Untitled Flashcards Set

Turing's Question

A fundamental shift from 'Can machines think?' to whether a machine can exhibit behavior indistinguishable from that of a human.

Turing Test

An experiment to assess a machine's ability to exhibit intelligent behavior equivalent to that of a human.

Sufficiency of the Turing Test

The capacity for a machine to display intelligent behavior is sufficient grounds to label it intelligent.

Mathematical Objection

The critique asserting that machines cannot perform tasks requiring genuine understanding or creativity.

Argument from Consciousness

The argument that machines lack consciousness and cannot replicate genuine subjective experiences.

Lady Lovelace’s Objection

The belief that machines can only perform explicitly programmed tasks and cannot innovate independently.

Strong AI

The viewpoint that properly programmed computers can genuinely possess minds and consciousness.

Chinese Room Thought Experiment

Searle's experiment showing that manipulating symbols does not equate to genuine understanding.

Missing Element in Programs

Programs lack true understanding and consciousness as they operate devoid of intrinsic meaning.

Systems Reply

The argument that a system may possess understanding even if an individual component does not.

Simulation Reply

The notion that simulating intelligent behavior implies actual understanding, challenged by Searle.

Physical Stance

Predicts behavior based on physical laws and properties, focusing on a mechanistic view.

Design Stance

Assesses what a system is designed to achieve, focusing on its functional attributes.

Intentional Stance

Treating a system as if it holds beliefs and desires to enhance prediction accuracy.

Neural Networks vs. von Neumann Architecture

Neural networks adapt and learn from data, unlike traditional fixed architecture systems.

Backpropagation

An algorithm that adjusts weights in a neural network by feeding errors backward to enhance learning.

Key Feature of Neural Networks

The ability to learn from examples and generalize effectively from training data.

Hidden Layer Activation Patterns

Signify learned features or representations of input data within a neural network.

Graceful Degradation

The ability of neural networks to maintain functionality despite parts failing.

Too Many Hidden Units

Overfitting occurs when a model is tailored too closely to training data, degrading performance on new data.

Begging the Question

Critique of Searle’s argument for presupposing the immaterial nature of understanding.

Analogous Thought Experiment

A thought experiment extending Searle's Chinese Room analogy to challenge Searle's argument.

Default Assumption

The assumption that neurons could give rise to understanding, contrasting Searle's view.

Individual Unit Objection

Questions whether understanding can emerge from the actions of individual units without complexity.

Neural Networks and Cognitive Processes

Proposes that neural networks could reflect aspects of human brain function related to cognition.

Emergence

Complex systems manifest behaviors not predictable from their individual components.

Iteration Proposal

A reconfiguration of Searle's thought experiment to align with human brain functionalities.

Response to Churchlands

Searle's clarification on distinguishing between human cognition and machine intelligence.

Galactic Brain Structure

A construct suggesting collective thinking requires shared meaningful understanding.

Symbols and Intrinsic Semantics

Distinction between symbols as data and the importance of representing meaning cognitively.

Synthesis vs. Simulation

Genuine cognitive synthesis is necessary for understanding, beyond mere imitation.

Philosophy Targeted

Nagel critiques reductionist approaches for overlooking the subjective experience of consciousness.

Organisms' Feature

The subjective nature of experiences that cannot be fully articulated by outsiders.

Definition of Consciousness

Characterized by individual awareness and what it is like to be a specific organism.

Bat's Problematic Case

Bats exemplify challenges in understanding different forms of consciousness.

Conclusion of Nagel's Essay

Objective theories often fail to capture subjective experience.

Microworld

Simplistic domains in AI where limited variables facilitate easier problem-solving.

SHRDLU vs. Turing Test

SHRDLU's performance in controlled tasks contrasts with its inability to pass the Turing Test.

Frame in AI Context

A structured model used by AI systems to interpret situations based on stereotypes.

Frame Problem

The difficulty AI systems face in determining which elements of information to apply.

Performance in Real-world Contexts

Symbolic AI excels in microworlds but struggles in the complexity of real-world applications.

Dennett’s Broader Concern

Links the frame problem to philosophical inquiries on representation and understanding in AI.

Empirical Science Claim

Computer science tests hypotheses through experimentation, aligning with traditional sciences.

Heuristics in Problem-solving

Practical strategies that simplify decision-making and problem-solving processes.

Heuristic-Search Hypothesis

Problem-solving occurs through exploration of a symbol system using heuristics.

True or False Statements

Symbols guided by real-world principles in operations but not restricted to human-created entities.

Physical Symbol System Hypothesis

Physical symbol systems possess the necessary conditions for intelligent action.