In the philosophy of artificial intelligence and machine intelligence evaluation, what is the name of the classic test designed to determine whether a machine can exhibit human-like conversational intelligence?

Introduction / Context:
The question of whether machines can think has long been framed by a famous proposal: evaluate a machine's intelligence through an imitation-based conversation test. Instead of defining “thinking,” the test asks whether a human judge can reliably distinguish the machine from a human in text-based dialogue. This has influenced AI research, public perception, and benchmarks for conversational agents.

Given Data / Assumptions:

• The test involves a human interrogator, a human respondent, and a machine respondent.
• Communication is typically via text to avoid cues like voice or appearance.
• Success is defined by the machine’s ability to appear human to the judge over sustained interaction.

Concept / Approach:

Alan Turing proposed the “imitation game,” now widely called the Turing test. If the judge cannot distinguish the machine from the human beyond chance within the rules of the game, the machine is said to have passed. The test sidesteps philosophical debates by operationalizing intelligence as observable behavior during conversation.

Step-by-Step Solution:

Verification / Alternative check:

AI history texts and philosophy of mind references uniformly attribute this test to Alan Turing’s 1950 paper “Computing Machinery and Intelligence.”

Why Other Options Are Wrong:

Boolean and Gaussian relate to algebra and statistics; McCarthy is an AI pioneer but not the namesake of this test.

“None” is incorrect because a well-known term exists.

Common Pitfalls:

Equating passing a Turing test with general intelligence; the test measures conversational deception or imitation under specific conditions, not full cognitive parity.

Final Answer:

Turing test