‘Learning Objectives of Error and Risk’

1. ‘Learning Objectives of Error and Risk’ • Give a critical account of generic models of error • Understand the conceptual difficulties involved in the use of the term error • To begin to be able to plan error prevention/minimisation strategies in organisations • Give a critical account of two models of risk taking behaviour • Evaluate the utility of models of risk taking behaviour in the workplace.

2. Reading

3. Error • Conceptual Issues • Generic models • Prevention

4. Conceptual Issues • What is an error? • Can you make an error while you are asleep? • Can you make an error by doing nothing? • If there are no negative outcomes from an ‘error’, has there been an error?

5. Conceptual Issues (cont.) • Does an error involve intent? • What do you do to people who make errors? • How do organisational factors impinge on error? • Can one persons error be another's intended action?

6. To What Extent is ‘blame’ useful • Is it fair? • Who might apportion blame? • Operators normally get blamed - this is cheap. • Allocation of individual responsibility removes moral responsibility from management

7. Blame (cont.) • Does blame have a certain utility? • The term ‘error’ precipitates a mantle of causality around around those proximate to an event

8. Emerging Themes • Errors are rarely issues of personal responsibility. • Errors are completely dependent on context. • Errors are normally distributed system failures not the result of one persons actions • Errors are multi-causal.

9. Models of Error • Many variants • Slips vs. Mistakes • Omission vs. Commission • Skill, Rule and Knowledge based errors • Generic Error Modelling Systems

10. Some Problems with these models • Generic models, by their nature play down the importance of context • The distinction between slips and mistakes - e.g... valve operation • The role of intention • The difficulty in distinguishing between skills rules and knowledge

11. Problems (cont.) • Tend to be non falsifiable • Tend to be post hoc and descriptive, not prospective (this would allow effective planning) • The baby disappears with the bath water.

12. Error Prevention • Not possible • So we try to • Reduce the probability of error • Design systems that degrade gracefully, rather than fail catastrophically • Allow error recovery

13. What can be done to mitigate ‘error’ (general) • View errors as distributed failures of systems • Appreciate the complex causality of ‘error’ • Operate a blame free culture - errors are very useful ways of learning about organisations and system performance

14. Mitigation (gen.) cont... • Be flexible and responsive • Plan • Distinguish between prevention e.g... by design, and recovery • Recognise operators are part of system not separate from it.

15. What can be done to mitigate ‘error’ (particular) • Train and inform designers, trainers, procedure writers, managers as well as operators - ensure very one has domain specific knowledge and is not far removed. • Train operators in dealing with unusual or unexpected systems configurations, not just in routine operations. • Ensure procedures are congruent with system characteristics

16. Mitigation (particular - cont.) • Ensure management style is consistent and has no hidden agendas (q. is this possible) • Pay attention to communication between different professional groups • Pay attention to communications both within and between operations

17. Continued • Learn from past mistakes in general terms • Institute operational feedback systems • e.g... CHIRPS • e.g... Operational feedback officers • Train ( properly) • Attend to organisational safety culture • Have management commitment to safety

18. Automation - a particular issue • Creeping de-skilling • Opaque systems • Complex and unpredictable systems states • Additional reading on this topic ‘Ironies of Automation’ by Lisanne Bainbridge, in ‘New Technology and Human Error’ eds, Rasmussen, Duncan and Leplat’ LEA, 1987. Also Chapter by Brehmer.