Extending Naturalistic Decision Making to Complex Organizations: A Dynamic Model of Situated Cognition

2006 ◽  
Vol 27 (7) ◽  
pp. 989-1009 ◽  
Author(s):  
Lawrence G. Shattuck ◽  
Nita Lewis Miller
Keyword(s):  
Complex System ◽  
Decision Making ◽  
Complex Systems ◽  
Dynamic Model ◽  
Situated Cognition ◽  
Theoretical Perspective ◽  
Complex Domain ◽  
Fishing Vessel ◽  
Naturalistic Decision Making ◽  
Us Navy

Naturalistic decision making (NDM) has become established as a methodological and theoretical perspective. It describes how practitioners actually make decisions in complex domains. However, NDM theories tend to focus on the human agents in the system. We extend the NDM perspective to include the technological agents in complex systems and introduce the dynamic model of situated cognition. We describe the general characteristics of NDM and the field of situated cognition, and provide a detailed description of our model. We then apply the model to a recent accident in which a US Navy submarine (USS Greeneville) collided with a Japanese fishing vessel ( Ehime Maru). The discussion of the accident illustrates how decisions made are often a result of the interaction between a variety of technological and human agents and how errors introduced into the complex system can propagate through it in unintended ways. We argue that the dynamic model of situated cognition can be used to describe activities in virtually any complex domain.

scholarly journals Applying a Dynamic Model of Situated Cognition to the Investigation of Mishaps

2005 ◽  
Vol 49 (3) ◽  
pp. 219-223 ◽  
Author(s):  
Nita Lewis Miller ◽  
Lawrence G. Shattuck
Keyword(s):  
Complex Systems ◽  
Dynamic Model ◽  
Human Error ◽  
Situated Cognition ◽  
Organizational Factors ◽  
Operator Error ◽  
Military Command ◽  
And Control ◽  
Analysis Of Error ◽  
The U.S

Complex systems will, inevitably, experience failures. The cause of these failures or mishaps may be labeled 'operator error,' but often they are actually caused by the confluence of technological, situational, individual, and organizational factors. Several models and theories of human error have been proposed over the years and are reviewed in this paper. The authors propose another model, the Dynamic Model of Situated Cognition (DMSC), to explain how complex systems fail. Miller and Shattuck (2004) developed the DMSC in an effort to link technological aspects of a system to the perceptual and cognitive aspects of that system. They illustrated the model by applying it to the USS Stark incident and to a military command and control simulation (Shattuck and Miller, 2004). The model also appears to have utility as a retrospective explanatory tool to identify when and where things went wrong. In this paper, the authors describe the DMSC as it relates to the analysis of error in complex systems and apply it to the February 2001 mishap in which the U.S. Navy submarine USS Greeneville collided with the Japanese motor vessel Ehime Maru off the coast of Oahu, Hawaii.

scholarly journals Iterative Filling and Updating of Information When Managing a Hierarchical Database

2020 ◽  
Vol 10 (2) ◽  
pp. 93-101
Author(s):  
T.I. Korotkova ◽  
A.A. Mokhov
Keyword(s):  
Complex System ◽  
Decision Making ◽  
Optimal Control ◽  
Complex Systems ◽  
Hierarchical Structure ◽  
Software Package ◽  
Database Management ◽  
Amount Of Information ◽  
The Hierarchical Structure ◽  
Decision Making System

The choice of optimal control in complex systems involves handling large amounts of information. The database of such a decision-making system has a hierarchical structure. The article describes the principle of filling and updating information when managing a hierarchical database of a complex system in the presence of uncertain factors. Uncertain factors are present in the criteria for the effectiveness of a complex system and in the criteria for its subsystems. The hierarchical structure of the decision-making system has a level of coordination of decisions of local subsystems. Coordination in a complex system is carried out with a step of discreteness. This allows you to use the iterative principle of filling the database and updating it. Uncertainty conditions significantly increase the amount of information processed. As a result, a hierarchical software package for database management is built.

Perceived Effectiveness of Artificial Intelligence based Decision Support System in a Clinical Setting: A Systematic Literature Review (Preprint)

2020 ◽  
Author(s):  
Avishek Choudhury
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Decision Support ◽  
Literature Review ◽  
Decision Support System ◽  
Support System ◽  
Clinical Setting ◽  
Clinical Decision Making ◽  
Theoretical Perspective ◽  
Care Providers

UNSTRUCTURED Objective: The potential benefits of artificial intelligence based decision support system (AI-DSS) from a theoretical perspective are well documented and perceived by researchers but there is a lack of evidence showing its influence on routine clinical practice and how its perceived by care providers. Since the effectiveness of AI systems depends on data quality, implementation, and interpretation. The purpose of this literature review is to analyze the effectiveness of AI-DSS in clinical setting and understand its influence on clinician’s decision making outcome. Materials and Methods: This review protocol follows the Preferred Reporting Items for Systematic Reviews and Meta- Analyses reporting guidelines. Literature will be identified using a multi-database search strategy developed in consultation with a librarian. The proposed screening process consists of a title and abstract scan, followed by a full-text review by two reviewers to determine the eligibility of articles. Studies outlining application of AI based decision support system in a clinical setting and its impact on clinician’s decision making, will be included. A tabular synthesis of the general study details will be provided, as well as a narrative synthesis of the extracted data, organised into themes. Studies solely reporting AI accuracy an but not implemented in a clinical setting to measure its influence on clinical decision making were excluded from further review. Results: We identified 8 eligible studies that implemented AI-DSS in a clinical setting to facilitate decisions concerning prostate cancer, post traumatic stress disorder, cardiac ailment, back pain, and others. Five (62.50%) out of 8 studies reported positive outcome of AI-DSS. Conclusion: The systematic review indicated that AI-enabled decision support systems, when implemented in a clinical setting and used by clinicians might not ensure enhanced decision making. However, there are very limited studies to confirm the claim that AI based decision support system can uplift clinicians decision making abilities.

Exploring the Differences in Macrocognition Between Experts and Non-CHD Experts Managing Congenital Heart Disease (CHD)

2021 ◽  
Vol 10 (1) ◽  
pp. 335-339
Author(s):  
Azadeh Assadi ◽  
Peter C. Laussen ◽  
Patricia Trbovich
Keyword(s):  
Decision Making ◽  
Emergency Medicine ◽  
Congenital Heart Disease ◽  
Heart Disease ◽  
Congenital Heart ◽  
Pediatric Emergency ◽  
Acute Management ◽  
Naturalistic Decision Making ◽  
The Face

Background and aims: Children with congenital heart disease (CHD) are at risk of deterioration in the face of common childhood illnesses, and their resuscitation and acute management is often best achieved with the guidance of CHD experts. Access to such expertise may be limited outside specialty heart centers and the fragility of these patients is cause for discomfort among many emergency medicine physicians. An understanding of the differences in macrocognition of these clinicians could shed light on some of the causes of discomfort and facilitate the development of a sociotechnological solution to this problem. Methods: Cardiac intensivists (CHD experts) and pediatric emergency medicine physicians (non-CHD experts) in a major academic cardiac center were interviewed using the critical decision method. Interview transcripts were coded deductively based on Klein’s macrocognitive framework and inductively to allow for new or modified characterization of dimensions. Results: While both CHD-experts and non-CHD experts relied on the macrocognitive functions of sensemaking, naturalistic decision making and detecting problems, the specific data and mental models used to understand the patients and course of therapy differed between CHD-experts and non-CHD experts. Conclusion: Characterization of differences between the macrocognitive processes of CHD experts and non-CHD experts can inform development of sociotechnological solutions to augment decision making pertaining to the acute management of pediatric CHD patients.

scholarly journals Integrating Value Considerations in the Decision Making for the Design of Biorefineries

2020 ◽  
Vol 26 (6) ◽  
pp. 2927-2955
Author(s):  
Mar Palmeros Parada ◽  
Lotte Asveld ◽  
Patricia Osseweijer ◽  
John Alexander Posada
Keyword(s):  
Decision Making ◽  
Complex Systems ◽  
Research And Development ◽  
Design Process ◽  
Design Decision ◽  
Value Sensitive Design ◽  
Design Practice ◽  
Novel Approach ◽  
Design Alternatives ◽  
Biobased Production

AbstractBiobased production has been promoted as a sustainable alternative to fossil resources. However, controversies over its impact on sustainability highlight societal concerns, value tensions and uncertainties that have not been taken into account during its development. In this work, the consideration of stakeholders’ values in a biorefinery design project is investigated. Value sensitive design (VSD) is a promising approach to the design of technologies with consideration of stakeholders’ values, however, it is not directly applicable for complex systems like biorefineries. Therefore, some elements of VSD, such as the identification of relevant values and their connection to a technology’s features, are brought into biorefinery design practice. Midstream modulation (MM), an approach to promoting the consideration of societal aspects during research and development activities, is applied to promote reflection and value considerations during the design decision making. As result, it is shown that MM interventions during the design process led to new design alternatives in support of stakeholders' values, and allowed to recognize and respond to emerging value tensions within the scope of the project. In this way, the present work shows a novel approach for the technical investigation of VSD, especially for biorefineries. Also, based on this work it is argued that not only reflection, but also flexibility and openness are important for the application of VSD in the context of biorefinery design.

Naturalistic Decision Making in High Performance Team Sport Coaching

2015 ◽  
Vol 2 (2) ◽  
pp. 152-168 ◽  
Author(s):  
Stephen Harvey ◽  
John William Baird Lyle ◽  
Bob Muir
Keyword(s):  
Decision Making ◽  
High Performance ◽  
Recent Literature ◽  
Critical Factors ◽  
Naturalistic Decision Making ◽  
Problem Framing ◽  
Stimulated Recall ◽  
Suitable Framework ◽  
And Training

A defining element of coaching expertise is characterised by the coach’s ability to make decisions. Recent literature has explored the potential of Naturalistic Decision Making (NDM) as a useful framework for research into coaches’ in situ decision making behaviour. The purpose of this paper was to investigate whether the NDM paradigm offered a valid mechanism for exploring three high performance coaches’ decision-making behaviour in competition and training settings. The approach comprised three phases: 1) existing literature was synthesised to develop a conceptual framework of decision-making cues to guide and shape the exploration of empirical data; 2) data were generated from stimulated recall procedures to populate the framework; 3) existing theory was combined with empirical evidence to generate a set of concepts that offer explanations for the coaches’ decision-making behaviour. Findings revealed that NDM offered a suitable framework to apply to coaches’ decision-making behaviour. This behaviour was guided by the emergence of a slow, interactive script that evolves through a process of pattern recognition and/or problem framing. This revealed ‘key attractors’ that formed the initial catalyst and the potential necessity for the coach to make a decision through the breaching of a ‘threshold’. These were the critical factors for coaches’ interventions.

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