Challenge of Tacit Knowledge in Acquiring Information in Cognitive Mimetics

Saariluoma, Pertti; Karvonen, Antero; Wahlström, Mikael; Happonen, Kai; Puustinen, Ronny; Kujala, Tuomo

doi:10.1007/978-3-030-11051-2_35

Cited by 4 publications

(11 citation statements)

References 4 publications

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“…Specialists of human technology interaction will need to meet with this challenge on designing technologies with intelligent capacities. 39 Purpose of human-centred design is to create technological solutions easy to use and commit community of practices can support design in cyber training.…”

Section: Training and Exercise Designmentioning

confidence: 99%

Utilising Experiential and Organizational Learning Theories to Improve Human Performance in Cyber Training

Aaltola

Taitto²

2019

ISIJ

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Development of information technology and the globalization require constant investment in people. New and emerging technologies such as autonomous systems, machine learning and AI radically re-contextualize the human dimension of the organization. Strategic changes have revealed new critical vulnerabilities such as social media-based election meddling and disinformation campaigning with impact on the human aspects at state, societal, organizational and individual levels. Education and training raise the level of expertise, skills and competences and ensure better performance in complex cyber situations. Researchers have addressed assumptions, models, concepts and cognitive aspects of human performance in the cyber domain. However, the theories and approaches of human learning in training and exercises are only partly touched. New techniques for enhancing organizational cyber resilience to cyber-attacks are needed and they still lack sound theoretical foundations. This article aims to advance the discussion suggesting viewpoints on training and exercises in the cyber domain, taking into consideration specifics of skills in cyber security. It provides overview of theories of learning to better support human performance. Our critical interpretation enhances the comprehensive understanding of decision-making, learning theories, and design of cyber security training and exercises. Furthermore, our intention is to constructively promote discussion on current issues about human learning in cyber training and education and thus boost multidisciplinary studies to enhance cyber awareness.

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Section: Training and Exercise Designmentioning

confidence: 99%

Utilising Experiential and Organizational Learning Theories to Improve Human Performance in Cyber Training

Aaltola

Taitto²

2019

ISIJ

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“…A major line of research and inspiration for intelligent systems has been the information processing in humans which we call cognitive mimetics [2], [3], [4]. Early AI was a collaborative effort between neuroscience, computer science and psychology [24] united under the topic of cognitive science.…”

Section: Types Of Mimetics For Intelligent Technologymentioning

confidence: 99%

“…Through empirical inquiry we may draw a rich description of the domainspecific information environment in which the action is embedded. Note that this inquiry is not trivial, because much of the information is tacit and unconscious [4]. The entry-point for cognitive mimetics are the representations which organize and structure information processes.…”

Section: Cognition As a Source Of Mimickingmentioning

confidence: 99%

“…However, in creating intelligent technologies designers can use existing organizational and individual information processes as the source of ideas. Designing intelligent systems by utilizing existing human information processes as the source of solutions we have termed 'cognitive mimetics' [2], [3], [4]. Cognitive mimetics differs from typical and established biomimetics as it has different source of mimicking: human shared and individual cognitive processes, as well as the mental contents, representations, and constraints that establish the boundaries and forms it takes.…”

Section: Introductionmentioning

confidence: 99%

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Types of Mimetics for the Design of Intelligent Technologies

Karvonen

Kujala

Saariluoma

2019

Human Systems Engineering and Design II

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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 intelligent technology. We offer a two-part ontology for cognitive mimetics, suggest an approach and discuss possible implications for AI in general.

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“…The second is where to look for the basis for ethical reasoning -where should "ethics modules" derive their contents and their basis for reasoning? This article offers a conceptual discussion on these issues and then lays out how cognitive mimetics [2][3][4][5][6] can be used in the context of AI ethics.…”

Section: Introductionmentioning

confidence: 99%

Cognitive Mimetics for AI Ethics: Tacit Knowledge, Action Ontologies and Problem Restructuring

Karvonen

2020

Culture and Computing

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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 information contents. Here we focus on ethical information processing as a property of the system (rather as a general constraint on it). We explore three specific concepts relevant for cognitive mimetics from the perspective of ethics: tacit knowledge, ontologies, and problem restructuring. We close with a general discussion on the difference between abilities and mental contents noted as relevant in previous articles on cognitive mimetics and reiterate its importance in this context as well.

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Challenge of Tacit Knowledge in Acquiring Information in Cognitive Mimetics

Cited by 4 publications

References 4 publications

Utilising Experiential and Organizational Learning Theories to Improve Human Performance in Cyber Training

Utilising Experiential and Organizational Learning Theories to Improve Human Performance in Cyber Training

Types of Mimetics for the Design of Intelligent Technologies

Cognitive Mimetics for AI Ethics: Tacit Knowledge, Action Ontologies and Problem Restructuring

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