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Human Error

Human Error. James Reason Chapter 4 Chen, Xiaohui . The Words. What is “Underspecification”? I can not find it in Webster The cognitive specification is not so clearly defined??? Error Types Differentiated according to the performance levels Error Forms

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Human Error

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  1. Human Error James Reason Chapter 4 Chen, Xiaohui CS851 Forensic Software Engineering

  2. The Words • What is “Underspecification”? • I can not find it in Webster • The cognitive specification is not so clearly defined??? • Error Types • Differentiated according to the performance levels • Error Forms • Recurrent varieties of fallibility that appear in all kinds of cognitive activity CS851 Forensic Software Engineering

  3. The most Important Two Words • Similarity and Frequency • When cognitive operations are underspecified, they tend to default to contextually appropriate, high-frequency responses CS851 Forensic Software Engineering

  4. Why Bother? • Frequency biasing gives predictable shape to human errors in a wide variety of activities and situations (Norman,1981; Reason&Mycielska,1982; Rasmussen,1982) • Why we human being have this tendency to “gamble”? CS851 Forensic Software Engineering

  5. The specification of mental operation • Complex interaction between conscious workspace and the schematic knowledge base • Correct performance in any sphere of mental activity is achieved by activating the right schemata in the right order at the right time • One path for correct; infinite paths for error CS851 Forensic Software Engineering

  6. Schemata • Require a certain threshold level of activation to call them into operation • Specific and General activators CS851 Forensic Software Engineering

  7. Specifications are context-dependent • Descriptions are normally formed to be unambiguous within the context in which they were first used, which defines a memory schema relative to a context • Little additional specification is needed to retrieve the appropriate schemata once the contextual frame is established • While individual schemata are ‘context-dependent’, the cognitive system as a whole is not ‘context-bound’ CS851 Forensic Software Engineering

  8. Semantic contexts • “if the word we intend to speak is highly associated with another word that meets the contextual constraints operating within the utterance, then, given a certain time limit, that other word may be produced in-stead. The error word needs to be a word of high frequency or one whose threshold for production is lowered by other events occurring at the same time for it to have the necessary short latency in response.”(Hotopf,1980) • Oak -> Joke ->Croak ->Cloak ->Yolk(sic!) • Oak -> Joke ->Croak ->Cloak ->Shell(right!) CS851 Forensic Software Engineering

  9. Another kind of contexts • The famous beauty from Stephen R. Covey CS851 Forensic Software Engineering

  10. Cognitive “primitives” • Similarity and frequency information appear to be processed automatically without conscious effort or even awareness, regardless of age, ability, cultural background, motivation or task instruction. CS851 Forensic Software Engineering

  11. Demonstrations of underspecification • Word identification • The recall of verbal list items • Category generation • Recurrent intrusions in blocked memory searches • Slips of the tongue • Slips of action • Failures of prospective memory • Planning for uncertain futures • Pathological underspecification CS851 Forensic Software Engineering

  12. Kinds of underspecification • Incomplete or ambiguous inputs • fragmentary retrieval cues • Incomplete or inaccurate knowledge • Losses from prospective memory • Spillage from the conscious workspace • Intentional limitations • Failures of attentional monitoring(normal or pathologically-induced) CS851 Forensic Software Engineering

  13. Taking stock • Different underspecifications Similar responses • More familiar, more expected and more frequently-encountered • Context-bound: conform both to the current physical situation and the ‘semantic context’ • Effects of frequency are relatively clear-cut, those of similarity are a little bit subtle CS851 Forensic Software Engineering

  14. Taking Stock (cont.) • “Difficulties encountered at the level of formulating the intention of plan tend to create errors that are moulded primarily by immediate contextual considerations; those that occur at the level of storage or execution may reflect the influences of both intentional and environmental ‘calling conditions’” • Why these two levels’ error forms differ? CS851 Forensic Software Engineering

  15. Memory searches • Convergent • Sufficient cues (calling conditions) to identify uniquely a single knowledge structure • Divergent • Entirely similarity-matching because of lack of cues CS851 Forensic Software Engineering

  16. Memory searches (cont.) CS851 Forensic Software Engineering

  17. Memory searches (cont.) CS851 Forensic Software Engineering

  18. Memory searches (cont.) CS851 Forensic Software Engineering

  19. Memory searches (cont.) CS851 Forensic Software Engineering

  20. Retrieval of incomplete semantic knowledge • Answering general knowledge questions • Possible to vary both the specificity of the calling conditions and the adequacy of the stored schemata • Answers tend to be highly predictable • Common but wrong, when the information in semantics memory is both relatively sparse and unevenly distributed CS851 Forensic Software Engineering

  21. Retrieval mechanisms • Four cognitive activities: • Metacognitive assessment of whether or not the sought-for item is likely to be available in semantic memory • Similarity-matching of retrieval cues to the attributes of stored knowledge structures • Resolving conflicts created by the partial matching of several ‘candidates’ by gambling in favor of high-frequency alternatives • Inferential work performed by the conscious workspace, the product of which is a revised set of ‘calling conditions’ CS851 Forensic Software Engineering

  22. Frequency information as the basis of epistemic awareness • Epistemic awareness: • The feelings of knowing (FOK) about what one knows • Upon what basis are these assessments being made? CS851 Forensic Software Engineering

  23. The basis of FOK • FONK ( feeling of NOT knowing) • Two stage model (Glucksberg & McCloskey 1981) • Rapid and confident • Slow and uncertain CS851 Forensic Software Engineering

  24. The basis of FOK • Based on frequency information • Two assumptions: • Frequency-of encounter information appears to be stored in memory by “an implicit or automatic encoding process” • Multiple trace hypothesis: each encounter with a given item is recorded as an additional trace on a ‘pile’ of like traces • Instant ‘frequency maps’ of particular semantic regions CS851 Forensic Software Engineering

  25. Similarity-matching • Matching of the calling conditions present in a question to the attributes of knowledge items stored in semantic memory • The basis of memory search • How the calling conditions are perceived plays a critical part • Not all of the available calling conditions need be active at the outset CS851 Forensic Software Engineering

  26. Frequency-gambling • Insufficient retrieval cues and incomplete stored knowledge • Selection is biased in favor of the more frequently-encountered CS851 Forensic Software Engineering

  27. inference • Establish connections between the propositions available in a question and stored knowledge items • Help to fill the missing pieces CS851 Forensic Software Engineering

  28. Serial and parallel search • The one direct and rapid; the other slower and indirect • “as a search relies more on nonhabitual, novel associations in the memory structure, it demands more attention. Direct search is achieved by activation of well established memory pathways and lies at the low end of the continuum. Associative search uses attention in varying amounts” (Klatzky 1984) CS851 Forensic Software Engineering

  29. Three Studies • “The buck stops here” • The quotations study • The presidential recognition study CS851 Forensic Software Engineering

  30. The buck stops here CS851 Forensic Software Engineering

  31. The quotations study • The amount of frequency-gambling evident in responses to general knowledge questions will be inversely related to the degree of relevant knowledge possessed by the respondent CS851 Forensic Software Engineering

  32. The presidential recognition study • Control both domain knowledge and cue specificity • Provide qualified support for the notion that a decrease in search specificity leads to an increase in the employment of the frequency-gambling and a corresponding diminution in the use of similarity-matching CS851 Forensic Software Engineering

  33. Examine a real error • Therac-25 • X->edit->E->enter->B • “Malfunction 54” CS851 Forensic Software Engineering

  34. Examine a real error (cont.) • The error message is a cognitive underspecification • The error message usually means the treatment has not proceeded • What can we do to help preventing this error? CS851 Forensic Software Engineering

  35. Conclusion • Cognitive system is disposed to select contextually appropriate, high-frequency responses in conditions of underspecification, and this tendency gives predictable form to a wide variety of errors • Can we use this conclusion to predict errors in software engineering? CS851 Forensic Software Engineering

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