scholarly journals Artificial “Intelligence” and the Human Mind: Futuristic Synecdoche and Reality (Linguistic and Linguomental Aspects)

2020 ◽  
Vol 11 (4) ◽  
pp. 745-759
Author(s):  
Valery V. Volkov
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Abilities ◽  
Native Speakers ◽  
Fundamental Problem ◽  
Human Mind ◽  
Cultural Aspects ◽  
Word Combination ◽  
Special Knowledge ◽  
Electrical Impulses ◽  
The Mind

The study aims to make a model of the semantic processes taking place during hermeneutic interpretation of the Russian terminological word-combination искусственный интеллект ( artificial intelligence ) in comparison with the noun ум ( mind ). The relevance of the work is due to the fact that nave (i.e., who does not have special knowledge) native speakers tend to identify (1) mind, (2) intelligence, (3) those imitations of human cognitive activities that are associated with the use of automata and computer equipment. The semantics of the noun ум ( mind ) refers to everything that is connected with consciousness in all its manifestations; in this sense, the concept of mind is among the primary concepts that cannot be correctly defined. The word интеллект (intelligence) captures only a certain part of the mind, namely, the cognitive abilities. The human mind, consciousness is beyond the capabilities of computer imitation; intelligence, understood as cognitive abilities, is partially amenable to techno-electronic modeling. The term искусственный интеллект ( artificial intelligence ) is constructed as a double synecdoche: 1) a part instead of a whole (intelligence as a part - mind as a whole); 2) a whole instead of a part (intelligence as a whole - representing this whole set of electrical impulses in the computer - a mechanism for working with data). The semantic result is the basis of the transhuman ideology, which is based on the identification of the mind, intelligence, and computer simulations. The term artificial intelligence in stylistic and cultural aspects: 1) personification of the mechanism (robot, automaton, computer), 2) depersonification of the person (human); in general - depersonificational travesty. The personification of virtual simulation intelligence and depersonification of real, authentic intelligence / mind are interpreted as the neutralization of privative antonymic opposition, as the formation of a virtual middle element, which is related to the dehumanization of human race as a fundamental problem of our time.

The Intersections of Creativity, Technology, and the Mind

2020 ◽  
pp. 123-140
Author(s):  
Audri Phillips
Keyword(s):  
Artificial Intelligence ◽  
Computer Vision ◽  
Motion Capture ◽  
Human Mind ◽  
Media Technology ◽  
The Senses ◽  
Creativity Studies ◽  
The Mind ◽  
Immersive Technologies

This chapter examines the relationships between technology, the human mind, and creativity. The chapter cannot possibly cover the whole spectrum of the aforementioned; nonetheless, it covers highlights that especially apply to new immersive technologies. The nature of creativity, creativity studies, the tools, languages, and technology used to promote creativity are discussed. The part that the mind and the senses—particularly vision—play in immersive media technology, as well as robotics, artificial intelligence (AI), computer vision, and motion capture are also discussed. The immersive transmedia project Robot Prayers is offered as a case study of the application of creativity and technology working hand in hand.

scholarly journals Contribution of Cognitive Science and Artificial Intelligence in the Simulation of the Complex Human Mind

2020 ◽  
Vol 9 (2) ◽  
pp. 928-932
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Science ◽  
Real Time ◽  
Human Mind ◽  
Scientific Study ◽  
Computational Procedures ◽  
The Mind ◽  
And Behavior ◽  
Interdisciplinary Theory ◽  
The Brain

The research incorporated encircles the interdisciplinary theory of cognitive science in the branch of artificial intelligence. It has always been the end goal that better understanding of the idea can be guaranteed. Besides, a portion of the real-time uses of cognitive science artificial intelligence have been taken into consideration as the establishment for more enhancements. Before going into the scopes of future, there are many complexities that occur in real-time which have been uncovered. Cognitive science is the interdisciplinary, scientific study of the brain and its procedures. It inspects the nature, the activities, and the elements of cognition. Cognitive researchers study intelligence and behavior, with an emphasis on how sensory systems speak to, process, and change data. Intellectual capacities of concern to cognitive researchers incorporate recognition, language, memory, alertness, thinking, and feeling; to comprehend these resources, cognitive researchers acquire from fields, for example, psychology, artificial intelligence, philosophy, neuroscience, semantics, and anthropology. The analytic study of cognitive science ranges numerous degrees of association, from learning and choice to logic and planning; from neural hardware to modular mind organization. The crucial idea of cognitive science is that "thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures."

scholarly journals Hume’s guillotine and intelligent technologies

2021 ◽  
Author(s):  
Pertti Saariluoma
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Social Influence ◽  
David Hume ◽  
Intelligent Systems ◽  
Fundamental Problem ◽  
Human Mind ◽  
The Way

AbstractEmerging intelligent society shall change the way people are organised around their work and consequently also as a society. One approach to investigating intelligent systems and their social influence is information processing. Intelligence is information processing. However, factual and ethical information are different. Facts concern true vs. false, while ethics is about what should be done. David Hume recognised a fundamental problem in this respect, which is that facts can be used to derive values. His answer was negative, which is critical for developing intelligent ethical technologies. Hume’s problem is not crucial when values can be assigned to technologies, i.e. weak ethical artificial intelligence (AI), but it is hard when we speak of strong ethical AI, which should generate values from facts. However, this paper argues that Hume’s aporia is grounded on a mistaken juxtaposition of emotions and cognition. In the human mind, all experiences are based on the cooperation of emotions and cognitions. Therefore, Hume’s guillotine is not a real obstacle, but it is possible to use stronger forms of ethical AI to develop new ethics for intelligent society.

Aristotle's Formal Identity of Intellect and Object: A Solution to the Problem of Modal Epistemology

2019 ◽  
Vol 1 (1) ◽  
pp. 84-107
Author(s):  
Robert C. Koons
Keyword(s):  
Human Mind ◽  
Modal Epistemology ◽  
De Anima ◽  
Object A ◽  
Formal Identity ◽  
Identity Thesis ◽  
The Mind ◽  
Mental Objects ◽  
Aristotelian Metaphysics

In De Anima Book III, Aristotle subscribed to a theory of formal identity between the human mind and the extra-mental objects of our understanding. This has been one of the most controversial features of Aristotelian metaphysics of the mind. I offer here a defense of the Formal Identity Thesis, based on specifically epistemological arguments about our knowledge of necessary or essential truths.

scholarly journals Application of Eye Tracking Technology in Aviation, Maritime, and Construction Industries: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4289
Author(s):  
Daniel Martinez-Marquez ◽  
Sravan Pingali ◽  
Kriengsak Panuwatwanich ◽  
Rodney A. Stewart ◽  
Sherif Mohamed
Keyword(s):  
Eye Tracking ◽  
Human Error ◽  
Human Mind ◽  
Future Research ◽  
Mental Performance ◽  
Medical Scientist ◽  
Future Research Directions ◽  
The Mind ◽  
Attention Failure ◽  
Demographic Distribution

Most accidents in the aviation, maritime, and construction industries are caused by human error, which can be traced back to impaired mental performance and attention failure. In 1596, Du Laurens, a French anatomist and medical scientist, said that the eyes are the windows of the mind. Eye tracking research dates back almost 150 years and it has been widely used in different fields for several purposes. Overall, eye tracking technologies provide the means to capture in real time a variety of eye movements that reflect different human cognitive, emotional, and physiological states, which can be used to gain a wider understanding of the human mind in different scenarios. This systematic literature review explored the different applications of eye tracking research in three high-risk industries, namely aviation, maritime, and construction. The results of this research uncovered the demographic distribution and applications of eye tracking research, as well as the different technologies that have been integrated to study the visual, cognitive, and attentional aspects of human mental performance. Moreover, different research gaps and potential future research directions were highlighted in relation to the usage of additional technologies to support, validate, and enhance eye tracking research to better understand human mental performance.

Seven Things Every Trainer Must Know about Artificial Intelligence

1991 ◽  
Vol 20 (2) ◽  
pp. 153-156
Author(s):  
Mahima Ranjan Kundu
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Business Management ◽  
Human Mind ◽  
Educational Programs ◽  
Training Environment ◽  
Training And Education ◽  
Training Systems ◽  
Potential Benefits

This article provides information about the prospects and limitations of the Artificial Intelligence and Expert Systems as they relate to training systems and educational programs. The article describes the potential benefits of expert systems and how it can be gainfully employed in training environment, industry, and business management to perform complex jobs. The limitations of the applications of the Artificial Intelligence are discussed as some tend to believe that human mind and computers think alike and AI machines can function like a real expert in every aspect of training and education.

scholarly journals Top-down causation and emergence: some comments on mechanisms

2011 ◽  
Vol 2 (1) ◽  
pp. 126-140 ◽  
Author(s):  
George F. R. Ellis
Keyword(s):  
Causal Power ◽  
Physical World ◽  
Human Mind ◽  
Information Control ◽  
Top Down ◽  
Bottom Up ◽  
Adaptive Selection ◽  
Abstract Entities ◽  
The Mind ◽  
Medical Healthcare

Both bottom-up and top-down causation occur in the hierarchy of structure and causation. A key feature is multiple realizability of higher level functions, and consequent existence of equivalence classes of lower level variables that correspond to the same higher level state. Five essentially different classes of top-down influence can be identified, and their existence demonstrated by many real-world examples. They are: algorithmic top-down causation; top-down causation via non-adaptive information control, top-down causation via adaptive selection, top-down causation via adaptive information control and intelligent top-down causation (the effect of the human mind on the physical world). Through the mind, abstract entities such as mathematical structures have causal power. The causal slack enabling top-down action to take place lies in the structuring of the system so as to attain higher level functions; in the way the nature of lower level elements is changed by context, and in micro-indeterminism combined with adaptive selection. Understanding top-down causation can have important effects on society. Two cases will be mentioned: medical/healthcare issues, and education—in particular, teaching reading and writing. In both cases, an ongoing battle between bottom-up and top-down approaches has important consequences for society.

scholarly journals Artificial Cognition: How Experimental Psychology Can Help Generate Explainable Artificial Intelligence

2021 ◽  
Author(s):  
J. Eric T. Taylor ◽  
Graham Taylor
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Neural Networks ◽  
Experimental Approach ◽  
Well Being ◽  
Human Mind ◽  
Black Box ◽  
Psychological Science ◽  
Black Boxes ◽  
Explainable Artificial Intelligence

Artificial intelligence powered by deep neural networks has reached a levelof complexity where it can be difficult or impossible to express how a modelmakes its decisions. This black-box problem is especially concerning when themodel makes decisions with consequences for human well-being. In response,an emerging field called explainable artificial intelligence (XAI) aims to increasethe interpretability, fairness, and transparency of machine learning. In thispaper, we describe how cognitive psychologists can make contributions to XAI.The human mind is also a black box, and cognitive psychologists have overone hundred and fifty years of experience modeling it through experimentation.We ought to translate the methods and rigour of cognitive psychology to thestudy of artificial black boxes in the service of explainability. We provide areview of XAI for psychologists, arguing that current methods possess a blindspot that can be complemented by the experimental cognitive tradition. Wealso provide a framework for research in XAI, highlight exemplary cases ofexperimentation within XAI inspired by psychological science, and provide atutorial on experimenting with machines. We end by noting the advantages ofan experimental approach and invite other psychologists to conduct research inthis exciting new field.

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