THE STUDY OF COGNITIVE PSYCHOLOGY IN CONJUNCTION WITH ARTIFICIAL INTELLIGENCE

The major purpose of this research is to provide a thorough review and analysis of the interplay between artificial intelligence (AI) and psychology. I talk about state-of-the-art computer programs that are able to simulate human cognition and behavior (such as Human-Computer Interfaces, models of the mind, and data mining programs). Applications may be broken down into several sub-categories and have many different aspects. While developing artificially intelligent robots has been and continues to be the major goal of AI research and development, the widespread acceptance and usage of AI systems have resulted in a much broader transfer of technology. The article begins with a brief history of cognitive psychology, a discussion of its fundamental ideas and models, and a look at the ways in which the study is connected to artificial intelligence (AI). The second part of this article takes a closer look at the difficulties encountered by the field of human-computer interaction, along with its aims, duties, applications, and underlying psychological theories. Multiple scientific, pragmatic, and technical obstacles (complexity problems, disturbing coefficients, etc.) stand in the way of extending or overcoming these limits. We also demonstrate the potential use of mental modeling in the areas of diagnosis, manipulation, and education support in this work. Predictions may be made with the use of data mining, knowledge discovery, or expert systems (for instance, the prognoses of children with mental problems based on their settings). The article reviews the missing features and offers an overview of the coefficients used in the system. Finally, we discuss the application of expert systems and life simulation (applied mental model) in virtual reality to benefit autistic people and their loved ones

Ai in the european manufacturing industry - a management guide

Artificial intelligence will have significant influence upon the manufacturing industry. Rapid disruption of existing processes will lead to a clear distinction between those who were able to adapt quickly enough and those that fall behind. There are several challenges e.g. data availability and IT-security that come along with AI,that managers must addressin advance to be prepared. The opportunities lie mainly in enhancing efficiency as well as fault detection and error recognition. Defininga framework and following certain success factors such as the definition of KPIs and developing a minimum viable product,increases the chances of success massivel

Success Factors Impacting Artificial Intelligence Adoption --- Perspective From the Telecom Industry in China

As the core driving force of the new round of informatization development and the industrial revolution, the disruptive achievements of artificial intelligence (AI) are rapidly and comprehensively infiltrating into various fields of human activities. Although technologies and applications of AI have been widely studied, and factors that affect AI adoption are identified in existing literature, the impact of success factors on AI adoption remains unknown. Accordingly, the main study of this paper proposes a framework to explore the effects of success factors on AI adoption by integrating the technology, organization, and environment (TOE) framework and diffusion of innovation (DOI) theory. Particularly, this framework consists of factors regarding the external environment, organizational capabilities, and innovation attributes of AI. The framework is empirically tested with data collected by surveying telecom companies in China. Structural equation modeling is applied to analyze the data. The results indicate that compatibility, relative advantage, complexity, managerial support, government involvement, and vendor partnership are significantly related to AI adoption. Managerial capability impacts other organizational capabilities and innovation attributes of AI, but it is indirectly related to AI adoption. Market uncertainty and competitive pressure are not significantly related to AI adoption, but all the external environment factors positively influence managerial capability. The study provides support for firms\u27 decision-making and resource allocation regarding AI adoption. In addition, based on the resource-based view (RBV), this article conducts study 2 which explores the factors that influence the firm sustainable growth. Multiple regression model is applied to empirically test the hypotheses with longitudinal time-series panel data from telecom companies in China. The results indicate that at the firm level, the customer value and operational expenses are significantly related to sustainable growth. Also, at the industry level, industry investment significant impacts sustainable growth. Study 2 provides insights for practitioners the way to keep sustainable growth

Artificial intelligence, rationality, and the World Wide Web

Scholars debate whether the arrival of artificial super intelligence - a form of intelligence that significantly exceeds the cognitive performance of humans in most domains - would bring positive or negative consequences. I argue that a third possibility is plausible yet generally overlooked: for several different reasons, an artificial superintelligence might choose to exert no appreciable effect on the status quo ante (the already existing collective superintelligence of commercial cyberspace). Building on scattered insights from web science, philosophy, and cognitive psychology, I elaborate and defend this argument in the context of current debates about the future of artificial intelligence.</p