Cognitive systems engineering

Last updated

Cognitive systems engineering (CSE) is a field of study that examines the intersection of people, work, and technology, with a focus on safety-critical systems. The central tenet of cognitive systems engineering is that it views a collection of people and technology as a single unit that is capable of cognitive work, which is called a joint cognitive system. [1]

Contents

CSE draws on concepts from cognitive psychology and cognitive anthropology, such as Edwin Hutchins's distributed cognition, James Gibson's ecological theory of visual perception, Ulric Neisser's perceptual cycle, and William Clancey's situated cognition. [2] CSE techniques include cognitive task analysis [3] and cognitive work analysis. [4]

History

Cognitive systems engineering emerged in the wake of the Three Mile Island (TMI) accident. [5] At the time, existing theories about safety were unable to explain how the operators at TMI could be confused about what was actually happening inside of the plant. [6]

Following the accident, Jens Rasmussen did early research on cognitive aspects of nuclear power plant control rooms. [7] This work influenced a generation of researchers who would later come to be associated with cognitive systems engineering, including Morten Lind, Erik Hollnagel, and David Woods. [5]

Following the publication of a textbook on cognitive systems engineering by Kim Vicente in 1999 the techniques employed to establish a cognitive work analysis (CWA) were used to aid the design of any kind of system were humans have to interact with technology. The tools outlined by Vicente were not tried and tested, and there are few if any published accounts of the five phases of analysis being implemented. [8]

"Cognitive systems engineering" vs "Cognitive engineering"

The term "cognitive systems engineering" was introduced in a 1983 paper by Hollnagel and Woods. [1]

Although the term cognitive engineering had already been introduced by Don Norman, Hollnagel and Woods deliberately introduced new terminology. They were unhappy with the framing of the term cognitive engineering, which they felt focused too much on improving the interaction between humans and computers, through the application of cognitive science. Instead, Hollnagel and Woods wished to emphasize a shift in focus from human-computer interaction to joint cognitive systems as the unit of analysis. [9]

Despite the intention by Hollnagel and Woods to distinguish cognitive engineering from cognitive systems engineering, some researchers continue to use the two terms interchangeably. [10]

Themes

Joint cognitive systems

As mentioned in the Origins section above, one of the key tenets of cognitive systems engineering is that the base unit of analysis is the joint cognitive system. Instead of viewing cognitive tasks as being done only by individuals, CSE views cognitive work as being accomplished by a collection of people coordinating with each other and using technology to jointly perform cognitive work as a system. [1]

Studying work in context

CSE researchers focus their studies on work in situ, as opposed to studying how work is done in controlled laboratory environments. [11] This research approach, known as macrocognition, is similar to the one taken by naturalistic decision-making. Examples of studies of work done in context include Julian Orr's ethnographic studies of copy machine technicians, [12] Lucy Suchman's ethnographic studies of how people use photocopiers, [13] Diane Vaughan's study of engineering work at NASA in the wake of the Space Shuttle Challenger disaster, [14] and Scott Snook's study of military work in the wake of the 1994 Black Hawk shootdown incident. [15]

Coping with complexity

A general thread that runs through cognitive systems engineering research is the question of how to design joint cognitive systems that can deal effectively with complexity, including common patterns in how such systems can fail to deal effectively with complexity. [16] [11] [17] [18]

Anomaly response

As mentioned in the Origins section above, CSE researchers were influenced by TMI. One specific application of coping with complexity is the work that human operators must do when they are supervising a process such as nuclear power plant, and they must then deal with a problem that arises. This work is sometimes known as anomaly response [11] [19] or dynamic fault management. [20] This type of work often involves uncertainty, quickly changing conditions, and risk tradeoffs in deciding what remediation actions to take.

Coordination

Because joint cognitive systems involve multiple agents that must work together to complete cognitive tasks, coordination is another topic of interest in CSE. One specific example is the notion of common ground [21] and its implications for building software that can contribute effectively as agents in a joint cognitive system. [22]

Cognitive artifacts

CSE researchers study how people use technology to support cognitive work and coordinate this work across multiple people. Examples of such cognitive artifacts, which have been studied by researchers, include "the bed book" used in intensive care units, [23] "voice loops" used in space operations, [24] "speed bugs" used in aviation, [25] drawings and sketches in engineering work, [26] and the various tools used in marine navigation. [27]

Of particular interest to CSE researchers is how computer-based tools influence joint cognitive work, [28] in particular the impact of automation, [29] and computerized interfaces used by system operators. [30]

Books

See also

Related Research Articles

<span class="mw-page-title-main">Cognitive science</span> Interdisciplinary scientific study of cognitive processes

Cognitive science is the interdisciplinary, scientific study of the mind and its processes with input from linguistics, psychology, neuroscience, philosophy, computer science/artificial intelligence, and anthropology. It examines the nature, the tasks, and the functions of cognition. Cognitive scientists study intelligence and behavior, with a focus on how nervous systems represent, process, and transform information. Mental faculties of concern to cognitive scientists include language, perception, memory, attention, reasoning, and emotion; to understand these faculties, cognitive scientists borrow from fields such as linguistics, psychology, artificial intelligence, philosophy, neuroscience, and anthropology. The typical analysis of cognitive science spans many levels of organization, from learning and decision to logic and planning; from neural circuitry to modular brain organization. One of the fundamental concepts of cognitive science is that "thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures."

<span class="mw-page-title-main">Systems engineering</span> Interdisciplinary field of engineering

Systems engineering is an interdisciplinary field of engineering and engineering management that focuses on how to design, integrate, and manage complex systems over their life cycles. At its core, systems engineering utilizes systems thinking principles to organize this body of knowledge. The individual outcome of such efforts, an engineered system, can be defined as a combination of components that work in synergy to collectively perform a useful function.

<span class="mw-page-title-main">Cognition</span> Act or process of knowing

Cognition is the "mental action or process of acquiring knowledge and understanding through thought, experience, and the senses". It encompasses all aspects of intellectual functions and processes such as: perception, attention, thought, imagination, intelligence, the formation of knowledge, memory and working memory, judgment and evaluation, reasoning and computation, problem-solving and decision-making, comprehension and production of language. Cognitive processes use existing knowledge and discover new knowledge.

Distributed cognition is an approach to cognitive science research that was developed by cognitive anthropologist Edwin Hutchins during the 1990s.

<span class="mw-page-title-main">Dynamical systems theory</span> Area of mathematics used to describe the behavior of complex dynamical systems

Dynamical systems theory is an area of mathematics used to describe the behavior of complex dynamical systems, usually by employing differential equations or difference equations. When differential equations are employed, the theory is called continuous dynamical systems. From a physical point of view, continuous dynamical systems is a generalization of classical mechanics, a generalization where the equations of motion are postulated directly and are not constrained to be Euler–Lagrange equations of a least action principle. When difference equations are employed, the theory is called discrete dynamical systems. When the time variable runs over a set that is discrete over some intervals and continuous over other intervals or is any arbitrary time-set such as a Cantor set, one gets dynamic equations on time scales. Some situations may also be modeled by mixed operators, such as differential-difference equations.

Human reliability is related to the field of human factors and ergonomics, and refers to the reliability of humans in fields including manufacturing, medicine and nuclear power. Human performance can be affected by many factors such as age, state of mind, physical health, attitude, emotions, propensity for certain common mistakes, errors and cognitive biases, etc.

Neuroinformatics is the field that combines informatics and neuroscience. Neuroinformatics is related with neuroscience data and information processing by artificial neural networks. There are three main directions where neuroinformatics has to be applied:

Cognitive ergonomics is a scientific discipline that studies, evaluates, and designs tasks, jobs, products, environments and systems and how they interact with humans and their cognitive abilities. It is defined by the International Ergonomics Association as "concerned with mental processes, such as perception, memory, reasoning, and motor response, as they affect interactions among humans and other elements of a system. Cognitive ergonomics is responsible for how work is done in the mind, meaning, the quality of work is dependent on the persons understanding of situations. Situations could include the goals, means, and constraints of work. The relevant topics include mental workload, decision-making, skilled performance, human-computer interaction, human reliability, work stress and training as these may relate to human-system design." Cognitive ergonomics studies cognition in work and operational settings, in order to optimize human well-being and system performance. It is a subset of the larger field of human factors and ergonomics.

Human error is an action that has been done but that was "not intended by the actor; not desired by a set of rules or an external observer; or that led the task or system outside its acceptable limits". Human error has been cited as a primary cause contributing factor in disasters and accidents in industries as diverse as nuclear power, aviation, space exploration, and medicine. Prevention of human error is generally seen as a major contributor to reliability and safety of (complex) systems. Human error is one of the many contributing causes of risk events.

Augmented cognition is an interdisciplinary area of psychology and engineering, attracting researchers from the more traditional fields of human-computer interaction, psychology, ergonomics and neuroscience. Augmented cognition research generally focuses on tasks and environments where human–computer interaction and interfaces already exist. Developers, leveraging the tools and findings of neuroscience, aim to develop applications which capture the human user's cognitive state in order to drive real-time computer systems. In doing so, these systems are able to provide operational data specifically targeted for the user in a given context. Three major areas of research in the field are: Cognitive State Assessment (CSA), Mitigation Strategies (MS), and Robust Controllers (RC). A subfield of the science, Augmented Social Cognition, endeavours to enhance the "ability of a group of people to remember, think, and reason."

Nancy G. Leveson is an American specialist in system and software safety and a Professor of Aeronautics and Astronautics at MIT, United States.

In psychology, the human mind is considered to be a cognitive miser due to the tendency of humans to think and solve problems in simpler and less effortful ways rather than in more sophisticated and effortful ways, regardless of intelligence. Just as a miser seeks to avoid spending money, the human mind often seeks to avoid spending cognitive effort. The cognitive miser theory is an umbrella theory of cognition that brings together previous research on heuristics and attributional biases to explain when and why people are cognitive misers.

Macrocognition indicates a descriptive level of cognition performed in natural instead of artificial (laboratory) environments. This term is reported to have been coined by Pietro Cacciabue and Erik Hollnagel in 1995. However, it is also reported that it was used in the 1980s in European Cognitive Systems Engineering research. Possibly the earliest reference is the following, although it does not use the exact term "macrocognition":

A macro-theory is a theory which is concerned with the obvious regularities of human experience, rather than with some theoretically defined unit. To refer to another psychological school, it would correspond to a theory at the level of Gestalten. It resembles Newell’s suggestion for a solution that would analyse more complex tasks. However, the idea of a macro-theory does not entail an analysis of the mechanistic materialistic kind which is predominant in cognitive psychology. Thus we should have a macro-theory of remembering rather than of memory, to say nothing of short-term memory, proactive inhibition release, or memory scanning. To take another example, we should have a macro-theory of attending, rather than a mini-theory of attention, or micro-theories of limited channel capacities or logarithmic dependencies in disjunctive reaction times. This would ease the dependence on the information processing analogy, but not necessarily lead to an abandonment of the information processing terminology, the Flowchart, or the concept of control structures. The meta-technical sciences can contribute to a psychology of cognition as well as to cognitive psychology. What should be abandoned is rather the tendency to think in elementaristic terms and to increase the plethora of mini-and micro-theories. ... To conclude, if the psychological study of cognition shall have a future that is not a continued description of human information processing, its theories must be at what we have called the macro-level. This means that they must correspond to the natural units of experience and consider these in relation to the regularities of human experience, rather than as manifestations of hypothetical information processing mechanisms in the brain. A psychology should start at the level of natural units in human experience and try to work upwards towards the level of functions and human action, rather than downwards towards the level of elementary information processes and the structure of the IPS.

David Charles Gooding was a Professor of History and Philosophy of Science, and the Director of the Science Studies Centre, at the University of Bath, UK. He was President of the History of Science Section of the BAAS (2002–2003).

<span class="mw-page-title-main">Human factors and ergonomics</span> Designing systems to suit their users

Human factors and ergonomics is the application of psychological and physiological principles to the engineering and design of products, processes, and systems. Primary goals of human factors engineering are to reduce human error, increase productivity and system availability, and enhance safety, health and comfort with a specific focus on the interaction between the human and equipment.

<span class="mw-page-title-main">Guy André Boy</span>

Guy André Boy is a French and American scientist and engineer, Fellow of the International Council on Systems Engineering (INCOSE), the Air and Space Academy and the International Academy of Astronautics. He is FlexTech chair holder and university professor at CentraleSupélec and ESTIA Institute of Technology. He was university professor and dean (2015–2017) at Florida Institute of Technology (FIT), where he created the Human-Centered Design Institute in 2010. He was senior research scientist at Florida Institute for Human and Machine Cognition (IHMC). He was Chief Scientist for Human-Centered Design at NASA Kennedy Space Center (KSC) from 2010 to 2016. He is known for his work on intelligent assistance, cognitive function analysis, human-centered design (HCD), orchestration of life-critical systems, tangible interactive systems and human systems integration.

Cognitive computing refers to technology platforms that, broadly speaking, are based on the scientific disciplines of artificial intelligence and signal processing. These platforms encompass machine learning, reasoning, natural language processing, speech recognition and vision, human–computer interaction, dialog and narrative generation, among other technologies.

<span class="mw-page-title-main">Alan Yuille</span> English academic

Alan Yuille is a Bloomberg Distinguished Professor of Computational Cognitive Science with appointments in the departments of Cognitive Science and Computer Science at Johns Hopkins University. Yuille develops models of vision and cognition for computers, intended for creating artificial vision systems. He studied under Stephen Hawking at Cambridge University on a PhD in theoretical physics, which he completed in 1981.

David D. Woods is an American safety systems researcher who studies human coordination and automation issues in a wide range safety-critical fields such as nuclear power, aviation, space operations, critical care medicine, and software services. He is one of the founding researchers of the fields of cognitive systems engineering and resilience engineering.

Resilience engineering is a subfield of safety science research that focuses on understanding how complex adaptive systems cope when encountering a surprise. The term resilience in this context refers to the capabilities that a system must possess in order to deal effectively with unanticipated events. Resilience engineering examines how systems build, sustain, degrade, and lose these capabilities.

References

  1. 1 2 3 Hollnagel, Erik; Woods, David D. (June 1983). "Cognitive Systems Engineering: New wine in new bottles". International Journal of Man-Machine Studies. 18 (6): 583–600. doi:10.1016/S0020-7373(83)80034-0. S2CID   15398274.
  2. Flach, John (2020). A meaning processing approach to cognition : what matters?. Fred Voorhorst. New York, NY. ISBN   978-0-367-40428-4. OCLC   1117930294.{{cite book}}: CS1 maint: location missing publisher (link)
  3. Crandall, Beth (2006). Working minds : a practitioner's guide to cognitive task analysis. Gary A. Klein, Robert R. Hoffman. Cambridge, Mass.: MIT Press. ISBN   978-0-262-27092-2. OCLC   76064684.
  4. Vicente, Kim J. (1999). Cognitive work analysis : toward safe, productive, and healthy computer-based work. Mahwah, N.J.: Lawrence Erlbaum Associates. ISBN   0-585-16171-2. OCLC   44961122.
  5. 1 2 Klein, G.; Wiggins, S.; Deal, S. (March 2008). "Cognitive Systems Engineering: The Hype and the Hope". Computer. 41 (3): 95–97. doi:10.1109/MC.2008.81. ISSN   0018-9162. S2CID   38587194.
  6. Cook, Richard (2014-02-05), 1. It all started at TMI, 1979 , retrieved 2022-09-23
  7. Jens Rasmussen (1986). Information processing and human-machine interaction : an approach to cognitive engineering. North-Holland. ISBN   0444009876. OCLC   13792295.
  8. Ann M. Bisantz; Catherine M. Burns, eds. (2016). Applications of Cognitive Work Analysis. CRC Press. pp. 1–2. ISBN   9781420063059.
  9. Philip J. Smith; Robert R. Hoffman (2018). Cognitive systems engineering : the future for a changing world. CRC Press, Taylor & Francis. ISBN   9781472430496. OCLC   987070476.
  10. DOWELL, JOHN; LONG, JOHN (1998-02-01). "Target Paper: Conception of the cognitive engineering design problem". Ergonomics. 41 (2): 126–139. doi:10.1080/001401398187125. ISSN   0014-0139.
  11. 1 2 3 Woods, D. (2019). JOINT COGNITIVE SYSTEMS : patterns in cognitive systems engineering. [Place of publication not identified]: CRC Press. ISBN   978-0-367-86415-6. OCLC   1129755331.
  12. Orr, Julian E. (2016). Talking about Machines : an Ethnography of a Modern Job. Cornell University Press. ISBN   978-1-5017-0740-7. OCLC   1030353116.
  13. Suchman, Lucy (2009). Human-machine reconfigurations : plans and situated actions. Cambridge Univ. Press. ISBN   978-0-521-85891-5. OCLC   902661378.
  14. Vaughan, Diane (4 January 2016). The Challenger launch decision : risky technology, culture, and deviance at NASA. University of Chicago Press. ISBN   978-0-226-34682-3. OCLC   944938820.
  15. A., Snook, Scott (2011). Friendly Fire : the Accidental Shootdown of U.S. Black Hawks over Northern Iraq. Princeton University Press. ISBN   978-1-4008-4097-7. OCLC   749265018.{{cite book}}: CS1 maint: multiple names: authors list (link)
  16. Hollnagel, Erik (2005). Joint cognitive systems : foundations of cognitive systems engineering. David D. Woods. Boca Raton, FL: Taylor & Francis. ISBN   0-8493-2821-7. OCLC   309875728.
  17. Rasmussen, Jens; Lind, Morten (1981). "Coping with complexity" (PDF). Risø-M (2293). Risø National Laboratory.{{cite journal}}: Cite journal requires |journal= (help)
  18. Hollnagel, Erik (2012-09-01). "Coping with complexity: past, present and future". Cognition, Technology & Work. 14 (3): 199–205. doi:10.1007/s10111-011-0202-7. ISSN   1435-5566. S2CID   15222531.
  19. "Cognitive Work of Hypothesis Exploration During Anomaly Response - ACM Queue". queue.acm.org. Retrieved 2022-09-24.
  20. WOODS, DAVID D. (1995-11-01). "The alarm problem and directed attention in dynamic fault management". Ergonomics. 38 (11): 2371–2393. doi:10.1080/00140139508925274. ISSN   0014-0139.
  21. Klein, Gary; Feltovich, Paul J.; Bradshaw, Jeffrey M.; Woods, David D. (2005-06-27), "Common Ground and Coordination in Joint Activity", Organizational Simulation, Hoboken, NJ, USA: John Wiley & Sons, Inc., pp. 139–184, doi:10.1002/0471739448.ch6, ISBN   9780471739449 , retrieved 2022-09-24
  22. Klien, G.; Woods, D.D.; Bradshaw, J.M.; Hoffman, R.R.; Feltovich, P.J. (November 2004). "Ten challenges for making automation a "team player" in joint human-agent activity". IEEE Intelligent Systems. 19 (6): 91–95. doi:10.1109/MIS.2004.74. ISSN   1941-1294. S2CID   27049933.
  23. "BEING BUMPABLE (by R. I. Cook)", Joint Cognitive Systems, CRC Press, pp. 33–46, 2006-03-27, doi:10.1201/9781420005684-8, ISBN   978-0-429-12766-3 , retrieved 2022-09-24
  24. Patterson, Emily S.; Watts-Perotti*, Jennifer; Woods, David D. (December 1999). "Voice Loops as Coordination Aids in Space Shuttle Mission Control". Computer Supported Cooperative Work (CSCW). 8 (4): 353–371. doi:10.1023/A:1008722214282. ISSN   0925-9724. PMID   12269347. S2CID   5341838.
  25. Hutchins, Edwin (July 1995). "How a Cockpit Remembers Its Speeds". Cognitive Science. 19 (3): 265–288. doi: 10.1207/s15516709cog1903_1 . ISSN   0364-0213. S2CID   9409426.
  26. Henderson, Kathryn (October 1991). "Flexible Sketches and Inflexible Data Bases: Visual Communication, Conscription Devices, and Boundary Objects in Design Engineering". Science, Technology, & Human Values. 16 (4): 448–473. doi:10.1177/016224399101600402. ISSN   0162-2439. S2CID   111281029.
  27. Hutchins, Edwin (1995). Cognition in the wild. Cambridge, Mass.: MIT Press. ISBN   978-0-262-27597-2. OCLC   44965743.
  28. Henderson, Kathryn (1999). On line and on paper : visual representations, visual culture, and computer graphics in design engineering. Cambridge, Mass.: MIT Press. ISBN   978-0-262-27525-5. OCLC   42856204.
  29. Bainbridge, Lisanne (1983-11-01). "Ironies of automation". Automatica. 19 (6): 775–779. doi:10.1016/0005-1098(83)90046-8. ISSN   0005-1098. S2CID   12667742.
  30. Woods, David D. (September 1984). "Visual momentum: a concept to improve the cognitive coupling of person and computer". International Journal of Man-Machine Studies. 21 (3): 229–244. doi:10.1016/S0020-7373(84)80043-7.

Journals