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m
Perception
of
Risk
PAUL
SLOVIC
Studies
of
risk perception examine
the
judgments
people
make
when
they are asked
to
characterize
and
evaluate
hazardous activities
and
technologies. This research aims
to
aid risk analysis
and
policy-making by (i) providing a
basis for
understanding
and
anticipating public responses
to
hazards
and
(ii) improving
the
communication
of
risk
information anlong lay people, technical experts,
and
decision-makers. This
work
assumes
that
those
who
pro
-
mote
and
regulate health
and
safety need
to
understand
how
people
think
about
and
respond
to
risk.
Without
such understanding, well-intended policies may be inef-
fective.
T
HE
ABILITY
TO
SENSE
AND
AVOID
HARMFUL
ENVIRONMEN-
tal conditions
is
necessary for the survival
of
all
li
ving
organisms. Survival
is
also aided by an ability
to
codif)r
and
learn from past experience. Humans ha
ve
an additional capability
that allows them to alter their environment
as
well
as
respond
to
it.
This capacity both creates and reduces risk.
In recent decades, the profound development
of
chemical and
nuclear technologies has been accompanied
by
the potential
to
cause
catastrophic and long-lasting damage
to
the earth and the
life
forms
that inhabit it. The mechanisms underlying these complex techno
lo
-
gies are unfamiliar and incomprehensible
to
most citizens. Their
most harmful consequences are rare and often delayed, hence
difficult
to
assess
by statistical analysis and not
well
suited
to
management by trial-and-error learning. The elusive and hard
to
manage qualities
of
toda
y's
hazards have forced the creation
of
a new
intellectual discipline called risk assessment, designed
to
aid
in
identif)ring, characterizing, and quantif)ring risk (1).
Whereas technologically sophisticated analysts employ
risk
assess-
ment
to
evaluate hazards, the majority
of
citizens
rely
on intuitive
risk judgments, typically called "
ri
sk perceptions." For these people,
280
experience with hazards tends to come from the news media, which
rather thoroughly document mishaps and threats occurring
throughout the world. The dominant perception for most Ameri-
cans (and one that contrasts sharply with the views
of
professional
risk
assessors)
is
that they
face
more risk today than
in
the past and
that future risks
wi
ll
be even greater than today's (2). Similar views
appear
to
be
held by citizens
of
many other industrialized nations.
These perceptions and the opposition to technology that accompa-
nies them have puzzled and frustrated industrialists and regulators
and have led numerous observers to argue that the American
public's apparent pursuit
of
a "zero-risk
society"
threatens the
nation's political and economic stability. Wildavsky (3,
p.
32)
collunenred
as
follows
on
this state
of
affairs.
How
extraordinary! The richest, longest lived, best protected, most
resourceful
civi
li
zation, with the highest degree
of
in
sight into its own
technology,
is
on its way to becoming the most frightened.
Is it our environment
or
ourselves that h
ave
changed? Would people
like
us h
ave
had this sort
of
concern
in
the past?
...
Toda
y,
there are
risks
from
numerous small dams far exceeding those from nuclear reactors. Why
is
the
one feared and nor the other?
Is
it just that
we
are used to the old
or
are some
of
us
looking differently at essentially the same sorts
of
experience?
During the past decade, a small number
of
researchers has been
attempting
to
answer such questions
by
examining the opinions that
people express when they are asked, in a variety
of
ways, to evaluate
hazardous activities, substances, and technologies. This research has
attempted
to
develop techniques for assessing the complex and
subtle opinions that people have about risk. With these techniques,
researchers have sought
to
discover what people mean when th
ey
say
that something
is
(or
is
not)
"r
isky,
" and
to
determine what factors
underlie
th
ose perceptions. The basic assumption underlying these
efforts
is
that those who promote and regulate health and safety need
to
wldersralld the
ways
in
which people think about and respond
to
risk.
----
---
-- .. ------
-----
The aumor
is
president of Decision Research, 1201 Oak Street, Eugene,
OR
97401,
and protessor
of
psychology at me University
of
Oregon.
SCIENCE,
VOL.
236
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If
successful, this research should aid policy-makers by improving
communication between them and the public, by directing educa-
tional efforts, and
by
predicting public responses
to
new technolo-
gies (for example, genetic engineering), events (for example, a good
safety record
or
an accident), and new risk management strategies
(for example, warning labels, regulations, substitute products).
Risk Perception Research
Important contributions
to
our
current understanding
of
risk
perception have come from geography, sociology, political science,
anthropology, and psychology. Geographical research focused orig-
inally
on
understanding human behavior in the
face
of
natural
hazards,
but
it has since broadened
to
include technological hazards
as
well (4). Sociological (5) and anthropological studies (6) have
shown that perception and acceptance
of
risk have their roots in
social and cultural factors. Short (5) argues that response
to
hazards
is
mediated
by
social influences transmitted by friends, family, fellow
workers, and respected public officials.
In
many cases, risk percep-
tions may form afterwards,
as
part
of
the
ex
post facto rationale for
one's own behavior. Douglas and Wildavsky (6) assert that people,
acting within social groups, downplay certain risks and emphasize
others
as
a means
of
maintaining and controlling the group.
Psychological research
on
risk perception, which shall be my
focus, originated in empirical studies
of
probability assessment,
utility assessment, and decision-making processes (7). A major
development in this area has been the discovery
of
a set
of
mental
strategies,
or
heuristics, that people employ in order to make sense
out
of
an uncertain world (8). Although these rules are valid in some
circumstances, in others they lead
to
large and persistent biases, with
serious implications for risk assessment.
In
particular, laboratory
research
on
basic perceptions and cognitions has shown that difficul-
ties in understanding probabilistic processes, biased media coverage,
misleading personal experiences, and the anxieties generated
by
life's
gambles cause uncertainty
to
be denied, risks
to
be misjudged
(sometimes overestimated and sometimes underestimated), and
judgments
of
fact to be held with unwarranted confidence. Experts'
judgments appear
to
be prone
to
many
of
the same biases
as
those
of
the general public, particularly when experts are forced to go beyond
the limits
of
available data and rely
on
intuition
(8,
9).
Research further indicates that disagreements about risk should
not be expected
to
evaporate in the presence
of
evidence. Strong
initial views are resistant
to
change because they influence the way
that subsequent information
is
interpreted. New evidence appears
reliable and informative
if
it
is
consistent with one's initial beliefs;
contrary evidence tends
to
be dismissed
as
unreliable, erroneous,
or
unrepresentative (10). When people lack strong prior opinions, the
opposite situation
exists-they
are at the mercy
of
the problem
formulation. Presenting the same information about risk in different
ways
(for example, mortality rates
as
opposed
to
survival rates) alters
people's perspectives and actions (11).
The Psychometric Paradigm
One broad strategy for studying perceived risk
is
to develop a
taxonomy for hazards that can be used
to
understand and predict
responses
to
their risks. A taxonomic scheme might explain, for
example, people's extreme aversion
to
some hazards, their indiffer-
ence
to
others, and the discrepancies between these reactions and
opinions
of
experts. The most common approach
to
this goal has
employed the psychometric paradigm (12, 13), which uses psycho-
physical scaling and multivariate analysis techniques
to
produce
17
APRIL
1987
quantitative representations
or
"cognitive maps"
of
risk attitudes
and perceptions. Within the psychometric paradigm, people make
quantitative judgments about the current and desired riskiness
of
diverse hazards and the desired level
of
regulation
of
each. These
judgments are then related to judgments about other properties,
such
as
(i)
the hazard's status
on
characteristics that have been
hypothesized to account for risk perceptions and attitudes (for
example, voluntariness, dread, knowledge, controllability), (ii) the
benefits that each hazard provides to society, (iii) the number
of
deaths caused by the hazard in an average year, and
(iv)
the number
of
deaths caused by the hazard in a disastrous year.
In
the rest
of
this article, I shall briefly review some
of
the results
obtained from psychometric studies
of
risk perception and outline
some implications
of
these results for risk communication and risk
management.
Revealed and Expressed Preferences
The original impetus for the psychometric paradigm came from
the pioneering effort
of
Starr (14)
to
develop a method for weighing
technological risks against benefits in order
to
answer the fundamen-
tal question,
"How
safe
is
safe enough?" His "revealed preference"
approach assumed that,
by
trial and error, society has arrived at an
"essentially optimum" balance between the risks and benefits associ-
ated with any activity.
One
may therefore use historical
or
current
risk and benefit data to reveal patterns
of
"acceptable" risk-benefit
trade-offs. Examining such data for several industries and activities,
Table 1. Ordering
of
perceived risk for 30 activities and technologies (22).
The ordering
is
based
on
the geometric mean risk ratings within each group.
Rank 1 represents the most risky activity
or
technology.
Activity League
of
College Active
or
Women club Experts
technology Voters students members
Nuclear power 1 1 8
20
Motor vehicles 2 5 3 1
Handguns 3 2 1 4
Smoking 4 3 4 2
Motorcycles 5 6 2 6
Alcoholic beverages 6 7 5 3
General (private) 7 15
11
12
aviation
Police work 8 8 7
17
Pesticides 9 4 15 8
Surgety 10
11
9 5
Fire fighting
11
10 6 18
Large construction 12 14 13 13
Hunting 13 18 10 23
Spray cans
14
13
23 26
Mountain climbing 15
22
12
29
Bicycles
16
24
14 15
Commercial aviation 17 16 18 16
Electric power (non- 18 19 19 9
nuclear)
Swimming 19 30 17 10
Contraceptives 20 9 22
11
Skiing 21 25 16 30
X-rays
22 17
24
7
High school and 23
26
21
27
college football
Railroads
24
23 29 19
Food preservatives 25 12 28 14
Food coloring 26
20
30 21
Power mowers
27
28
25 28
Prescription antibiotics 28 21 26 24
Home appliances 29
27
27
22
Vaccinations 30 29 29 25
ARTICLES
281
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Starr concluded that (i) acceptability
of
risk from
an
acnvlty
is
roughly proportional to the third power
of
the benefits for that
activity, and (ii) the public will accept risks from voluntary activities
(such
as
skiing) that are roughly 1000 times
as
great
as
it would
tolerate from involuntary hazards (such
as
food preservatives) that
provide the same
level
of
benefits.
revealed preferences approach stimulated Fischhoff et
ai.
(12) to
conduct
an
analogous psychometric analysis
of
questionnaire data,
resulting in "expressed preferences." In recent years, numerous other
studies
of
expressed preferences have been carried out within the
psychometric paradigm (16-24).
These studies have shown that perceived risk
is
quantifiable and
predictable. Psychometric techniques seem well suited for identify-
ing similarities and differences among groups with regard to risk
perceptions and attitudes (Table 1). They have
also
shown that the
The merits and deficiencies
of
Starr's approach have been debated
at length (15). They will not
be
elaborated here, except to note that
concern about the validity
of
the many assumptions inherent in the
Coa
1
Water
Fluoridation.
Laetri
1 e •
r4;crawave
over.s.
Sa
cchar;
n.
Ni
tr;
tes.
Factor 2
Unknown risk
.Electric
FieldS
•
DES
Water
Chlorination
••
HeX;Ocl:1vo;
rn;
tethel0r~de
.
•
Ni
trogen
Fert
i 1 i
zers
•
DNA
Technology
•
SST
Tar
Hairdyese
Ora
1
Contracept;
ves.
•
Oiagnostic
X
Rays
•
Cadm;
urn
Usage
.Trichloroethylene
.2,4,5·T
• Ri!dioactive Waste
•
Cd
ffei
ne
•
Aspirin
Valium.
Oarvone
•
IUD
Antibiotics.
Rubber
Mfg.
• Vacc i
nes
Auto
Lead.
•
lead
Pal
nt
Mirex
.Pe
sticid
es
•
Urani
um
Mining
•
Asbestos
Insulation
•
pes's
•
Mercury
.
Satellite
Crashes
.DDT
.Fos
si
l
Fuels
.Coal
Burning
(Po
lluti
on )
• Nuclear Reactor Accidents
• Nuclear
Weapons
Fallout
Factor 1
Dread risk
Skateboards
. •
Auto
Exhaust
(CO)
•
D-CON
• L
NG
Storag
e &
Transport
• Nerve
Gas
Accidents
Smoking
(Disease.
Power
Mowers.
Snowmobiles •
Trampol i
nes.
•
Tractors
Alcohol .
Cha
i nsaws •
•
Elevators
•
Co
al
Mining
(Dis
ea
se)
•
Large
Dams
•
Sk
yscraper
Fi
res
Home
Swinming
Pools
••
Electri
c Wir & Appl
(Fires)
• Underwa
ter
Cons t
•
Sport
Pa
ra
ch
utes
• Coal
Mining
Accident
s
Down
hill
Skiing~
• Smoking
(Fires)
Rec
Boatlng.
•
General
Aviation
Electric
Wir
&
Appl
(Shock).
CONTROLLABLE
NOT
DREAD
B
icyc
l
es.
NOT
GLOBAL
CATASTROPHIC
CONSEQUENCES
NOT
FATAL
EQUITABLE
INDIVIDUAL
LOW
RISK
TO
FUTURE
GENERATIONS
EASILY
REDUCED
RISK
DECREASING
VOLUNTARY
Motorcycles.
Bridges.
• H
igh
Construction
•
Railroad
Collisions
Ac;:idents
•
Conm
Aviation
Fi
reworks.
• Auto Rac i
ng
Auto
Accidents
Factor
2
NOT
OBSERVABLE
UNKNOWN
TO
THOSE
EXPOSED
EFFECT
DELAYED
NEW
RI
SK
RI
SKS
UNKNOWN
TO
SC
I
ENCE
~~
____
~~~
____
-,J
I
r~------~~~----~'
OBSERVABLE
KNOWN
TO
THOSE
EXPOSED
EFFECT
IMMEDIATE
OLD
RISK
RISKS
KNOWN
TO
SCI
ENCE
• Handguns
•
Dy
na
mi
te
UNCONTROLLABLE
DREAD
GLOBAL
CATASTROPHIC
CONSEQUENCES
FATAL
NOT
EQUITABLE
CATASTROPHIC
HIGH
RISK
TO
FUTURE
GENERATIONS
NOT
EASILY
REDUCED
RISK
INCREASING
INVOLUNTARY
Nuclear
Weapons (War).
Factor
1
Fig. 1. Location
of
81
hazards on factors 1 and 2 derived from the relationships among 18 risk characteristics. Each factor
is
made up
of
a combination
of
characteristics,
as
indicated
by
the lower diagram (25).
282
SCIENCE,
VOL.
236
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concept "risk" means different things to different people. When
experts judge risk, their responses correlate highly with technical
estimates
of
annual fatalities. Lay people can
assess
annual fatalities
if
they are asked to (and produce estimates somewhat like the technical
estimates). However, their judgments
of
"risk" are related more to
other hazard characteristics (for example, catastrophic potential,
threat to future generations) and,
as
a result, tend to differ from their
own (and experts') estimates
of
annual fatalities.
Another consistent result from psychometric studies
of
expressed
preferences
is
that people tend to view current risk
levels
as
unacceptably high for most activities. The gap between perceived
and desired risk
levels
suggests that people are
not
satisfied with the
way that market and other regulatory mechanisms have balanced
risks
and benefits. Across the domain
of
hazards, there seems to
be
little systematic relationship between perceptions
of
current
risks
and benefits. However, studies
of
expressed preferences do seem to
support Starr's argument that people are willing to tolerate higher
risks
from activities seen
as
highly beneficial. But, whereas Starr
concluded that voluntariness
of
exposure was the
key
mediator
of
risk acceptance, expressed preference studies have shown that other
(perceived) characteristics such
as
familiarity, control, catastrophic
potential, equity, and
level
of
knowledge
also
seem to influence the
relation between perceived risk, perceived benefit, and risk accept-
ance
(12,
22).
Various models have been advanced to represent the relation
between perceptions, behavior, and these qualitative characteristics
of
hazards.
As
we
shall
see,
the picture that emerges from this work
is
both orderly and complex.
Factor-Analytic Representations
Many
of
the qualitative risk characteristics are correlated with
each other, across a wide range
of
hazards. For example, hazards
judged to
be
"voluntary" tend also to
be
judged
as
"controllable";
hazards whose adverse
effects
are delayed tend to
be
seen
as
posing
risks
that are
not
well
known, and so on. Investigation
of
these
relations by means
of
factor analysis
has
shown that the broader
domain
of
characteristics can
be
condensed to a small set
of
higher
order characteristics
or
factors.
The factor space presented in Fig. 1 has been replicated across
groups
of
lay
people and experts judging large and diverse sets
of
hazards. Factor
1,
labeled "dread risk,"
is
defined at its high (right-
hand) end by perceived lack
of
control, dread, catastrophic poten-
tial, fatal consequences, and the inequitable distribution
of
risks and
benefits. Nuclear weapons and nuclear power score highest on the
characteristics that make up this factor. Factor 2, labeled "unknown
risk,"
is
defined at its high end by hazards judged
to
be
unobserv-
able, unknown, new, and delayed in their manifestation
of
harm.
Chemical technologies score particularly high
on
this factor. A third
factor, reflecting the number
of
people exposed to the
risk,
has been
obtained in several studies. Making the set
of
hazards more
or
less
specific
(for example, partitioning nuclear power into radioactive
waste, uranium mining, and nuclear reactor accidents)
has
had little
effect
on
the factor structure
or
its relation to risk perceptions (25).
Research has shown that
lay
people's risk perceptions and atti-
tudes are closely related to the position
of
a hazard within this type
offactor space. Most important
is
the horiwntal factor "dread risk."
The higher a hazard's score
on
this factor (the further to the right it
appears in the space), the higher its perceived risk, the more people
want to
see
its current
risks
reduced, and the more they want to
see
strict regulation employed to achieve the desired reduction in risk
(Fig. 2). In contrast, experts' perceptions
of
risk are
not
closely
related to any
of
the various risk characteristics
or
factors derived
17 APRIL 1987
Unknown risk
•
.
•••
•
.
,.
• •
. •
••
• •
!.
•
• • • • •
•
t.
•
• •
••
• • Dread risk
•
• • •
',.
.
..
•
, . •
. •
••
•
•
• • •
Fig, 2, Attitudes toward regulation
of
the hazards in Fig.
1.
The larger the
point, the greater the desire for strict regulation to reduce risk (25).
from these characteristics (25). Instead,
as
noted earlier, experts
appear to
see
riskiness
as
synonymous with expected annual mortal-
ity (26).
As
a result, conflicts over "risk" may result from experts and
lay
people having different definitions
of
the concept.
The representation shown in Fig.
1,
while robust and informative,
is
by no means a universal cognitive mapping
of
the domain
of
hazards. Other psychometric methods (such
as
multidimensional
scaling analysis
of
hazard similarity judgments), applied to quite
different sets
of
hazards, produce different spatial models
(13,
18).
The utility
of
these models for understanding and predicting
behavior remains to be determined.
Accidents
as
Signals
Risk analyses typically model the impacts
of
an
unfortunate event
(such
as
an
accident, a discovery
of
pollution, sabotage, product
tampering) in terms
of
direct harm to victims-deaths, injuries, and
damages. The impacts
of
such events, however, sometimes extend
far
beyond these direct harms and may include significant indirect
costs (both monetary and nonmonetary) to the responsible govern-
ment agency
or
private company that far exceed direct costs. In some
cases,
all
companies in an industry are affected, regardless
of
which
company was responsible for the mishap. In extreme cases, the
indirect costs
of
a mishap may extend past industry boundaries,
affecting companies, industries, and agencies whose business
is
minimally related to the initial event. Thus, an unfortunate event can
be
thought
of
as
analogous to a stone dropped in a pond. The
ripples spread outward, encompassing first the directly affected
victims, then the responsible company
or
agency, and, in the
extreme, reaching other companies, agencies, and industries.
Some events make only small ripples; others make larger ones.
The challenge
is
to discover characteristics associated with
an
event
and the way that it
is
managed that can predict the breadth and
seriousness
of
those impacts (Fig. 3). Early theories equated the
magnitude
of
impact to the number
of
people killed
or
injured,
or
to
the amount
of
property damaged. However, the accident at the
Three Mile Island (TMI) nuclear reactor in 1979 provides a
dramatic demonstration that factors besides injury, death, and
property damage impose serious costs. Despite the fact that
not
a
single person died, and
few
if any latent cancer fatalities are
expected, no other accident in our history has produced such costly
societal impacts. The accident at
TMI
devastated the utility that
owned and operated the plant.
It
also imposed enormous costs (27)
on the nuclear industry and
on
society, through stricter regulation
(resulting in increased construction and operation costs), reduced
ARTICLES
283
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-
Eel ~
/
Ee2
0"
~e3
..
'-
Een
,
Event Event
character-
istics
~---------
Other technologies
Interpretation
of
E
-
-----
----
----
Signal
Interpretation Spread
of
impact
Loss
of
sales
Regulatory
constraints
Litigation
Community
opposition
Investor
flight
Type
of
im
pact
(company level)
Fig. 3. A model
of
impact for unfortunate events.
operation
of
reactors worldwide, greater public Opposltion to
nuclear power, and reliance on more expensive energy sources.
It
may
even have led
to
a more hostile view
of
other complex
technologies, such
as
chemical manufacturing and genetic engineer-
ing. The point
is
that traditional economic and risk analyses tend
to
neglect these higher order impacts, hence they greatly underestimate
the costs associated with certain kinds
of
events.
Although the TMI accident
is
extreme, it
is
by
no
means unique.
Other recent events resulting in enormous higher order impacts
include the chemical manufacturing accident at Bhopal, India, the
pollution
of
Love Canal, New York, and Times Beach, Missouri, the
disastrous launch
of
the space shuttle Challenger, and the meltdown
of
the nuclear reactor at Chernobyl. Following these extreme events
are a myriad
of
mishaps varying in the breadth and
size
of
their
impacts.
An
important concept that has emerged from psychometric
research
is
that the seriousness and higher order impacts
of
an
unfortunate event are determined, in part, by what that event signals
or
portends (28). The informativeness
or
"signal potential"
of
an
event, and thus its potential social impact, appears
to
be
systemati-
cally
related
to
the characteristics
of
the hazard and the location
of
tl1e
event within the factor space described earlier (Fig.
>!).
An
accident that takes many
lives
may produce relatively little social
disturbance (beyond that experienced
by
the victims' families and
friends)
if
it occurs
as
part
of
a familiar and well-understood system
(such
as
a train wreck). However, a small accident in
an
unfamiliar
•
•
•
•
Factor 2
Unknown
risk
• •
•
•
•
•
•
Accidents
as
signals
•
• •
• Factor 1
Dread
risk
• •
Fig. 4. Relat,ion be-
tween signal potential
• and risk characteriza-
tion for 30 hazards in
Fig.
1.
The larger the
point, the greater the
degree to which
an
ac-
cident involving that
hazard
was
judged
to
"serve
as
a warning signal for society, providing new information about the
probability that similar or even more destructive mishaps might occur within
this type
of
activity." Media attention and the higher order costs
of
a mishap
are likely
to
be
correlated with signal potential (28).
system (or one perceived
as
poorly understood), such
as
a nuclear
reactor
or
a recombinant DNA laboratory,
may
have immense social
consequences if it
is
perceived
as
a harbinger
of
further and possibly
catastrophic mishaps.
The concept
of
accidents
as
signals was eloquently expressed in an
editorial addressing the tragic accident at Bhopal (29).
What truly grips
us
in these accounts
is
not
so
much the numbers
as
the
spectacle
of
suddenly vanishing competence,
of
men utterly routed
by
technology,
of
fail-safe
systemS"
failing with a logic
as
inexorable
as
it
was
once-indeed,
right up until that very moment-unforeseeable. And the
spectacle haunts
us
because it seems
to
carry allegorical import,
like
the
whispery omen
of
a hovering future.
One implicatioh
of
the signal concept
is
that effort and expense
beyond that indicated
by
a cost-benefit analysis might be warranted
to reduce the possibility
of
"high-signal accidents." Unfortunate
events involving hazards in the upper right quadrant
of
Fig. 1
appear particularly likely to have the potential to produce large
ripples.
As
a result, risk analyses involving these hazards need to be
made sensitive to these possible higher order impacts. Doing so
would likely bring greater protection to potential victims
as
well
as
to companies and industries.
Analysis
of
Single
Hazard
Domains
Psychometric analyses have
also
been applied to judgments
of
diver
se
hazard scenarios within a single technological domain, such
as
railroad transport
(30)
or
automobiles (31). Kraus
(30)
had
people evaluate the riskiness
of
49
railroad hazard scenarios that
varied with respect to type
of
train, type
of
cargo, location
of
the
accident, and the nature and cause
of
the accident (for example, a
high-speed train carrying passengers through a mountain tunnel
derails due
to
a mechanical system failure). The results showed that
these railroad hazards were highly differentiated, much
like
the
hazards
in
Fig.
1.
The highest signal potential' (and thus the highest
potential for large ripple effects) was associated with accidents
involving trains carrying hazardous chemicals.
A study by Slovic, MacGregor, and Kraus (31) examined percep-
tions
of
risk and signal value for
40
structural defects
in
automobiles.
Multivariate
analysis
of
these defects, rated in terms
of
various
characteristics
of
risk, produced a two-factor space.
As
in
earlier
studies with diverse hazards, the position
of
a defect in this space
predicted judgments
of
riskiness and signal value quite
well.
One
defect stood out much
as
nuclear hazards
do
in Fig.
1.
It
was a
fuel
tank rupture upon impact, creating the possibility
of
fire
and burn
injuries. This,
of
course,
is
similar to the notorious design problem
that plagued Ford Pinto and that Ford allegedly declined to correct
because a cost-benefit analysis indicated that the correction costs
greatly exceeded the expected benefits from increased safety (32) .
Had Ford done a psychometric study, the
analysis
might have
highlighted this particular defect
as
one whose seriousness and
higher order costs (lawsuits, damaged company reputation) were
likely
to
be
greatly underestimated
by
cost-benefit analysis .
Forecasting Public Acceptance
Results from studies
of
the perception
of
risk have been used to
explain and forecast acceptance and opposition for specific technolo-
gies (33). Nuclear power
has
been a frequent topic
of
such analyses
because
of
the dramatic opposition it has engendered in the
face
of
experts' assurances
of
its safety. Research shows that pepple judge
the benefits from nuclear power to
be
quite small and the
risks
to be
unacceptably.great. Nuclear power risks occupy extreme positions in
SCIEN
CE
,
VOL
.
236
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psychometric factor spaces, reflecting people's views that these
risks
are
unknown, dread, uncontrollable, inequitable, catastrophic, and
likely to
affect
future generations (Fig. 1). Opponents
of
nuclear
power recognize that few people have died thus
far
as
a result
of
this
technology. However, long before Chernobyl, they expressed great
concern over the potential for catastrophic accidents.
These public perceptions have evoked harsh reactions from
experts. One noted psychiatrist wrote that "the irrational fear
of
nuclear plants
is
based on a mistaken assessment
of
the risks" (34, p.
8). A nuclear physicist and leading advocate
of
nuclear power
contended
that"
...
the public has been driven insane over fear
of
radiation [from nuclear power]. I
use
the word 'insane' purposefully
since
one
of
its
definitions
is
loss
of
contact with reality. The public's
understanding
of
radiation dangers
has
virtually lost
all
contact with
the actual dangers
as
understood
by
scientists"
(35,
p.
31).
Risk perception research paints a different picture, demonstrating
that people's deep anxieties are linked to the reality
of
extensive
unfavorable media coverage and to a strong association between
nuclear power and the proliferation and use
of
nuclear weapons.
Attempts
to
"educate"
or
reassure the public and bring their
perceptions in line with those
of
industry experts appear unlikely
to
succeed because the low probability
of
serious reactor accidents
makes empirical demonstrations
of
safety difficult to achieve.
Be-
cause nuclear risks are perceived
as
unknown and potentially
catastrophic, even small accidents will be highly publicized and may
produce large ripple effects (Fig. 4).
Psychometric research may be able to forecast the response
to
technologies that have yet to arouse strong and persistent public
opposition. For example,
DNA
technologies seem to evoke several
of
the perceptions that make nuclear power so hard to manage. In
the aftermath
of
an
accident, this technology could
face
some
of
the
same problems and opposition now confronting the nuclear indus-
try.
Placing Risks in Perspective
A consequence
of
the public's concerns and its opposition to risky
technologies has been an increase in attempts to inform and educate
people about risk. Risk perception research
has
a number
of
implications for such educational efforts (36).
One frequently advocated approach to broadening people's per-
spectives
is
to present quantitative risk estimates for a variety
of
hazards, expressed in some unidimensional index
of
death
or
disability, such
as
risk per hour
of
exposure, annual probability
of
death,
or
reduction in life expectancy. Even though such compari-
sons have
no
logically necessary implications for acceptability
of
risk
(15), one might still hope that they would help improve people's
intuitions about the magnitude
of
risks. Risk perception research
suggests, however, that these sorts
of
comparisons may not be very
satisfactory even for this purpose. People's perceptions and attitudes
are determined
not
only by the sort
of
unidimensional statistics used
in such tables but also by the variety
of
quantitative and qualitative
characteristics reflected in Fig. 1.
To
many people, statements such
as,
"the annual risk from living near a nuclear power plant
is
equivalent
to
the risk
of
riding
an
extra 3 miles in an automobile,"
give inadequate consideration to the important differences in the
nature
of
the risks from these two technologies.
In short, "riskiness" means more to people than "expected
number
of
fatalities." Attempts to characterize, compare, and regu-
late risks must be sensitive to this broader conception
of
risk.
Fischhoff, Watson, and
Hope
(37) have made a start in this direction
by demonstrating how one might construct a more comprehensive
measure
of
risk.
They show that variations in the scope
of
one's
17
APRIL
1987
definition
of
risk can greatly change the assessment
of
risk from
various energy technologies.
Whereas psychometric research implies that risk debates are not
merely about risk statistics, some sociological and anthropological
research implies that some
of
these debates may not even
be
about
risk
(5,
6). Risk concerns may provide a rationale for actions taken
on other grounds
or
they may be a surrogate for other social
or
ideological concerns. When this
is
the case, communication about
risk
is
simply irrelevant
to
the discussion. Hidden agendas need
to
be
brought to the surface for discussion (38).
Perhaps the most important message from this research
is
that
there
is
wisdom
as
well
as
error in public attitudes and perceptions.
Lay people sometimes lack certain information about hazards.
However, their basic conceptualization
of
risk
is
much richer than
that
of
the experts and reflects legitimate concerns that are typically
omitted from expert risk assessments.
As
a result, risk communica-
tion and risk management efforts are destined to
fail
unless they are
structured
as
a two-way process. Each side, expert and public, has
something valid to contribute. Each side must respect the insights
and intelligence
of
the other.
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ARTICLES
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