1. HUMAN EROR

2. Is it really human error? This is the first question that tends to be posed in light of a critical situation gone wrong, and the answer tends to fall short The easiest explanation as the ‘best’ Human Error vs Designer Error Defining errors as commission or omission, with relation to intention and whether things work out as planned It may be better to rely on hindsight, instead of Occam’s Razor So for example: Instead of saying “The operator pressed the wrong button because he was tired”, ask: Why was the operator tired? Why did it matter that the operator was tired?

4. Overarching categories of human fallibility Information Processing Long Term Memory Decision Making Mental Models (SRK) ‘Other’ (Ex: situation awareness, affect, fatigue)

5. Context in Human Error

6. Categorization and Taxonomy Used to determine “where to look” for a given issue There is more than one possible method Can be approached from a cognitive, information processing, decision making, procedural, SRK, or task analysis perspective To the right is just one framework, the book chapter has about 6 of them listed Each perspective has benefits and drawbacks, because it considers specific factors within context

7. Quantifying Error Essentially assumes that you can predict the probability of an abnormal occurrence, or probabilistic risk analysis (PRA) Fault trees for determining event combination probabilities for a given possible outcome Event trees determine possible outcomes of a given triggering event If an event tree only considers human actions, it refers to an Operator Action Event Tree (OAET) Each of these represents a component of Human Reliability Analysis (HRA) The depth of analysis varies dramatically, most rely on performance shaping factors THERP and SLIM-MAUD are two examples of reliability analysis

8. Incident Reporting Systems (IRS) Human errors can be classified as accidents, adverse events, incidents, near misses, and close calls, but definitions vary based on the institution Effective reporting requires minimal blame attribution and fear of reprisal, as well as appropriate feedback in light of an event. Composed of ‘relevant’, comprehensive and comprehensible quantitative and qualitative data

9. Automation Errors Also a component of designer error Most of these have been discussed in previous sections of the course, test your memory, see if you can remember them.

10. Investigating human error within an incident Determining cause and effect using hindsight is subject to bias Investigations may be informal or systematic, and combining these observations poses issues. Many systematic approaches are listed in the text The book suggests the root cause analysis method of investigation, because the depth of analysis is contextual, and the process is consistent

11. Questions?