scholarly journals Chinese room and program identity

2017 ◽  
Vol 60 (1) ◽  
pp. 28-39
Author(s):  
Nenad Filipovic
Keyword(s):  
Artificial Intelligence ◽  
The Other ◽  
John Searle ◽  
Chinese Room ◽  
Chinese Room Argument ◽  
Strong Conclusion ◽  
Famous Argument ◽  
Present Argument

The Chinese room argument is famous argument introduced by John Searle, in which Searle presented various problems with the claim that it is possible for the artificial intelligence to have understanding of a language in a way in which intelligent beings such as humans have that capacity. The argument was influential enough to, in decades following it, sparke numerous responses and critiques, along with a few alleged improvements to it from Searle. In this article, I will analyze one atypical critique of Searle?s argument, made by Mark Sprevak. Sprevak, unlike the other critics of the argument, agrees with Searle that understanding does not exist in Chinese room in any way, but he claims that Chinese room cannot execute every possible program, like Searle claims. Because of that, Searle cannot conclude the strong conclusion he wants from The Chinese room argument. In this article, I will analyze Searle?s argument, I will give a brief overview of typical responses to it, and I will analyze Sprevak?s response. In the last section, I will present argument that shows that Sprevak, if he wants to keep his conclusions, must either give up one part of his response, or accept one of the typical responses to Searle?s argument, thus making his own response dependent on the response from others.

Looking to the Future

2019 ◽  
pp. 254-263
Author(s):  
Alan J. McComas
Keyword(s):  
Artificial Intelligence ◽  
20Th Century ◽  
Thought Experiments ◽  
Chinese Room ◽  
Chinese Room Argument ◽  
Inorganic Matter ◽  
The Future

This chapter considers the question of whether or not nonliving systems can acquire consciousness. It explores contemporary advances in technology, particularly in the field of artificial intelligence. The chapter also considers whether or not consciousness can be performed if inorganic matter replaced the components with which organisms experience consciousness. These and similar questions on nonhuman intelligence and consciousness are fleshed out with scenarios and thought experiments proposed throughout the 20th century, such as John Searle’s Chinese room argument and the archangel paradigm proposed by C. D. Broad. The chapter concludes with reflections on the human being’s inability to truly experience consciousness in the same way as nonhumans.

Chinese room argument

2018 ◽  
Author(s):  
Robert Van Gulick
Keyword(s):  
Artificial Intelligence ◽  
Computer Program ◽  
Mental States ◽  
Chinese Room ◽  
Chinese Room Argument ◽  
Strong Ai

John Searle’s ‘Chinese room’ argument aims to refute ‘strong AI’ (artificial intelligence), the view that instantiating a computer program is sufficient for having contentful mental states. Imagine a program that produces conversationally appropriate Chinese responses to Chinese utterances. Suppose Searle, who understands no Chinese, sits in a room and is passed slips of paper bearing strings of shapes which, unbeknown to him, are Chinese sentences. Searle performs the formal manipulations of the program and passes back slips bearing conversationally appropriate Chinese responses. Searle seems to instantiate the program, but understands no Chinese. So, Searle concludes, strong AI is false.

Intelligence et intentionalité. Critique de l'argument de Searle contre l'intelligence artificielle

Dialogue ◽  
1991 ◽  
Vol 30 (1-2) ◽  
pp. 85-102 ◽  
Author(s):  
Maryvonne Longeart
Keyword(s):  
John Searle ◽  
Chinese Room ◽  
Chinese Room Argument ◽  
Intelligence Artificielle ◽  
Alan Turing ◽  
Computing Machinery

Dans son célèbre article de 1950 «Computing Machinery and Intelligence», Alan Turing suggère qu'un critère d'intelligence pour une machine serait qu'elle puisse se faire passer pour un interlocuteur humain. Ce test, appelé «Test de Turing», a été critiqué par John Searle, qui a remis en cause sa pertinence en s'appuyant sur une expérience mentale connue sous le nom de l'argument de la chambre chinoise (Chinese Room Argument). L'expérience tend à montrer que l'intelligence artificielle au sens propre du terme est impossible, parce que les symboles manipulés par les programmes de prétendue «intelligence artificielle» (IA) sont dépourvus de signification. L'intentionalité propre à certains êtres vivants peut seule faire naître le sens. L'imitation d'un comportement intentionnel ne le peut pas. Le test de Turing serait done insatisfaisant, parce qu'il ne permettrait pas de distinguer les systèmes intentionnels de systèmes qui ne le sont pas, et que par conséquent il ne permettrait pas de distinguer l'intelligence authentique (intentionnelle) de la simulation de l'intelligence (non intentionnelle).

scholarly journals In Defense of Strong AI

2017 ◽  
Vol 10 (1) ◽  
pp. 38-49
Author(s):  
Corey Baron
Keyword(s):  
Machine Learning ◽  
Thought Experiment ◽  
Second Order ◽  
Order System ◽  
Semantic Meaning ◽  
John Searle ◽  
Chinese Room ◽  
Chinese Room Argument ◽  
Strong Ai

This paper argues against John Searle in defense of the potential for computers to understand language (“Strong AI”) by showing that semantic meaning is itself a second-order system of rules that connects symbols and syntax with extralinguistic facts. Searle’s Chinese Room Argument is contested on theoretical and practical grounds by identifying two problems in the thought experiment, and evidence about “machine learning” is used to demonstrate that computers are already capable of learning to form true observation sentences in the same way humans do. Finally, sarcasm is used as an example to extend the argument to more complex uses of language

scholarly journals Searle, Syntax, and Observer Relativity

1996 ◽  
Vol 26 (1) ◽  
pp. 101-122 ◽  
Author(s):  
Ronald P. Endicott
Keyword(s):  
Physical Properties ◽  
Physical System ◽  
John Searle ◽  
Chinese Room ◽  
Chinese Room Argument ◽  
Syntactic Property ◽  
Computational Psychology ◽  
Syntactic Properties ◽  
The Mind ◽  
Digital Computers

In his bookThe Rediscovery of the Mind(hereafter RM), John Searle attacks computational psychology with a number of new and boldly provocative claims. Specifically, in the penultimate chapter entitled ‘The Critique of Cognitive Reason,’ Searle targets what he calls ‘cognitivism,’ according to which our brains are digital computers that process a mental syntax. And Searle denies this view on grounds thatthe attribution of syntaxisobserver relative.A syntactic property is arbitrarily assigned to a physical system, he thinks, with the result that syntactic states ‘do not even exist except in the eyes of the beholder’(RM,215). This unabashed anti-realism differs significantly from Searle's earlier work. The Chinese room argument, for example, was intended to show that syntactic properties will not suffice for semantics, where the syntax was realistically construed. But now Searle claims that physical properties will not suffice to determine a system's syntactic properties.

DEVELOPING THE SCIENTIFIC MAGAZINE IN THE PERIOD OF THE FOURTH INDUSTRIAL REVOLUTION 4.0

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Nguyen Duy Dung
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Industrial Revolution ◽  
Scientific Journal ◽  
Publishing Research ◽  
The Other ◽  
High Tech ◽  
Fourth Industrial Revolution ◽  
Socio Economic Development ◽  
International Scientific Journal

Characteristics of the industrial revolution 4.0 is the wide application of high-tech achievements, especially information technology, digitalization, artificial intelligence, network connections for management to create sudden changes in socio-economic development of many countries. Therefore, to reach the high-tech time, many magazines in Vietnam have changed dramatically, striving to reach the international scientific journal system of ISI, Scopus. The publication of international standard scientific journal will meet the demand of publishing research results of local scientists, on the other hand contribute to strengthening exchange, cooperation, international integration in science and technology.

scholarly journals Interventional radiology and artificial intelligence in radiology: Is it time to enhance the vision of our medical students?

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Pierre Auloge ◽  
Julien Garnon ◽  
Joey Marie Robinson ◽  
Sarah Dbouk ◽  
Jean Sibilia ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Interventional Radiology ◽  
Clinical Practice ◽  
Medical Students ◽  
Medical Curriculum ◽  
New Technology ◽  
Large Population ◽  
The Other ◽  
Clinical Phase ◽  
Preclinical Phase

Abstract Objectives To assess awareness and knowledge of Interventional Radiology (IR) in a large population of medical students in 2019. Methods An anonymous survey was distributed electronically to 9546 medical students from first to sixth year at three European medical schools. The survey contained 14 questions, including two general questions on diagnostic radiology (DR) and artificial intelligence (AI), and 11 on IR. Responses were analyzed for all students and compared between preclinical (PCs) (first to third year) and clinical phase (Cs) (fourth to sixth year) of medical school. Of 9546 students, 1459 students (15.3%) answered the survey. Results On DR questions, 34.8% answered that AI is a threat for radiologists (PCs: 246/725 (33.9%); Cs: 248/734 (36%)) and 91.1% thought that radiology has a future (PCs: 668/725 (92.1%); Cs: 657/734 (89.5%)). On IR questions, 80.8% (1179/1459) students had already heard of IR; 75.7% (1104/1459) stated that their knowledge of IR wasn’t as good as the other specialties and 80% would like more lectures on IR. Finally, 24.2% (353/1459) indicated an interest in a career in IR with a majority of women in preclinical phase, but this trend reverses in clinical phase. Conclusions Development of new technology supporting advances in artificial intelligence will likely continue to change the landscape of radiology; however, medical students remain confident in the need for specialty-trained human physicians in the future of radiology as a clinical practice. A large majority of medical students would like more information about IR in their medical curriculum; almost a quarter of students would be interested in a career in IR.

scholarly journals The Speech Act Fallacy Fallacy

1982 ◽  
Vol 12 (3) ◽  
pp. 509-526 ◽  
Author(s):  
Thomas Hurka
Keyword(s):  
Speech Act ◽  
Illocutionary Force ◽  
The Other ◽  
John Searle ◽  
Speech Act Analysis

John Searle has charged R.M. Hare's prescriptivist analysis of the meaning of ‘good,’ ‘ought’ and the other evaluative words with committing what he calls the ‘speech act fallacy.’ This is a fallacy which Searle thinks is committed not only by Hare's analysis, but by any analysis which attributes to a word the function of indicating that a particular speech act is being performed, or that an utterance has a particular illocutionary force. ‘There is a condition of adequacy which any analysis of the meaning of a word must meet,’ Searle writes, ‘and which the speech act analysis fails to meet. Any analysis of the meaning of a word must be consistent with the fact that the same word (or morpheme) can mean the same thing in all the different kinds of sentences in which it can occur.' Hare maintains that the word ‘good’ is used to indicate the speech act of prescribing. He maintains that one of the principal functions of this word is to indicate that utterances of sentences containing it have prescriptive illocutionary force, and that an analysis of its meaning must make explicit and ineliminable reference to this force-indicating function. But ‘good’ regularly occurs in sentences utterances of which appear to have no prescriptive illocutionary force.

Towards a Lexically Oriented Automatic Parsing

1991 ◽  
Vol 15 (1) ◽  
pp. 1-40
Author(s):  
Lucio Costa
Keyword(s):  
Artificial Intelligence ◽  
Distributed Control ◽  
Data Structures ◽  
General Framework ◽  
Computational Models ◽  
The Other ◽  
Sono Stati ◽  
Use Context ◽  
And Linguistics ◽  
Context Free

RIASSUNTO La ricerca sul linguaggio naturale condotta in Intelligenza Artificiale si è sviluppata, malgrado le apparenze, in modo alquanto indipendente dal la-voro dei linguisti. Da un lato sono stati elaborati modelli computazionali delle facoltà di lunguaggio che si configurano come largamente autonomi rispetto a quelli sviluppati in linguistica. D'altro lato, l'implementazione dei sistemi è stata influenzata da soluzioni pragmatiche connesse all'efficacia computazionale delle regole indipendenti dal contesto, alla necessità di evitare componenti trasformazionali inversi e ad una concezione rappresenta-zionale del significato. Il presente articolo propone l'interesse dei lavori lin-guistici di Z. S. Harris e M. Gross ai fini dello sviluppo di un'analisi sintat-tica automatica che sia a controllo diffuso e incentrata sul comportamento idiosincratico delle unità lessicali. Essa è anche inquadrata nel tentativo di gettare luce sulla natura del processo denotazionale. SUMMARY In spite of the claim on the interactions between artificial intelligence (AI) and linguistics, AI research on natural language has developed independently from the work of linguists. On one hand, computational models of the faculties of language which are independent from the models developed in linguistics have been worked out. On the other hand, the AI system design has been oriented towards practical solutions, whose main motivations where to use context-free rules, to avoid an inverse transformational component, and to represent meanings by some data structures. This paper is about the linguistic works of Z.S. Harris and M. Gross to develop automatic distributed control parsing which takes seriously into account the indiosyncratic behaviour of the lexical items. The general framework for the discussion is the procedural nature of the denotational process.

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