COGNITIVE ERGONOMICS IN HIGHLY RELIABLE SYSTEMS

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Kenneth Dale Lang
5 years ago
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1 Università degli studi di Genova Facoltà di Scienze della Formazione COGNITIVE ERGONOMICS IN HIGHLY RELIABLE SYSTEMS Fabrizio Bracco*, Luciano Pisano #, Giuseppe Spinelli* *University of Genoa, Dept. of Anthropological Sciences - DISA, Unit of Psychology, corso A. Podestà, Genoa, Italy. Tel. (+39) , fax (+39) # Airline pilot Corresponding author: Fabrizio Bracco, bracco@nous.unige.it Workshop Human Factors in Ship Design Genova, October 6 th 2005

2 Abstract Human cognitive system is the key point in a wider field where technology, psychology and organization meet. Our strength is at the same time our weakness: we are flexible but fallible, instead of machines, less fallible, but more rigid. Cognitive ergonomics emerges as a feasible perspective to face with these issues. Specifically, we point to High Reliability Systems (HRS), i.e. those activities where the cost of a failure is greater than the lesson learned. Perfect examples of HRS are transportations (aircrafts, ships, trains, etc.) and industrial activities (e.g. power plants). The aim of future research is to build a stronger integration among the several actors in HRS, keeping in mind that the human factor is, and has to be, the core of a multidisciplinary approach. As Alan Turing once said: if a machine is expected to be intelligent, it will not be error-free; if it has to be error-free, it will not be intelligent.

3 Transportations as dynamic complex systems We define a system as the organization of elements or of other subsystems, each with its specific function, but all directed towards a broader goal.

4 Transportations as dynamic complex systems Dynamicity: Continually changing environment Feedback loop in changes between system and environment system environment

5 Transportations as dynamic complex systems Complexity: Unpredictable interactions among system s elements Correct functioning Element 1 Element 2 Bad interaction error Correct functioning

6 Transportations as dynamic complex systems or High Reliability Organizations - HRO Systems where the cost of a failure is greater than the advantage of the lesson learned The development CANNOT be that of trial-and-error

7 The Turing Dilemma if a machine is expected to infallible, it will not be intelligent; if it is expected to be intelligent, it will not be infallible. It is valid for all complex systems, also for maritime transportations

8 The Human Factor in the Turing Dilemma Automation Reliable but rigid and contextinsensitive Human Element Flexible and creative but fallible Automation errors solved by humans safety Human errors solved by automation Unsolved automation errors accident Unsolved human errors

9 From: Swiss Re: Natural catastrophes and man-made disasters in 2004: more than fatalities, record insured losses, Sigma, 1, (2005).

10 From: Swiss Re: Natural catastrophes and man-made disasters in 2004: more than fatalities, record insured losses, Sigma, 1, (2005). Miscellaneous 20% Collapse of buildings/bridges 3% Natural catastrophes 36% Mining accidents 4% Rail disasters 6% Shipping disasters 14% Major fires, explosions 13% Aviation disasters 4%

11 Costs in maritime industry due to failures and errors Source:

12 The Human Factor in the Turing Dilemma The human being has to be considered both the strong and the weak aspect of a complex system It is impossible to avoid the human presence in the system We have to study human potentials and limits by means of COGNITIVE ERGONOMICS

Cognitive Ergonomics It is the study of cognition in the workplace with a view to design technologies, organizations, and learning environments.

13 Cognitive Ergonomics It is the study of cognition in the workplace with a view to design technologies, organizations, and learning environments. Cognitive ergonomics analyzes work in terms of cognitive representations and processes, and contributes to designing workplaces that elicit and support reliable, effective, and satisfactory cognitive processing From MIT Encyclopaedia of Cognitive Sciences (1999)

14 Roots of Cognitive Ergonomics Cognitive perspective: Human Information Processing model (Neisser, 1967) INPUT OUTPUT

15 Roots of Cognitive Ergonomics Theory of bounded rationality (Simon, 1957): we are not optimal decision makers, we tend to relative satisfaction, not to perfection we have never complete information availability we have finite memory storage we cannot foresee all the possible effects of options we follow euristics rather than algorithms

16 Roots of Cognitive Ergonomics Theory of human error (Reason, 1990): INTERPRETATION EVALUATION PLANNING ANTICIPATION IDENTIFICATION RULE PROCEDURE INPUT SKILL ACTION

17 Roots of Cognitive Ergonomics Theory of human error (Reason, 1990): Organizational factors Latent failures Unsafe supervision Latent failures Absent or failed defenses Preconditions for violations Latent failures Safety violations Active failures Accident

18 Human performance limitations Inattentional blindness (Mack & Rock, 1998)

21 Human performance limitations Change blindness (Rensink, 2002) Airplane Dinner

22 The sketch model (Bracco & Spinelli, 2004) Everything in our environment can be potentially informative and information has several aspects going from bottom-up to top-down. These aspects give a kind of priority to the element with respect to the surrounding context and the higher is its value, the deeper is the processing and the creation of a stable memory trace Objective, hard-wired, bottom-up Subjective, contingent, top-down Aspects of the INFORMATION POTENTIAL Pop out of salient elements Gestalt Properties Protoobject formation Typicality of the element in the scene Contingent Motivations Incongruence of the element in the scene Fundamental motivations Personal expe rience

The sketch model Aspects of the INFORMATION POTENTIAL Pop out of salient elements Gestalt Properties Protoobject formation Typicality of the element in the scene Contingent Motivations Incongruence

23 The sketch model Aspects of the INFORMATION POTENTIAL Pop out of salient elements Gestalt Properties Protoobject formation Typicality of the element in the scene Contingent Motivations Incongruence of the element in the scene Fundamental motivations Personal expe rience Contextual coherence Subjective relevance Two persons at the table, a couple, food and drinks on the table LAYOUT GIST SKETCH

24 The Situation Awareness (Endsley( Endsley,, 1999) Data not available Data hard to see Data not observed SA level 1: Perception 72% Data not interpreted Memory losses Absent or poor mental models Use of wrong mental models Overtrust in habits Other Absent or poor mental models Bad trends projection Other SA level 2: Comprehension 22% SA level 3: Projection 6% 0% 10% 20% 30% 40% errors

25 Overcoming human limitations Human flexibility, context sensitivity and creativity are not the other side of the well-known limits of our cognition, i.e. rough perception and representation of the environmental data, lack of attention and memory, poor mental models, fallible decisions and actions. It is possible to rely on human potentials designing systems that can manage all the other situations where we are fallible

26 Balancing automation and human skills Human cognitive system Machine/computer system Kind of processing Analogical Digital Speed of processing Slow Fast Time needs High Low Precision Low High Flexibility High Low Memory capacity Low High Workload sensitivity High Low Insight High Absent

27 Balancing automation and human skills The challenge for system designers is to introduce automation in order to free human cognitive system from fallible tasks, leaving time and resources to more natural activities. Cognitive ergonomics shows us the three main stages where automation could replace human functions: 1. information acquisition and analysis; 2. decision and choice; 3. execution

28 Potential risks of automation Out-of-the-loop syndrome more automation = more complexity = higher probability of faults in components interaction as complexity grows operators mental models weaken undertrust (e.g. neglect of redundant alarms) overtrust (e.g. operators complacency in system s reliability, loss of situation awareness) lack of operators training on basic skills now performed by automation

29 Potential risks of automation To avoid such problems we should follow some rules as: implement automation following HFE principles; keeping the operator informed of current tasks; keeping the operator trained; slow introduction of automation in the workplace; making automation flexible

30 System approaches to Human Factors Normal Accident Theory (NAT) by Charles Perrow (1999) Main properties of system s susceptibility to accidents: (i) interactive complexity (origin of unexpected events), (ii) tight coupling, (strong interdependency of parts) BUT Perrow s theory is intrinsically pessimistic, because it states that errors are normal in system s life, i.e., it is impossible to absolutely prevent them.

31 System approaches to Human Factors High Reliability Organizations (HRO) Organizational study of those systems that have a record of high safety over long periods. However, this perspective have been criticised because it is too much focused on an organizational view and, most of all, it applies to systems that are not properly complex and tightly coupled

32 Beyond NAT and HRO: HRS We need an approach that adopts models wide enough to see the system in its multidimensionality, and acute enough to note, in accidents analysis, the causal dynamics and, in prevention processes, the weak signals that anticipate a dangerous event.

33 The need for HRS experts It is necessary that an expert in HRS is involved not only when dangerous events happen, but in all the aspects of the system design: ideation, research and development, realization, operation, reengineering, etc., and as a consequence it is necessary to spread his competencies on all the related jobs. This allows us to transform safety from a bolt-on factor to a built-in factor, i.e. inside the system nature. Cognitive Ergonomics Organization Engineering

34 Beyond the Turing dilemma Nancy Leveson (MIT Engineering Systems Division) Systemic approach (Bertalanffy, 1950) Hierarchy of levels of organization each more complex that the one below each level has emergent properties specific for the level and not reducible to the previous ones

35 Beyond the Turing dilemma In HRS the hierarchies are the several levels of analysis, from the operator cognitive system, to the technology, the socio-organizational domain, the environmental aspect etc. the emergent property in HRS is safety, because it is determined not only the reliable function of all its elements, but also in the correct relationship among them

36 Beyond the Turing dilemma Reliability (to do the task a device is designed for) may sometimes be risky, the human element is flexible and could willingly break the operation in particular circumstances Automation Reliable but rigid and context-insensitive Human Element Flexible and creative but fallible emergent property: SAFETY

37 Beyond the Turing dilemma Systemic approach to safety Only when we will have a wide view of the system, from the cognitive aspects to the technical and organizational ones, we could hope to solve the Turing dilemma, because if an infallible (read reliable) machine will not be intelligent, a well designed system could be both infallible and intelligent.

38 Thank you for your attention

Lisa Ramthun, RN, MSN, CPHRM AVP Risk Management

Lisa Ramthun, RN, MSN, CPHRM AVP Risk Management Disclosure I have no potential conflicts of interest to disclose Our systems are producing the results they were designed to produce. In other words: Benefits