Cognitive Machines

We used 4 basis for our work: AI - six thinking levels model described in book "The emotion machine". Evolutionary psychology model of emotions that is called "Wheel of emotions", we used as subjective perception model. Neuroscience(neurotransmission) theory of emotions by Lövheim "Cube of emotions" was used as objective brain emotional response model. Based on neurotransmitters impact we propose to model emotional computing systems. Overall presented work is synthesis of several emotional/affective theories to produce model of emotions and affective mechanisms that fit model of six thinking levels architecture.

In the past, philosophers, scientists, and even the general opinion, had no problem in accepting the existence of consciousness in the same way as the existence of the physical world. After the advent of Newtonian mechanics, science embraced a complete materialistic conception about reality. Scientists started proposing hypotheses like abiogenesis (origin of first life from accumulation of atoms and molecules) and the Big Bang theory (the explosion theory for explaining the origin of universe). How the universe came to be what it is now is a key philosophical question. The hypothesis that it came from Nothing (as proposed by Stephen Hawking, among others), proves to be dissembling, since the quantum vacuum can hardly be considered a void. In modern science, it is generally assumed that matter existed before the universe came to be. Modern science hypothesizes that the manifestation of life on Earth is nothing but a mere increment in the complexity of matter — and hence is an outcome of evolution of matter (chemical evolution) following the Big Bang. After the manifestation of life, modern science believed that chemical evolution transformed itself into biological evolution, which then had caused the entire biodiversity on our planet. The ontological view of the organism as a complex machine presumes life as just a chance occurrence, without any inner purpose. This approach in science leaves no room for the subjective aspect of consciousness in its attempt to know the world as the relationships among forces, atoms, and molecules. On the other hand, the Vedantic view states that the origin of everything material and non-material is sentient and absolute (unconditioned). Thus, sentient life is primitive and reproductive of itself – omne vivum ex vivo – life comes from life. This is the scientifically verified law of experience. Life is essentially cognitive and conscious. And, consciousness, which is fundamental, manifests itself in the gradational forms of all sentient and insentient nature. In contrast to the idea of objective evolution of bodies, as envisioned by Darwin and followers, Vedanta advocates the idea of subjective evolution of consciousness as the developing principle of the world. In this paper, an attempt has been made to highlight a few relevant developments supporting a sentient view of life in scientific research, which has caused a paradigm shift in our understanding of life and its origin.

Purpose
The contributions proposed in this paper are motivated by principles of incompatibility, and non‐equilibrium states, existing between the continuous growth in the level of environmental complexity and the insufficient cognitive capacity of the organization. From such a view, the purpose of this paper is to ask: what are the core competencies of the new industrial organization in the twenty‐first century?
Design/methodology/approach
First, the paper examines the characteristics and limitations of past and current industrial organizations; second, it contributes by extending their frontiers and by proposing technological, managerial and organizational core competencies of the new enterprise.
Findings
From such analyses, this paper introduces the features of customer‐centric systems (CCS) which represent new industrial organizations in the pursuit of high degrees of organizational cognition, intelligence and autonomy, and consequently, high degrees of agility and flexibility, in order to manage high levels of environmental complexity and uncertainty, to operate through intensive mass customization, and to provide customers with immersiveness.
Research limitations/implications
For further research, this paper suggests the investigation of practical implementation of the features of the new enterprise of CCS. In such a direction, it recommends additional reading on the concept and design of computational organizational management networks.
Practical implications
This paper emphasizes that CCS are firm types which strategically organize their resources and competencies around customers' values and needs, in order to involve customers into their business. By involving customers into their task environments and business, CCS‐based firms have the chance to understand their clients' real needs and to produce the appropriate goods and services.
Originality/value
The uniqueness of this paper lies in its attempt to master, analyze and integrate technological, managerial and organizational perspectives of past and current manufacturing organizations, which contribute to illuminate features and to identify core competencies of future industrial firms, which are in the pursuit of innovation and sustainable competitive advantage in the twenty‐first century.

Humans and organizations have limitations of computational capacity and information management. Such constraints are synonymous with bounded rationality. Therefore, in order to extend the human and organizational boundaries to more advanced models of cognition, this research proposes concepts of cognitive machines in organizations. From a micro point of view, what makes this research distinct is that, beyond people, it includes in the list of participants of the organization the cognitive machines. From a macro point of view, this paper relies on the premise that cognitive machines can improve the cognitive abilities of the organization. From such perspectives, it presents rationale and principles of a class of cognitive machines with capabilities to carry out complex cognitive tasks in organizations. It also introduces analyses of the cognitive machines in organizations through theories of bounded rationality, economic decision-making, and conflict resolution. The analyses indicate that these machines can solve or reduce intra-individual and group dysfunctional conflicts which arise from decision-making processes in the organization, and thus they can improve the degree of organizational cognition. From all these backgrounds, this research outlines implications of cognitive machines for organizations.

Humans and organizations have limitations of computational capacity and information management. Such constraints are synonymous with bounded rationality. Therefore, in order to extend the human and organizational boundaries to more advanced models of cognition, this research proposes concepts of cognitive machines in organizations. From a micro point of view, what makes this research distinct is that, beyond people, it includes in the list of participants of the organization the cognitive machines. From a macro point of view, this paper relies on the premise that cognitive machines can improve the cognitive abilities of the organization. From such perspectives, it presents rationale and principles of a class of cognitive machines with capabilities to carry out complex cognitive tasks in organizations. It also introduces analyses of the cognitive machines in organizations through theories of bounded rationality, economic decision-making, and conflict resolution. The analyses indicate that these machines can solve or reduce intra-individual and group dysfunctional conflicts which arise from decision-making processes in the organization, and thus they can improve the degree of organizational cognition. From all these backgrounds, this research outlines implications of cognitive machines for organizations.