How the heck did I miss that? How visual attention limits visual perception Jeremy Wolfe Brigham & Women s Hospital/ Harvard Medical School

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1 How the heck did I miss that? How visual attention limits visual perception Jeremy Wolfe Brigham & Women s Hospital/ Harvard Medical School

2 Why the heck did I miss that? Profusion Spatial uncertainty Inattentional blindness Prevalence Ambiguity and Decision Criteria

3 Profusion: Too much data Andriole, K. P., Wolfe, J. M., Khorasani, R., Treves, S. T., Getty, D. J., Jacobson, F. L., et al. (2011). Optimizing Analysis, Visualization, and Navigation of Large Image Data Sets: One 5000-Section CT Scan Can Ruin Your Whole Day. Radiology, 259(2),

4 Spatial Uncertainty Optical Illusions

5 Inattentional Blindness: Looking for nodules in lung CT Round white nodules

6 There was something odd about this case

7 Not subtle but missed by 20 of 24 radiologists Note that radiologists were guiding to small white nodules

8 REALLY IMPORTANT NOTE: This is not a criticism of radiologists! Just evidence that experts use the human search engine, too. Drew, T., Vo, M. L.-H., & Wolfe, J. M. (2013). The Invisible Gorilla Strikes Again: Sustained Inattentional Blindness in Expert Observers. Psychological Science, 24(9),

9 The problem is the attentional bottleneck

10 The problem is the attentional bottleneck

11 The problem is the attentional bottleneck

12 The problem is the attentional bottleneck

13 Prevalence The Problem of Rare Targets Can you find a threat?

14 Can you find a threat?

15 Can you find a threat?

16 Can you find a threat?

17 Can you find a threat?

18 Does prevalence matter? Let s take 20 bags with guns and knives And put them in a stack of 40 bags 50% Prevalence Or 1000 bags 2% Prevalence

19 When targets are present in half of the bags people miss about 20% of them NOTE: THESE ARE VOLUNTEERS, NOT AIRPORT SECURITY OFFICERS

20 When targets are present in 2% of the bags people miss over 40% of them! Same threats, just rarer

21 False alarm errors go the other way. Which kind of error do you want to minimize?

22 That just the lab. Would this ever happen in a real clinical setting?

23 The Radiology Result Evans, K. K., Birdwell, R. L., & Wolfe, J. M. (2013). If You Don t Find It Often, You Often Don t Find It: Why Some Cancers Are Missed in Breast Cancer Screening.. PLoS ONE 8(5): e64366

24 Oh and these are real transportation security officers (TSOs) J. of Vision (any moment now)

25 Ambiguity and decision Knife?

26 Ambiguity and decision Knife?

27 Ambiguity and decision No

28 Ambiguity and decision Yes

29 A little model of the problem NOT a threat Maximal THREAT

30 There are various sorts of threat Typical threat Less Very Rare Maybe threat? Not very threatening Maximal threat Maximally threatening

31 Then there are non-threats Typical threat Less Very Rare Maybe threat? Maximal threat Not a Threat Not very threatening Maximally threatening

32 If you need to decide about Threat or not threat, that is pretty easy. NOT THREAT THREAT Less Very Rare

33 Call this green line your criterion NOT THREAT THREAT Less Very Rare

34 The problem is that the distributions overlap Less NOT THREAT? THREAT? Very Rare

35 If you have to make a decision, all you can do is put a criterion, somewhere Less NOT THREAT? THREAT? Very Rare

36 Now you have four possibilities It was a threat and you called it a threat Less Very Rare

37 Now you have four possibilities It was not a threat and you did not call it a threat Less Very Rare

38 Less Now you have four possibilities ERROR: It was not a threat and you called it a threat Very Rare

39 Now you have four possibilities Less ERROR: It was a threat and you missed it Very Rare Not bear-like Maximally bear-like

40 If MISS errors are bad Less Very Rare Move the criterion

41 But that is a high false alarm rate Less Very Rare Move the criterion

42 If you move the other direction, to keep the line moving Don t stop Stop Less Very Rare Missed threats Your choice

43 In summary Our limited-capacity visual system has too much to look at in unknown locations while hunting for rare and ambiguous targets

44 The problem is ubiquitous The solutions are not

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