Human Factors: The Possible Future by Sidney Dekker

As I mentioned in yesterday’s post, Sidney W. A. Dekker has identified some “hard” truths that human factors and ergonomics practitioners need to face as the discipline moves into the future.  Specifically, in his book “Ten Questions about Human Error: A New View of Human Factors and Human Error,” he states:  

Technological change gave rise to human factors and system safety thinking. The practical demands posed by technological changes endowed human factors and system safety with the pragmatic spirit they have to this day. But pragmatic is no longer pragmatic if it does not match the demands created by what is happening around us now. The pace of sociotechnological change is not likely to slow down any time soon. If we think that World War II generated a lot of interesting changes, giving birth to human factors as a discipline, then we may be living in even more exciting times today. If we in human factors and system safety keep doing what we have been doing, simply because it worked for us in the past, we may become one of those systems that drift into failure. Pragmatics requires that we too adapt to better cope with the complexity of the world facing us now. Our past successes are no guarantee of continued future achievement. (p. xv)

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Human Factors: The Past by Sidney Dekker

Sidney W. A. Dekker, a Professor of Human Factors and System Safety at Lund University, made the following comment regarding the history of human factors in his book “Ten Questions About Human Error: A New View of Human Factors and System Safety:”

Human factors was preceded by a mental Ice Age of behaviorism, in which any study of mind was seen as illegitimate and unscientific. Behaviorism itself had been a psychology of protest, coined in sharp contrast against Wundian experimental introspection that in turn preceded it. If behaviorism was a psychology of protest, then human factors was a psychology of pragmatics. The Second World War brought such a furious pace of technological development that behaviorism was caught short-handed. Practical problems in operator vigilance and decision making emerged that were altogether immune against Watson’s behaviorist repertoire of motivational exhortations. Up to that point, psychology had largely assumed that the world was fixed, and that humans had to adapt to its demands through selection and training. Human factors showed that the world was not fixed: Changes in the environment could easily lead to performance increments not achievable through behaviorist interventions. In behaviorism, performance had to be shaped after features of the world. In human factors, features of the world were shaped after the limits and capabilities of performance. (p. x)

Tomorrow I’ll post his thoughts regarding the possible future of the discipline if its’ practitioners do not face some hard ”truths” and make necessary changes to maintain relevance to the business community – and society at large.

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Characteristics of an Expert Team

Salas, Rosen, Burke, Goodwin, and Fiore (2006) have defined “…an expert team as a set of interdependent team members, each of whom possesses unique and expert-level knowledge, skills, and experience related to task performance, and who adapt, coordinate, and cooperate as a team, thereby producing sustainable, and repeatable team functioning at superior or at least near-optimal levels of performance” (p. 440).

Rosen, Salas, Lyons, and Fiore (2008), adapting a table from Salas, et al. (2006), presented a list that characterizes members of expert teams.  They (pp. 221-222):

1. Develop shared mental models.
   • They anticipate each other’s needs and actions.
   • They can communicate implicitly.
   • They interpret cues in a complimentary manner.
2. Learn and adapt.
   • They self-correct.
   • They learn from past decision-making episodes.
   • They adapt coordinating processes to dynamic environments.
   • They compensate for each other.
3. Maintain clear roles and responsibilities.
   • They manage expectations.
   • They understand each other’s roles and how they fit together.
   • They maintain clarity of roles while maintaining flexibility.
4. Possess clear, valued, and shared vision.
   • They develop their goals with a shared sense of purpose.
   • They guide their decisions with a common set of values.
5. Develop a cycle of pre-brief -> performance -> debrief.
   • They regularly provide individual and team level feedback to one another.
   • They establish and revise team goals and plans.
   • They dynamically set priorities.
   • They anticipate and review issues/problems of members.
   • They periodically diagnose team decision making “effectiveness,” including its results, and its processes.
6. Are led by strong team leaders.
   • They are led by someone with good leadership skills and not just technical competence.
   • They believe the leaders care about them.
   • Leaders of expert teams provide situation updates.
   • Leaders of expert teams foster teamwork, coordination, and cooperation.
   • Leaders of expert teams self-correct first.
7. Have a strong sense of “collective,” trust, teamness, and confidence.
   • They manage conflict well; they confront each other effectively.
   • They have a strong sense of team orientation.
   • They trust other team members’ “intentions.”
   • They strongly believe in the team’s collective ability to succeed.
8. Cooperate and coordinate.
   • They identify teamwork and task work requirements.
   • They ensure that, through staffing and/or development, the team possesses the right mix of competencies.
   • They consciously integrate new team members.
   • They distribute and assign work thoughtfully.
   • They examine and adjust the team’s physical workplace to optimize communication and coordination.

References

Rosen, M.A., Salas, E., Lyons, R., & Fiore, S.M. (2008). Expertise and naturalistic decision making in organizations: Mechanisms of effective decision making. In G.P. Hodgkinson & W.H. Starbuck (Eds.), The oxford handbook of organizational decision making (pp. 211-230). New York: Oxford University Press.

Salas, E., Rosen, M. A., Burke, C. S., Goodwin, G. F., & Fiore, S. (2006). The making of a dream team: When expert teams do best. In K. A. Ericsson, N. Charness, P. J. Feltovich & R. R. Hoffman (Eds.), The Cambridge Handbook of Expertise and Expert Performance (pp. 439-453). New York: Cambridge University Press.

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Expert Decision Makers

Have you ever wondered what separates expert decision makers from average ones?  Rosen, Salas, Lyons, and Fiore (2008) have developed a list of mechanisms that characterize expert decision making.  They include (p. 216):

1. Are tightly coupled to cues and contextual features of the environment.
   • They develop psychological and physiological adaptations to the task environment.
   • They are sensitive to and leverage contextual patterns of cues in decision making.
2. Have a larger knowledge base and organize it differently from non-experts.
   • They have a more conceptually organized knowledge base.
   • They have more robust connections between aspects of their knowledge.
   • They have a more abstracted and functional knowledge base.
3. Engage in pattern recognition.
   • They perceive larger and more meaningful patterns in the environment.
   • They are able to detect subtle cue configurations.
   • They are able to retrieve courses of action based on situation/action matching rules.
4. Engage in deliberate and guided practice.
   • They devote time and effort to improving knowledge and skills.
   • They have high motivation to learn and long term learning goals.
5. Seek diagnostic feedback.
   • They seek out input from other experts.
   • They self-diagnose their performance, indentify weaknesses in their knowledge and processes, and correct them.
6. Have better situation assessment and problem representations.
   • They spend more time evaluating the situation.
   • They create deeper, more conceptual, more functional, and more abstracted situation representations.
7. Have specialized memory skills.
   • They functionally increase their ability to handle large amounts of information.
   • They anticipate what information will be needed in the decision making.
8. Automate the small skills.
   • They quickly and effortlessly do what requires large amounts of attention for non-experts.
   • They have more cognitive resources available for dealing with more complex aspects of decision making.
9. Self-regulate and monitor their progress.
   • They evaluate their own understanding of a situation.
   • They judge the consistency, reliability, and completeness of their information.
   • They make good decisions about when to stop evaluating the situation.

References

Rosen, M.A., Salas, E., Lyons, R., & Fiore, S.M. (2008).  Expertise and naturalistic decision making in organizations: Mechanisms of effective decision making.  In G.P. Hodgkinson & W.H. Starbuck (Eds.), The oxford handbook of organizational decision making (pp. 211-230).  New York: Oxford University Press.

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HFES Technical Groups

The discipline of human factors and ergonomics is so broad and diverse, that at times, I find it challenging to adequately convey an overview to someone new to it in a timely manner.  Thus, besides providing a general definition and discussing some relevant examples, I’ve started talking more about the Human Factors and Ergonomics Society, including its 23 Technical Groups.  They include:

• Aerospace Systems
• Aging
• Augmented Cognition
• Cognitive Engineering and Decision Making
• Communications
• Computer Systems
• Education
• Environmental Design
• Forensics Professional
• Health Care
• Human Performance
• Individual Differences in Performance
• Industrial Ergonomics
• Internet
• Macroergonomics
• Perception and Performance
• Product Design
• Safety
• Surface Transportation
• Systems Development
• Test and Evaluation
• Training
• Virtual Environments

You can learn more from their descriptions or by visiting their individual websites.

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