    Year 1966
    Function Simulates a conversation using pattern matching
    Famous Script DOCTOR (psychotherapist simulation)
    Significance First chatbot, milestone in NLP, inspired future AI systems

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    Case Study: Student

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