In Defense of the Turing Test and its Legacy
- URL: http://arxiv.org/abs/2511.20699v1
- Date: Mon, 24 Nov 2025 12:57:54 GMT
- Title: In Defense of the Turing Test and its Legacy
- Authors: Bernardo Gonçalves,
- Abstract summary: Turing's original test was co-opted by Weizenbaum.<n>Six of the most common criticisms of the Turing test are unfair to both Turing's argument and the historical development of AI.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Considering that Turing's original test was co-opted by Weizenbaum and that six of the most common criticisms of the Turing test are unfair to both Turing's argument and the historical development of AI.
Related papers
- Normality and the Turing Test [51.56484100374058]
It argues that the Turing test is a test of normal intelligence as assessed by a normal judge.<n>It argues that the objectivization of normal human behavior in the Turing test fails due to the game configuration of the test.
arXiv Detail & Related papers (2025-08-29T07:55:16Z) - The next question after Turing's question: Introducing the Grow-AI test [51.56484100374058]
This study aims to extend the framework for assessing artificial intelligence, called GROW-AI.<n>GROW-AI is designed to answer the question "Can machines grow up?" -- a natural successor to the Turing Test.<n>The originality of the work lies in the conceptual transposition of the process of "growing" from the human world to that of artificial intelligence.
arXiv Detail & Related papers (2025-08-22T10:19:42Z) - The Imitation Game: Turing Machine Imitator is Length Generalizable Reasoner [71.41162392872393]
This paper proposes Turing MAchine Imitation Learning (TAIL) to improve the length generalization ability of large language models.<n>TAIL synthesizes chain-of-thoughts (CoT) data that imitates the execution process of a Turing Machine by computer programs.<n>Without bells and whistles, TAIL significantly improves the length generalization ability as well as the performance of Qwen2.5-7B on various tasks.
arXiv Detail & Related papers (2025-07-17T17:50:07Z) - The Imitation Game According To Turing [0.0]
Recent studies have claimed that Large Language Models (LLMs) can pass the Turing Test-a goal for AI since the 1950s-and therefore can "think"<n>We conducted a rigorous Turing Test with GPT-4-Turbo that adhered closely to Turing's instructions for a three-player imitation game.<n>All but one participant correctly identified the LLM, showing that one of today's most advanced LLMs is unable to pass a rigorous Turing Test.
arXiv Detail & Related papers (2025-01-29T13:08:17Z) - Human Bias in the Face of AI: Examining Human Judgment Against Text Labeled as AI Generated [48.70176791365903]
This study explores how bias shapes the perception of AI versus human generated content.<n>We investigated how human raters respond to labeled and unlabeled content.
arXiv Detail & Related papers (2024-09-29T04:31:45Z) - Turing's Test, a Beautiful Thought Experiment [0.0]
There has been a resurgence of claims and questions about the Turing test and its value.
If AI were quantum physics, by now several "Schr"odinger's" cats would have been killed.
This paper presents a wealth of evidence, including new archival sources, and gives original answers to several open questions about Turing's 1950 paper.
arXiv Detail & Related papers (2023-12-18T19:38:26Z) - The Turing Deception [0.0]
This research revisits the classic Turing test and compares recent large language models such as ChatGPT.
The question of whether an algorithm displays hints of Turing's truly original thoughts remains unanswered and potentially unanswerable for now.
arXiv Detail & Related papers (2022-12-09T16:32:11Z) - Can Machines Imitate Humans? Integrative Turing-like tests for Language and Vision Demonstrate a Narrowing Gap [56.611702960809644]
We benchmark AI's ability to imitate humans in three language tasks and three vision tasks.<n>Next, we conducted 72,191 Turing-like tests with 1,916 human judges and 10 AI judges.<n>Imitation ability showed minimal correlation with conventional AI performance metrics.
arXiv Detail & Related papers (2022-11-23T16:16:52Z) - The Meta-Turing Test [17.68987003293372]
We propose an alternative to the Turing test that removes the inherent asymmetry between humans and machines.
In this new test, both humans and machines judge each other.
arXiv Detail & Related papers (2022-05-11T04:54:14Z) - Reservoir memory machines [79.79659145328856]
We propose reservoir memory machines, which are able to solve some of the benchmark tests for Neural Turing Machines.
Our model can also be seen as an extension of echo state networks with an external memory, enabling arbitrarily long storage without interference.
arXiv Detail & Related papers (2020-02-12T01:45:00Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.