With the widespread use of large language models (LLMs), many researchers have turned their attention to detecting text generated by them. However, there is no consistent or precise definition of their target, namely "LLM-generated text". Differences in usage scenarios and the diversity of LLMs further increase the difficulty of detection. What is commonly regarded as the detecting target usually represents only a subset of the text that LLMs can potentially produce. Human edits to LLM outputs, together with the subtle influences that LLMs exert on their users, are blurring the line between LLM-generated and human-written text. Existing benchmarks and evaluation approaches do not adequately address the various conditions in real-world detector applications. Hence, the numerical results of detectors are often misunderstood, and their significance is diminishing. Therefore, detectors remain useful under specific conditions, but their results should be interpreted only as references rather than decisive indicators.

ChatGPT can now easily pass any Turing test, a measure of successful A.I. proposed by a founder of computer science, Alan Turing. But contemporary Turing tests leave out the most interesting part of Turing's original test: the gender-bending. I can usually spot A.I. writing in my students' work by the overuse of words like "delve," but the accuracy of artificial intelligence is impossible to deny. A.I. is being integrated into every aspect of our written culture, from news sources to classrooms to medicine. But in 1950, Turing's ideas about A.I. were prescient, creative, and, when I read them, surprisingly queer.

AI has been rapidly finding industrial applications, such as the use of large language models to automate enterprise IT. Those applications may make the question of actual intelligence moot. The British mathematician Alan Turing wrote in 1950, "I propose to consider the question, 'Can machines think?'" His inquiry framed the discussion for decades of artificial intelligence research. For a couple of generations of scientists contemplating AI, the question of whether "true" or "human" intelligence could be achieved was always an important part of the work.

Less than a decade after helping the Allied Forces win World War II by breaking the Nazi encryption machine Enigma, mathematician Alan Turing changed history a second time with a simple question: "Can machines think?" Turing's 1950 paper Computing Machinery and Intelligence and its subsequent Turing Test established the fundamental goal and vision of AI. At its core, AI is the branch of computer science that aims to answer Turing's question in the affirmative. It is the endeavor to replicate or simulate human intelligence in machines. The expansive goal of AI has given rise to many questions and debates.

Starting today, the Privacy Center will stop using the terms "artificial intelligence," "AI," and "machine learning" in our work to expose and mitigate the harms of digital technologies in the lives of individuals and communities. I will try to explain what is at stake for us in this decision with reference to Alan Turing's foundational paper, Computing Machinery and Intelligence, which is of course most famous for its description of what the paper itself calls "the imitation game," but what has come to be known popularly as "the Turing test." The imitation game involves two people (one of whom takes the role of the "interrogator") and a computer. The object is for the interrogator, physically separated from the other player and the computer, to try to discern through a series of questions which of the responses to those questions is produced by the other human and which by the computer. "…in about fifty years' time it will be possible to programme computers, with a storage capacity of about 10⁹, to make them play the imitation game so well that an average interrogator will not have more than 70 percent, chance of making the right identification after five minutes of questioning."

Turing's paper "Computing Machinery and Intelligence" (1950), and its subsequent Turing Test, established the fundamental goal and vision of artificial intelligence. At its core, AI is the branch of computer science that aims to answer Turing's question in the affirmative. It is the endeavor to replicate or simulate human intelligence in machines. The expansive goal of artificial intelligence has given rise to many questions and debates. So much so, that no singular definition of the field is universally accepted.

Less than a decade after breaking the Nazi encryption machine Enigma and helping the Allied Forces win World War II, mathematician Alan Turing changed history a second time with a simple question: "Can machines think?" Turing's paper "Computing Machinery and Intelligence" (1950), and its subsequent Turing Test, established the fundamental goal and vision of artificial intelligence. At its core, AI is the branch of computer science that aims to answer Turing's question in the affirmative. It is the endeavor to replicate or simulate human intelligence in machines. The expansive goal of artificial intelligence has given rise to many questions and debates.

Can machines (or computers) think? What did Alan Turing have to say to that question? Well, he believed that the question is too "meaningless to answer". "The original question, 'Can machines think?', I believe to be too meaningless to deserve discussion." In other words, how can we even answer that question if we don't really know what thinking actually is in the first place?

On Artificial Minds Maria Odete Madeira 18-06-2016 "Sed hoc pacto, si quis tam minutum cerneret, ut in uermiculato pauimento nihil ultra unius tesserae modulum acies eius ualeret ambire…" ("De ordine", Augustine, Liber Primus, I, 2) …and if someone had a discernment so narrow that, in a mosaic pavement, could not encompass with the gaze nothing more than the surface of a single piece… Mēns, mentis, mente: spirit, soul, intellect, character, reason, pensamentum (thought) compose a semantic field with semiotic openings to interpretative superveniences for explicative reasons with postulated legitimacies, compatible with pragmatics of operative objectivity. Mente (Old Portuguese) radiculated in mentem (singular accusative of mēns), from the Proto-Indo-European *méntis with the meaning of pensamentum (thought). Mēns, mentis: mente (Old Portuguese): matrix of dispositional integrated order towards cognitive dynamics. We signalize the term dispositional (to put in order) and the term pensamentum: the result of the action of pensare (to think): "Pensare (Latin) means literally: to weigh, to analyze, to synthesize, to associate, to (dis)associate. In any of these definitions are synthesized cognitive dynamics of production of judgment, from the Latin judicium, term primitively connected to the senses of justice and of just, irrecusably linked to the senses of proportion and of measure, opening the term 1 pensare to semantic webs that connect it to the terms: to choose, to decide and to determine between available possibilities towards dynamics of action, in which it is included the action of pensare."

I propose to consider the question, 'Can machines think?' This should begin with definitions of the meaning of the terms'machine' and'think'. The definitions might be framed so as to reflect so far as possible the normal use of the words, but this attitude is dangerous. If the meaning of the words'machine' and'think' are to be found by examining how they are commonly used it is difficult to escape the conclusion that the meaning and the answer to the question, 'Can machines think?' is to be sought in a statistical survey such as a Gallup poll. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words. The new form of the problem can be described in terms of a game which we call the'imitation game'. It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart from the other two. The object of the ...