Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Introduction to Cognitive Psychology

Introduction to Cognitive Psychology

Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...

Theorems of Pappus and Guldinus: Problem Solving

Theorems of Pappus and Guldinus: Problem Solving

Pappus and Guldinus's theorems are powerful mathematical principles that are used for finding the surface area and volume of composite shapes. For example, consider a cylindrical storage tank with a conical top. Finding the surface area or volume can be challenging for such complex shapes. These theorems are particularly useful in calculating the volume and surface area of such systems. Here, the cylindrical storage tank with a conical top can be broken down into two simple shapes: a...

Cognitivism

Cognitivism

Cognitive psychology emerged as a significant field in the mid-20th century. It focused on understanding humans' internal mental processes. This approach emphasizes how people perceive, remember, think, and solve problems—elements critical to human cognition.
Previously dominated by behaviorism, which prioritized observable behaviors and largely ignored mental processes, psychology transformed in the 1950s. Cognitive psychologists argue that understanding how we think and process...

Cognitive Learning

Cognitive Learning

Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...

Piaget's Stage 3 of Cognitive Development

Piaget's Stage 3 of Cognitive Development

During Piaget's concrete operational stage, from ages 7 to 11, children exhibit a marked increase in logical thinking skills, specifically in relation to tangible, real-world events. This stage is characterized by the development of several essential cognitive concepts, including conservation, reversibility, and classification, all of which support the child's evolving capacity for structured thought.
Conservation and Constancy of Quantity
A significant cognitive milestone in the...

Language and Cognition

Language and Cognition

Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Thin Objects Are Not Transparent.

Theoria·2024

Same author

How to approximate fuzzy sets: mind-changes and the Ershov Hierarchy.

Synthese·2023

Same author

On logicality and natural logic.

Natural language semantics·2021

Same author

Classifying equivalence relations in the Ershov hierarchy.

Archive for mathematical logic·2020

Same journal

Artificial general intelligence and the clinical laboratory: a paradigm shift toward Lab 2.0.

Clinical chemistry and laboratory medicine·2026

Same journal

Addressing property and unit discordance in laboratory interoperability: the role of NPU as a governance layer.

Clinical chemistry and laboratory medicine·2026

Same journal

Ethical evaluation of reflex and reflective testing in conformity with ISO 15189:2022 at the value-based laboratory medicine era.

Clinical chemistry and laboratory medicine·2026

Same journal

Emerging blood-based diagnostic strategies for tuberculosis.

Clinical chemistry and laboratory medicine·2026

Same journal

Homocitrulline and 3-year mortality in older hospitalised adults: an exploratory study.

Clinical chemistry and laboratory medicine·2026

Same journal

Impact of age partitioning on classification discordance in pediatric ferritin reference intervals.

Clinical chemistry and laboratory medicine·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Sep 1, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Computability theory as a philosophical achievement.

Matteo Plebani¹, Luca San Mauro²

¹Filosofia e Scienze dell'Educazione, Universita degli Studi di Torino, Torino, Italy.

Clinical Chemistry and Laboratory Medicine

|August 15, 2022

Summary

This summary is machine-generated.

Philosophy

Keywords:

Rice’s theorem computability theory conceptual engineering

More Related Videos

Perspectives on Neuroscience

Perspectives on Neuroscience

Published on: July 31, 2007

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

Related Experiment Videos

Last Updated: Sep 1, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Perspectives on Neuroscience

Perspectives on Neuroscience

Published on: July 31, 2007

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

Area of Science:

Philosophy of Science
History of Computing
Artificial Intelligence

Background:

Artificial intelligence (AI) is crucial in modern medicine.
The historical development of AI is intertwined with philosophical inquiry.
Computability theory, foundational to computer science, emerged from philosophical questions.

Purpose of the Study:

To highlight the significant role of philosophy in the genesis of artificial intelligence.
To underscore the philosophical underpinnings of computability theory.
To illustrate the interconnectedness of philosophical and scientific advancement.

Main Methods:

Historical analysis of the origins of computability theory.
Philosophical examination of the foundational questions in computer science.
Conceptual review of the relationship between philosophy and AI development.

Main Results:

Research in computability theory was directly motivated by the philosophical problem of characterizing algorithmic solvability.
The theoretical foundations of modern computer science have deep roots in philosophical questioning.
Recognizing this connection reveals a symbiotic relationship between philosophical and scientific progress.

Conclusions:

Philosophy has played a foundational role in the development of artificial intelligence.
Understanding the philosophical origins of AI enhances our appreciation of its scientific trajectory.
Continued reflection on the philosophy-science nexus can foster future innovation in AI and other fields.