Human error

HUMAN ERROR
“To err is human…”
(Cicero, I century BC)

“…to understand the reasons why humans err is science”
(Hollnagel, 1993)

José Luis García-Chico
(jgarciac@email.sjsu.edu)
San Jose State University
ISE 105 Spring 2006
April 24, 2006

What is important to know about human error?

• Human error is in our nature
– It might happen everyone, at any time, in any context

• Some errors are preventable through
procedures, system design and automation.
– But careful, they may introduce new opportunities of erring.
– Emphasis should be put on error tolerant systems: error recovery instead of
erroneous action prevention.

• Human error might not be an accident cause in
itself…it might be caused by multiple factors
– Do not only blame last human operator alone.

Jose Luis Garcia-Chico April 24, 2006

Human error in nuclear powers plants
• Three Mile Island (1979)
• Due to a failure, temperature in the reactor increased rapidly.
The emergency cooling system should have come into
operation but maintenance staff left two valve closed, which
blocked flow. Relief valve opened to relief temperature and
pressure, but stuck open. Radioactive water pours into
containment area and basement for 2 hour.

• Operators failed to detect the
stuck open valve. An indicator
had been installed to indicate
the valve was commanded to
shut, not the status of the valve.
• Some little radioactivity was
released to the environment.


Human error in nuclear powers plants
• Uberlinguen (2002)
• B757 and Tu-154 collided in the German
airspace, under Zurich control. 71 people
were killed.
• Only one controller was in charge of two
positions during a night shift (two
separated displays). Telephone and
STCA under maintenance.
• ATC detected late the conflict between
both aircraft, and instructed T-154 to
descend. The TCAS on board the T-154
and B757 instructed the pilots to climb
and descend respectively. The T-154
pilot opted to obey controller orders and
began a descent to FL 350 where it
collided with the B757. B757 had
followed its own TCAS advisory to
descend.


Definition of Human Error
• Error will be taken as a generic term to encompass all those
occasions in which a planned sequence of mental or physical
activities fails to achieve its intended outcome, and when these
failures cannot be attributed to the intervention of some change
agency. (Reason, 1990)

• Human error occurrences are defined by the behavior of the total
man-task system (Rasmussen, 1987).

• Actions by human operators can fail to achieve their goal in two
different ways: the actions can go as planned, but the plan can be
inadequate, or the plan can be satisfactory, but the performance
can still be deficient (Hollnagel, 1993)


Human error performance
SITUATION ASSESSMENT

MISTAKES
SENSE/INTERPRET

INTENT OF ACTION

PLAN/COGNITION
SLIPS

OMMSSION/COMMISION

EXECUTION

(Norman, 1983)


Human error taxonomies

• Errors of omission (not doing the required thing)
– Forgetting to do it
– Ignoring to do it deliberately

• Errors of commission (doing the wrong thing)
– slips in which the operator has the correct motivation or
intention, but carries out the wrong execution
• Sequence or wrong order of execution
• Timing: too fast/slow
– errors based in erroneous expectations and schema.
(schema are sensory-motor knowledge structures stored in
memory used to guide behavior: efficient and low energy)


Human error taxonomies:
SRK model of behavior (Rasmussen, 1982)
Errors depend on behavior:
•Skill-based
•Ruled-based
•Knowledge-based


Error distinctions

Dimension Sk ill-based Er r or Rule- based err or Know ledge- based er r or

Activity Routine Problem solving

Focus of attention Something other Directed to the problem
than task in hand

Control Mode Highly automated Automated Conscious process
(schemata) (rules: if X then Y)

Detection Rapid and Difficult and often through external
effective intervention


Generic Error Modeling System-GEMS
(Reason, 1990)

Skill-based level


Human Error Distribution

• Humans are prone to slip & lapses with familiar
tasks:
– 61% of errors are skill-based
• Humans are prone to mistakes when tasks
become difficult.
– 28% of errors are rule-based
– 11% of errors are knowledge-based that require
novel reasoning from principles.

Approximate data (Reason, 1990) obtained averaging three studies


Human are error prone, but….is that all?

• It seems that human operator is responsible of
system disasters, just because they are the
last and more visible responsible of the system
performance.
• Distinction between:
– Active errors: error associated with the
performance of the front-line operators, i.e. pilots,
air traffic controllers, control rooms crews, etc
– Latent errors: related to activities removed in time
and space form the direct control interface, i.e.
designers, managers, maintenance, supervisors.


Model of Human Error causation (Reason, 1990)

Accident /
mishap

Adapted from Shappel (2000)


Building solutions

• Each system will require particular instantiation
of the approach, but some general
recommendations might include:
– Prevent errors: procedures, training, safety
awareness, UI design (allow only valid choices)
– Tolerate error: UI design (constraints on inputs),
decision support tools
– Recover error: undo capability, confirmation


Learning from past accident/incident

• Great source of lessons to be learnt…not of
facts to blame.
• Careful considerations to keep in mind:
– Most people involved in accidents are not stupid nor
reckless. They may be only blindness to their
actions.
– Be aware of possible influencing situational factors.
– Be aware of the hindsight bias of the retrospective
analyst.

Hindsight bias: Possession of output knowledge profoundly influence the way we analyze and judge past
events. It might impose a deterministic logic on the observer about the unfolding events that the
individual at the incident time would have not had.


Nine steps to move forward from error:
Woods & Cook (2002)
• Pursue second stories beneath the surface to discover
multiple contributors.
• Escape the hindsight bias
• Understand work as performed at the sharp end of the
system
• Search for systemic vulnerabilities
• Study how practice creates safety
• Search for underlying patterns
• Examine how changes create new vulnerabilities
• Used new technology to support and enhanced human
expertise
• Tame complexity through new forms of feedback


A cased study:

HUMAN FACTOR ANALYSIS OF OPERATIONAL
ERRORS IN AIR TRAFFIC CONTROL

Jose Luis Garcia-Chico
San Jose State University
Master Thesis of Human Factors and
Ergonomics

Motivation of the study
• Some figures - Air Traffic in the USA 2004 (FAA, 2005)
– 46,752,000 a/c in en-route operations
– 46,873,000 movement in tower operations
– 1216 OEs

• OE rate is been increasing during last years (FAA,
2005):
– 0.66%* in 2002
– 0.78% in 2003
– 0.79% in 2004

• Analysis of errors based on initial Air Traffic Controller
Reports:
– 539 reports (Jan-Jun 2004)
Overview | Method | Research Questions | Initial Results

Fa
i lC
Co on

0
100
120

20
40
60
80
De n ve
sc tro rgi
n
O end l co g
ve t or
Ve rl o rho d
c o u
He tor ked gh
Fa a in T
il Alt r/R ad rf
Al i tu ea eq
tC d d u
l im e In bac
b/ ad k
D e
es qu
Fa C R ce
i lim w nd
In l Ov b y I
st e th nc
r u rt a ro
c u
te no kin gh

Jose Luis Garcia-Chico
m -i g -
p nt Tr
e
da Mis erro nd f
ta ap r-i ed
bl p l ss
oc P u
k- r o e
m ce
is d
Tr A e n
an irs te
r
FP spo p a
ce
Sp S-m se
e e i s a/c
d en
in t
W ad e r
r o eq
O ng u
c a
a/ ean /c
c
ov Tr
Cl f
ea L e rl
OE Classification

re OA ap
d
M bl mi s
isr w
ot ead min
he i
r s nf o
/w
ha
t
Taxonomic study: Initial Results

April 24, 2006
ARTCC = 565
ARTCC

Total OE = 869
TRACON = 304
TRACON

Top-10 OEs


Proximity of encounters: OE output


Concurrent and contextual factors

Top - Contributing Factors
0 20 40 60 80 100 120 140 160

D-side Abs TRACON
OS Abs/CIC
Combned sect/decomb ARTCC
Mishearing
Misjudgment
Trf compexity
Training in prgrs
No pilot response/deviation
Distraction
Poor Performance Manouever
WX complexity
Pilot request
Lapse coordination
Other complx
Point Out Complexity
Others
Not enough info


Taxonomic study: Initial Results

DEV vs Prox Rating

None/Unknown

CPC
Rating C DEV

Rating B

Rating A

0% 10% 20% 30% 40% 50% 60% 70% 80%


Proximity in EOs
% Proximity Rating in OEs

Others
Cleared blw min
LOA mis
Misread info
a/c overlap
Wrong a/c
Speed inadequ
FPS-misenter
Transpose a/c
Airspace
datablock-misenter
A
Misappl Proced B
temp error-issue C
Instruc no-intended
Fail Overtaking-Trf No Rate
Climb trhough
Fail Alt Climb/Descend
Altitude Inadequ
Hear/Readback
Vector inadequ
Overlooked Trf
Descend trhough
Control coord
Fail Converging

0% 20% 40% 60% 80% 100%


Co-occurrence of OE


D-side presence/absence
Severtiy of EOs - D-side Present

0 10 20 30 40 50

Fail Overtaking
Overlook Trf
Fail Converging
Descend Through
Climb Through
Altitude Inadeq
Vector Inadeq
Hear/Readback A
Instruc no-intended
Transpose a/c
B
Control Coordination C
Data Bolck misenter
Severtiy of EOs - D-side Absent
Fail Alt Climb Desc
Temp error-issue
Misapplication Proc
0 10 20 30 40 50
FPS-Misenter Fail Overtaking
Overlook Trf
Fail Converging
Descend Through
Climb Through
Altitude Inadeq
Vector Inadeq
Hear/Readback A
Instruc no-intended
Transpose a/c
B
Control Coordination C
Data Bolck misenter
Fail Alt Climb Desc
Temp error-issue
Misapplication Proc
FPS-Misenter


Time on Position


Further Reading
• Besnard, D. Greathead, D., & Baxter, G. (2004). When mental models go wrong. Co-
occurrences in dynamic, critical systems. International Journal of human Computer Studies,
60, 117-128.
• Dekker, S. W. A. (2002) Reconstructing human contributions to accidents: the new view on
error and performance. Journal of Safety Research, 33, pp. 371-385.
• Hollnagel, E. (1993). The phenotype of erroneous actions. International Journal of Man-
Machines Studies, 39, 1-32.
• Norman, A. D. (1981). Categorization of slips. Psychological review, 88 (1), 1-15.
• Parasuraman, R., Sheridan, T.B., & Wickens, C.D. (2000). A model for types and levels of
human interaction with automation. IEEE transactions on systems, man, and cybernetics-Part
A: Systems and humans, 30 (3), 286-297
• Rasmussen, J. (1982). Human errors: A taxonomy for describing human malfunction in
industrial installations. Journal of Occupational Accidents, 4, 311-33.
• Rasmussen, J. (1987) The definition of human error and a taxonomy for technical system
design. In Rasmussen, J., Duncan, K., & Leplat, J. (Eds.), New Technology and Human Error
(pp. 23-30). New York, NY: John Wiley & Sons.
• Reason, J. T. (1990). Human error. Cambridge, England: Cambridge University Press.
• Reason, J. T. (1997). Managing the risks of organizational accidents. Aldershot, England:
Ashgate Publishing Company.
• Woods, D.D. & Cook, R.I. (2002). Nine steps to move forward from error. Cognition,
Technology, and Work, 4, 137-144.


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