0000000000010373
AUTHOR
Antero Karvonen
Challenge of tacit knowledge in acquiring information in cognitive mimetics
Intelligent technologies are rising. This is why methods for designing them are important. One approach is to study how people process information in carrying out intelligence demanding tasks and use this information in designing new technology solutions. This approach can be called cognitive mimetics. A problem in mimetics is to explicate tacit or subconscious knowledge. Here, we study a combination of thinking aloud in ship simulator driving and focus group commenting the solutions of subjects. On the ground of these early experiments, a multiple method combination seems to be the best way forward to solve problems of tacit or subconscious knowledge. peerReviewed
An ontology for cognitive mimetics
AI and autonomous systems are intended to replace people in several jobs. People have worked in these jobs being able to execute the required information processing. This implies that new technical artefacts must be able to perform equitably effective information processing. Thus, it makes sense to develop the analysis of human information processing in designing intelligent systems. This approach has been termed cognitive mimetics. This paper studies how it would be practical to gain knowledge about human information processing and organize this knowledge using ontologies.
Questions in Cognitive Mimetics
Human thinking advances through questions and answers. Any field of human endeavor is permeated by the presence of questions, answers and presuppositions. Questions have a kind of universality, whereby one can place the question marks on anything, including questions themselves. The process of asking the right questions about the right things and in the right way are key for the explication of an approach. Recently, we have begun thinking about an approach to the design of intelligent technology: Cognitive mimetics. In brief, the idea is to take inspiration of empirical human thinking in specific contexts to develop AI solutions. The purpose of this article is to question this approach from…
Human Digital Twins in Acquiring Information About Human Mental Processes for Cognitive Mimetics
Modern information technology makes it possible to redesign the ways people work. In the future, machines can carry out intelligence-requiring tasks, which previously were done by people. It is thus good to develop methodologies for designing intelligent systems. An example of such methods is cognitive mimetics, i.e. imitating human information processing. Today, machines cannot by themselves navigate in archipelagos. However, the fact that people can take care of ship steering and navigation means that there is an information process, which makes it possible to navigate ships. This information process takes place inside the minds of navigating people. If we are able to explicate the inform…
Cognitive Mimetics for AI Ethics : Tacit Knowledge, Action Ontologies and Problem Restructuring
Ethics and ethical information processing are an important problem for AI development. It is important for self-evident reasons, but also challenging in its’ implications and should be welcomed by designers and developers as an interesting technical challenge. This article explores AI ethics as a design problem and lays out how cognitive mimetics could be used a method for its design. AI ethics is conceptualized as a problem of implementation on the one hand, and as a problem of ethical contents on the other. From the viewpoint of human information processing, ethics becomes a special case of ethical information processing - one that has deep implications in terms of AI abilities and inform…
Types of Mimetics for the Design of Intelligent Technologies
Mimetic design means using a source in the natural or artificial worlds as an inspiration for technological solutions. It is based around the abstraction of the relevant operating principles in a source domain. This means that one must be able to identify the correct level of analysis and extract the relevant patterns. How this should be done is based on the type of source. From a mimetic perspective, if the design goal is intelligent technology, an obvious source of inspiration is human information processing, which we have called cognitive mimetics. This article offers some conceptual clarification on the nature of cognitive mimetics by contrasting it with biomimetics in the context of in…
Conceptual basis of cognitive mimetics for information engineering
Abstract Intelligent information processing is topical in modern technology design and development. The fundamental idea was developed by Turing as he made the first conceptual models of information-processing computers. Though it has practically never been noticed, Turing’s work was a model of how to mimic human intelligent information processes and generate technologies, which can carry out intelligent tasks. The design method can be called cognitive mimetics as it imitates human information processes to design technologies and their applications. One can use cognitive mimetics even in solving techno-ethical problems. This is why we think that cognitive mimetics are vital as a method to g…
Theory languages in designing artificial intelligence
The foundations of AI design discourse are worth analyzing. Here, attention is paid to the nature of theory languages used in designing new AI technologies because the limits of these languages can clarify some fundamental questions in the development of AI. We discuss three types of theory language used in designing AI products: formal, computational, and natural. Formal languages, such as mathematics, logic, and programming languages, have fixed meanings and no actual-world semantics. They are context- and practically content-free. Computational languages use terms referring to the actual world, i.e., to entities, events, and thoughts. Thus, computational languages have actual-world refer…
The Psychology of Thinking in Creating AI
The broad-scale emergence of AI in industry calls forth basic questions in terms of the knowledge bases and approaches relevant for its design. Engineering design has been mainly developed for electromechanical artifacts. In practice, this has meant that the scientific knowledge required for creating technical artifacts such as engines, cars, ships, cranes, telephones, radios, TVs, and simple data processing units has been natural science. However, one cannot find intelligent processes by means of physics and chemistry. Natural scientific phenomena follow their deterministic laws, but intelligence is based on selection and decision processes. The conceptual landscape of natural science is o…
Cognitive Mimetics and Human Digital Twins : Towards Holistic AI Design
AI is replacing and supporting people in many intelligence-requiring tasks. Therefore, it is essential to consider the conceptual grounds of designing future technical artefacts and technologies for practical use. We are developing two new practical design tools: cognitive mimetics and human digital twins for AI designers. Cognitive mimetics analyses human information processing to be mimicked by intelligent technologies. Human digital twins provide a tool for modelling what people do based on the results of cognitive mimetics. Together they provide a new way of designing intelligent technology in individual tasks and industrial contexts. nonPeerReviewed
Human digital twins and cognitive mimetic
Digital twins – digital models of technical systems and processes – have recently been introduced to work with complex industrial processes. Yet should such models concern only physical objects (as definitions of them often imply), or should users and other human beings also be included? Models that include people have been called human digital twins (HDTs); they facilitate more accurate analyses of technologies in practical use. The cognitive mimetic approach can be used to describe human interactions with technologies. This approach analyses human information processes such as perceiving and thinking to mimic how people process information in order to design intelligent technologies. The …