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Ecological Economics 5
METHODS
Evolving knowledge and the precautionary principle
Peter Dorman
The Evergreen State College, Olympia, WA 98505, USA
Received 9 January 2004; received in revised form 17 January 2005; accepted 17 January 2005
Available online 15 April 2005
Abstract
Existing formulations of the Precautionary Principle tend to be too weak or too strong. They are too weak if they limit
themselves to rejecting, for policy purposes, the bias in scientific research toward minimization of Type I error. This position is
already embodied in classical decision theory. They are too strong if they demand proof of safety on the part of producers of
potentially hazardous products and processes; this would eliminate too many beneficial activities. An intermediate position is
proposed: the function of precaution is to take into account what we do not know as well as what we do about the consequences
of human activity. This leads to a meta-rule: decision-making is precautionary if unpredictable revisions in knowledge lead
equally to unpredictable revisions in regulation. In the context of evolving knowledge about the ecological impacts of human
activities, this implies a shift toward significantly greater protection.
D 2005 Elsevier B.V. All rights reserved.
1. Introduction
The precautionary principle is widely viewed as
the centerpiece of ecological and public health policy,
yet it is difficult to say just what it means. Very
general invocations can be found in national laws and
international agreements, but the precise content
varies from one circumstance to the next. At times
the principle adopts a mild demeanor, as in one of its
most prominent versions:
In order to protect the environment, the precautionary
approach shall be widely applied by states according to
their capabilities. Where there are threats of serious or
0921-8009/$ - see front matter D 2005 Elsevier B.V. All rights reserved.
doi:10.1016/j.ecolecon.2005.01.015
E-mail address: [email protected].
irreversible damage, lack of full scientific certainty
shall not be used as a reason for postponing cost-
effective measures to prevent environmental degrada-
tion. (Rio Declaration on Environment and Develop-
ment, 1992).
At other times (and sometimes the same times) it
takes a much stronger position:
Producers and proponents [of industrial activities]
therefore must bear the burden of demonstrating and
maintaining safety of products, projects, and technol-
ogies. (White Paper on Precaution of the City and
County of San Francisco, 2003).
The result is that precaution is often adopted by
official bodies as a relatively unobjectionable state-
3 (2005) 169–176
P. Dorman / Ecological Economics 53 (2005) 169–176170
ment of intent, even while its advocates and enemies
view it as a doctrine with revolutionary implications.
The position to be developed here holds that the
first interpretation is too permissive and the second
too restrictive. Precaution that goes beyond conven-
tional risk assessment while remaining analytically
defensible needs a new foundation. In the next section
I will explain why rejection of scientific certainty is
too weak a posture, and why the demand that
processes be proven safe before being adopted is too
strong. Section 3 takes a brief detour to address the
question of rights and their relation to precaution. The
final section offers an alternative approach based on
the goal of taking decisions that best anticipate the
choices we are likely to make in the future when we
better understand the risks at stake.
2. Too little, too much
The first claim commonly attached to the Precau-
tionary Principle is that lack of scientific certainty
should not preclude action to forestall risks to the
environment and human health. From a political
standpoint such a demand is understandable and even
necessary: crucial environmental issues are typically
adjudicated by government agencies and international
treaty organizations under pressure from business
interests. This pressure is usually so effective that the
default position of these bodies is to permit industries
to proceed with their plans, and that any interference
requires enormous countervailing support. The dis-
course on which regulators often rely for this support is
that of an objective scientific process whose evidence
is dispositive: evidence that bforces the handQ of theregulator. (Coglianese and Marchant, 2003).
In such situations the debate over policy becomes a
dispute over the definitiveness of the relevant science.
Those favoring action to protect the environment are
forced to argue that the weight of available evidence is
clear and sufficient, while business interests argue that
the evidence is still murky, contested and ill-under-
stood. Given the conservatism intrinsic to the scien-
tific process, as well as the ability of powerful
economic interests to finance their own research, it
is a debate that puts environmentalists at a disadvant-
age. A current example is provided by the dispute
over what measures to take in response to the threat of
global climate change. Even after decades of intensive
research, evidence in favor of human-induced global
warming is preponderant but falls well short of
certainty, and little confidence can be given to any
specific forecast of the general extent of projected
warming or its ecological consequences.
In this context it is reasonable for environmental
advocates to reject the argument that evidence must be
near-certain before any action can be taken. By the
time the evidence is all in we may have permitted
costly, irreversible effects to occur. One way to escape
the compulsion to speak from scientific certainty is to
have institutions commit themselves to action in its
absence, which is what the weakest version of the
Precautionary Principle proposes.
A deeper justification for this stance can be found in
the conflict between research and decision approaches
to uncertainty. By uncertainty in this context, we mean
a situation in which the available evidence is not
sufficient to establish an explanation or prediction with
complete certitude—in other words, the normal state
of affairs. This uncertainty can be thought of in the
framework of Types I and II error, where the first refers
to the possibility that a proposition, held to be true, is
actually false, and the second to the reverse possibility
that a rejected proposition is actually true. Logical
propositions can be proved one way or the other, but
empirical claims can never shed all possibility of error.
The best that one can do is to choose to bear the least
likely, or damaging, risk of being wrong.
Scientific research is based on the single-minded
minimization of Type I error. Typically experimental
protocols are devised to exclude spurious influences
that might result in false positives, hypothesis tests
must reduce such a risk to under 5% likelihood to
warrant bsignificantQ findings, and many corrobora-
tive studies are required to confer on a proposition the
status of bacceptedQ. Clearly, scientists are far more
concerned about unwittingly accepting a false hypoth-
esis than rejecting a true one. Errors that lead to such
acceptance, if uncovered, can be career-threatening,
whereas no researcher should expect to be pilloried
for the opposite mistake.
Such conservatism on the part of science is entirely
justified. The complexity of the scientific enterprise
has led to a vast division of labor in which each
research team focuses on a narrow set of questions by
taking as given the findings of all other teams, past
P. Dorman / Ecological Economics 53 (2005) 169–176 171
and present. If even one of those findings, which the
scientific community has come to rely on, is found to
have been in error, all the work that depended on it is
called into question. Type II error, at worst, slows the
rate of progress in science; Type I error undermines
and corrupts it. The bias we have described may well
be one of the core characteristics that distinguishes
science from all other forms of human inquiry.
Practical decision-making, on the other hand, has
no built-in bias toward either sort of error. What
matters is the cost of being wrong in one direction or
the other. In the case of global climate change, for
instance, societies must determine what policies to
enact in order to counter the accumulation of green-
house gases. Policy decisions ought to depend on
what effects we anticipate at various concentrations of
these gases, which in turn depend on a large number
of hypotheses about the mechanisms governing the
global climate system, the human and ecological
responses to climate alteration, etc. It would make no
sense to set policies on the basis of a dogmatic
avoidance of Type I error (refusing to accept any
hypotheses about the chain of causation linking, say,
the burning of fossil fuels to negative human or
environmental consequences without overwhelming
validation) than it would to set them on the basis of a
dogmatic fear of Type II error (refusing to take
account of the possibility that some of these proposed
linkages are false). In fact, orthodox decision theory
tells us to choose a course of action that maximizes
the expected value of future outcomes, so that the cost
of each sort of error, rather than a priori bias, serves as
the judgment weight.
In the simplest case, a policy might depend on a
single proposition, for instance that a particular
chemical compound is mutagenic at a defined con-
centration. We can either ban or authorize use of the
chemical. Thus we face the risk of Type I error, whose
cost is the economic value foregone through erro-
neous prohibition, or Type II error, measured by the
negative health effects endured as a result of
erroneous approval. Standard decision theory tells us
to multiply the estimated probability of each sort of
error by its associated cost and then choose the least-
cost alternative. Only in the unlikely case that the
health costs of mutagenicity are insignificant com-
pared to economic costs of doing without the
chemical would the decision process approximate
the error bias of scientific research. On the contrary, in
most of the contexts we are concerned with the
relative costs to public health and the environment are
so severe that a reverse bias is called for, so that
correspondingly small likelihoods of Type I error call
for prudential regulation. It is probably this applica-
tion of decision theory that many proponents of the
Precautionary Principle have in mind when they
advocate a default position on the side of hypotheses
that human actions cause environmental harm.
If the most common versions of the Precautionary
Principle have such a well-established basis, what is
the problem? It is that the Principle, by ratifying
decision algorithms already accepted by policy pro-
fessionals, adds nothing new. It does not take us past
cost–benefit analysis, for example, which is a
particular application of the expected value criterion.
This is not a crime, but we should demand more, for,
as we will see, in important respects conventional
decision theory is not precautionary, in the sense that
it does not distinguish between risks we understand
well and those we understand poorly, taking extra care
with the latter.
On the other hand, some versions of the Precau-
tionary Principle overreact to the single-minded
minimization of Type I error on the part of scientific
research by advocating an equally dogmatic minimi-
zation of Type II error. This appears to be the meaning
proposed in the Wingspread Statement:
When an activity raises threats of harm to human health
or the environment, precautionary measures should be
taken even if some cause and effect relationships are
not fully established scientifically. In this context the
proponent of an activity, rather than the public, should
bear the burden of proof. (Wingspread, 1998).
A similar position was taken by the city of San
Francisco in the White Paper quoted above.
It is difficult to be sure what is being advocated
since three distinct propositions are being put forward.
(1) Acceptance of human activities posing risks to the
environment and public health should not be the
default public policy. (2) The burden of conducting
research to determine the extent of the risk should be
borne by those who favor or benefit from the activities
in question. (3) Potentially risky activities must be
bprovedQ safe to be permitted.
P. Dorman / Ecological Economics 53 (2005) 169–176172
The first has already been shown to be implicit in
conventional decision theory. The second is a distinct
recommendation, separate from any particular bias in
the evaluation of risk. It has the advantage of
extending the polluter pays principle to the costs of
uncertainty and its reduction through research, but the
greater disadvantage of relying on those with a stake
in an activity to inform us of its risk—the problem of
incentive compatibility. Indeed, there have been all
too many cases in which firms seeking to profit from
products provided false assurances of their safety.
(Markowitz and Rosner, 2002) It is unlikely that
environmentalists who invoke the Precautionary
Principle truly wish to have environmental research
conducted by, and therefore responsive to, the affected
businesses.
The final proposition is excessive. One does not
have to be a supporter of Popper in all matters of
methodology to accept the argument that falsifica-
tion, not proof, is the way of empirical research.
(Popper, 1968) It is simply not possible to bproveQany product or production method safe. Hence some
measure of environmental risk is unavoidable if
human beings are to do anything at all. Surely the
degree of risk we can accept has something to do
with the cost we endure if it eventuates as well as
the cost of avoiding it, even if we do not accept the
rigidity of the formal cost–benefit framework. As has
been said, if early humans had been precautionary in
this overly strong sense, we would never have
chosen to domesticate fire. (Rubin, 2000) It is not
necessary to make a formal case against the single-
minded minimization of environmental (Type II) risk
here; the task is not difficult and has been under-
taken elsewhere (Sunstein, 2003).
Thus we have two sorts of criticisms of the
Precautionary Principle as it usually appears. Either
it is so mild it disappears into the standard method-
ology of policy science, or it is so stringent that it
precludes nearly all human activity. What we need,
however, is an approach to precaution that responds
to the complacency of standard policy-making in a
way that also binds itself to the full range of
available evidence, a middle ground between the
paranoia of assuming that all fears are valid and the
hubris of thinking that we can predict, even
probabilistically, the ultimate consequences of our
actions.
3. A digression on rights
Before proposing a reformulation of precaution, it
is necessary to clarify the contexts in which it applies.
Despite the comments in the previous section, there
exists a range of situations in which something close
to the more extreme version of precaution, the
minimization of potential environmental harm with
no consideration of the costs of being excessively
restrictive, is applicable. This arises when there is an
unambiguous assignment of environmental or health
rights to an individual or community.
In such cases the burden of proof is on those in a
position to violate these rights to demonstrate that
there is no reasonable expectation that a violation will
occur. An example should make this clear. Suppose I
return home after being away for a week to find a
leftover casserole in my refrigerator. I remember that
this meal was delicious when I made it, but, having sat
for a while, it now poses a threat of food poisoning.
Let us say that, based on my best judgment of such
things, the probability of actually being poisoned is
1%. Weighing my appetite against my prudence, I
may decide to take a chance and reheat the food.
Now suppose that I operate a restaurant, and that I
have a casserole sitting in my cooler that was made
over a week ago. Can I serve it to my customers,
knowing that the risk of food poisoning is 1%? Surely
not. Diners have a right to expect that, when they
order food from a restaurant, all reasonable efforts
have been made to avoid health risks. Typically,
restaurant inspections aim to reduce risks to such a
level that no one can foresee potential harm. By
serving this food I would be violating the law as well
as widely agreed-on ethical responsibilities. Note that
it is not relevant for this parable that a 1% chance of
harm is a lower probability than that which often sets
the upper boundary for statistical significance in
research tests of environmental and health risk.
It is this insight that underlies one version of the
precautionary principle. Where the public or some
portion of it is invested with a right to not bear a
health or environmental burden, the standard for
potential violators must be stringent. It is their
responsibility to demonstrate that there is no plausible
threat of harm. To the extent that their ability to
predict the outcome of their actions is clouded in
uncertainty, they must be that much more careful, just
P. Dorman / Ecological Economics 53 (2005) 169–176 173
a driver should reduce her speed in a thick fog. This
principle should not be controversial.
The problem is that pure rights-based precaution is
a special case. There are three reasons for this:
1. In a great many questions involving public
health and the environment, there is no agreed upon
basis for assigning rights; in fact, analysis on the basis
of rights may be completely wrongheaded. A dramatic
example is provided by Rubin (2000): what are we to
do about the threat posed by a collision with an
asteroid or other near-earth object? This has all the
trappings of a situation for which precaution should
be relevant: it is a low-probability, but hardly
impossible, event of cataclysmic environmental and
health consequences. Science cannot tell us just how
likely it is, but what we do know indicates we should
pay attention to it. Rights are out of the question,
however; the asteroid is not a culpable agent. The
question of how much time, effort and money to
commit to forestalling this threat must be answered on
practical grounds alone.
2. It is often the case that rights–even fundamental
rights–are in conflict. A particular striking example is
the tension between indigenous land rights and
environmental conversion. After centuries of dispos-
session, indigenous peoples in many parts of the
world are gaining recognition for the right to some of
the ancestral lands. Surely those who now profit from
past acts of displacement and even annahilation
should accept this minimal duty. On the other hand,
these lands may sometimes be put to uses that threaten
significant ecological values, such as logging in old
growth forests, harvesting fish or wildlife at poten-
tially unsustainable levels or permitting mining
operations that results in water or air pollution. (I
am not claiming that this is common, only that it
happens.) Neither right negates the other: rights of
non-native populations to the environmental com-
mons and its services are not erased by the land rights
of natives, nor vice versa. Rather, the competing rights
must be adjudicated in some fashion, ideally taking
account of the most important interests of each party.
While such conflicts when they arise, are dramatic, we
see similar frictions arising from the overlapping and
competing claims of many communities to portions of
the environment. So long as we embrace a world of
multiple jurisdictions, environmental rights will typ-
ically be less than absolute.
3. The most important limitation to rights-based
precaution is that few rights are so fundamental that
they demand enforcement irrespective of the practical
consequences. A dogmatic adherence to rights is as
unacceptable as a dogmatic (e.g. purely utilitarian)
dismissal of them. A much-discussed case in which
this is perfectly clear concerns the merits of using
DDT to control malaria in at risk countries (The
Lancet, 2000). Although one could argue that an
uncontaminated environment is a right, it is also true
that malaria is extremely costly, and that it is at least
possible that application of DDT could be an
appropriate measure under some circumstances. By
bringing up this example, I am not suggesting that the
case for DDT has been made, just that it is a case. To
rebut it one would have to show that, when the
relevant alternatives are considered, the costs of
banning DDT are either nonexistent or at least
acceptable. At a deeper level, an example such as
this should not be taken as an endorsement of the
rights-neutral stance of cost–benefit analysis: it just
means that costs matter. If we accept this view, we
need a different sort of precautionary principle, one
that tells us how we might apply precaution to an
analysis of tradeoffs.
4. Precaution as a decision meta-rule
The broad context is this: as our technological
prowess increases, human beings are increasingly
taking actions that place fundamental ecological
values at risk. Whole ecosystems are threatened
with disappearance, the global mechanisms that
organize the cycling of energy and materials on
which living systems depend are rendered vulner-
able, and the consequences for human well-being
are potentially profound. These are all risks, but we
are seldom able to place precise probabilities on
them, or even to map the true state of our
ignorance. The mechanisms that regulate these
systems are at best dimly understood, and every
few years we receive a new shock that compels us
to alter our assumptions about what is safe, what is
dangerous, and what is at stake. Our problem is not
simply one of calculating on the basis of what we
know, as orthodox decision theory would have it,
but of taking account of the extent of our ignorance,
P. Dorman / Ecological Economics 53 (2005) 169–176174
and the potential this poses for blundering into
disasters we can barely envision.
From a theoretical standpoint, the general problem
is this: how should we alter our basis for making
decisions when we suspect we do not know important
aspects of the problem—particularly when the costs
for being wrong may be severe (or themselves little
known)? As long as we view each decision as an
isolated moment in time there is no solution; what we
do not know is what is by its nature not an input into
rational decision-making. We can, however, take the
step of locating our moment’s place in the passage of
time. This has two consequences: it redefines each
decision as one in a sequence of decisions, and it
permits the possibility that our understanding of the
risks and benefits will improve from one decision to
the next. Putting these together, we can restate the
problem as that of making a decision in one period
(the present) that will appear to have been appropriate
(however this is defined) in the future when we have
more information to go on. This imposes a particular
form of time consistency on the decision process, one
for which we have ample tools of analysis.
Let ut be the information set available to decision-
makers at time t. Assume that this set is altered over
time through a sequence of random (unpredictable)
perturbations. Let x be a continuous regulatory
parameter, such as a threshold limit value. (Continuity
simplifies the exposition but does not alter the logic.)
Suppose decision-makers make full use of u to
establish a particular value of x that best satisfies
their criteria. (It is convenient that this model does not
require us to specify the precise algorithm used in this
process; it could be a present value calculation or
something else.) Thus, corresponding to any ut is an
x*t, where x* is this best-practice determination of x.
Given this set of definitions, and assuming that the
decision criteria are unchanged over time, we know,
from the Rule of Iterated Expectations, that
Eðx�tþ1 4 utÞ ¼ x�t
This simply means that our best guess of what
these same decision-makers, using the same algo-
rithm, will do in the future, when more information is
available, is the decision they make today. It follows
from the reasonable assumption that changes in
information are unpredictable. It has the additional
implication that there is no difference between
anticipating the decisions of the near- and the far-
future, since the expectation relationship is recursive:
today’s best choice is the expectation of tomorrow’s,
which is the expectation of its tomorrow, and so on.
The logic behind this result lies at the basis of
modern research into financial markets. In particular,
it establishes the sequence of xt*, xt+1* , xt+2* , . . .., xt+n*as a martingale, random in its first moment. (LeRoy,
1989) One implication is that if profit in the regulated
sector is a first-order function of x, a risk-neutral
investor will be indifferent between two return
streams with different time structures whose present
value equality is predicated on the stationarity of x*.
This is analogous to the fair-game condition in
financial martingales.
This simple result has profound significance for
environmental decision-making. It says that, if deci-
sions are made in the best possible way using all
available information, and if the values of regulators
remain unchanged (or themselves fluctuate unpredict-
ably), there will be no systematic tendency for
regulations to be loosened or tightened over time.
The impact on regulation of an unpredictable addition
to our knowledge will itself be unpredictable. Of
course, by definition, all true additions or adjustments
to our knowledge are unpredictable. Incidentally, the
existence of a regulatory martingale is a necessary but
not a sufficient condition for the efficient use of
information, since the sequence of decisions could be
unpredictable yet all might fall short of the criteria on
which they are supposed to be based. (Among the
many other things they are said to be capable of,
typewriting monkeys could produce unpredictable
environmental regulations.) This distinction between
necessary and sufficient conditions is often over-
looked in the efficient market literature.
The principle of sequentially unbiased variation is
illuminated in the breach. Consider the opposite case:
suppose we have a regulation which is repeatedly
tightened with each new infusion of information. If it
is a TLV, for example, it is lowered year after year and
never raised. This would be a violation of the
efficiency standard specified above, and it is easy to
see why. To lower the threshold, if the decision
process is rational, is to indicate that it was previously
too high. This could be justified on the grounds that it
was impossible to foresee that this would be the case,
P. Dorman / Ecological Economics 53 (2005) 169–176 175
but such a defense is weakened with each repetition.
Moreover, to the extent that ostensible changes in the
information set on which the threshold was based
proved to be systematically biased or predictable, this
is an indication that information enabling such
predictions was available but unused. That is, if it
seems as though bnewQ information has been repeat-
edly telling us the same thing, it is likely that it is not
new at all; rather we have not been listening.
In general, this is precisely what we find in many,
if not most, fields of environmental regulation. A
pattern is established in which, with little information
to go on, minimal regulation is adopted. As studies are
conducted and evidence mounts, restrictions are made
tighter and tighter. In some cases, after the evidence
becomes incontrovertible, outright prohibitions are
enacted. Analysts of regulation sometimes survey
these trajectories and conclude that bscienceQ was
playing its appointed role in guiding public decision-
making, but this is mistaken. Regulations that are
constantly adjusted upward are systematically too low.
Regulators are failing to see that they are predictably
failing to anticipate future reassessments, and society
bears the cost–which may be substantial–over the
entire duration. (Harremoes, 2002).
Precaution in the sense advanced in this paper is a
product of our lack of understanding in a context in
which there is an evident pattern in the evolution of
our ignorance over time. This pattern should be
exploited to make the best possible predictions of
what our future state of knowledge will come to be,
and these in turn should provide the basis for
prudential regulation.
5. Implementation
As a meta-rule, the Precautionary Principle has ex
ante and ex post implications. The latter is more
straightforward: decision-making bodies should mon-
itor instances in which regulations are revised in the
light of new information. This could be as simple as
documenting all regulatory interventions attributable
to an agency over a number of years, and observing
the balance between decisions to intensify and relax.
If an imbalance appears that would be unlikely to
occur in a truly random process, and is not explained
by changing criteria, the agency would be called upon
to identify new procedures that would promote a more
efficient use of information. The sufficiency of these
reforms could be determined through continued
monitoring of decision outcomes.
But what procedures might these be? This raises
the question of ex ante measures to implement
precaution, and these are more difficult to specify at
a high level of generality. To orient ourselves, it will
help to review the movement toward fuller use of
information described in this paper. The most limited
use is that which relies only on statistically significant
results of empirical research—information that passes
the test of minimizing Type I error. Such an approach
excludes other findings whose Type I error may
exceed the cutoff normally employed in published
research, but which are nevertheless significant from
the standpoint of Type II error costs to public health
and the environment.
Standard decision theory advocates a shift toward
the incorporation of all findings that can be expressed
in the form of a probability distribution. Even
hypotheses of environmental risk with very high p
values (high likelihood that they are untrue) should be
entered into expected value calculations, with their
low probabilities multiplied by their (possibly high)
costs if they should prove to be correct. This is not
controversial from a theoretical standpoint, although it
is a difficult move to undertake for political reasons:
those who profit from activities that pose risks to
health and the environment have invoked bscienceQ(minimization of Type I error) as the only sound basis
for regulatory policy.
The Precautionary Principle, as characterized in
this paper, goes one step further by asking us to utilize
all available information so as to anticipate, to the best
of our ability, the judgment that would be made in the
future when the relevant issues are better understood.
This expanded information set includes the full range
of nonstandard and informal data which, whether or
not they qualify as research findings, would be of use
to someone attempting to predict the further evolution
of knowledge. Above all, this includes the past
trajectory of additions to our understanding that have
brought us to the present moment. In every field of
environmental policy, this points to the tendency for
researchers to discover new linkages between human
intervention and ecological response, new processes
that serve to integrate ecological systems, and reduced
P. Dorman / Ecological Economics 53 (2005) 169–176176
thresholds at which threats to human or ecosystem
health are consequential. Rationally, we ought to
expect that a portion of our current ignorance will be
replaced by future knowledge of this sort, and we
should continue to maintain this expectation until
there is no longer this predictable pattern to scientific
learning. Under the present circumstances, then,
greater ignorance in itself implies increased likelihood
of environmental risk.
This is the crux of the precautionary approach as
outlined in this paper. More schematically, we can say
that precaution, in this sense, is based on the
information employed in the expected value calculus
plus such additions as:
n the catalog of ongoing research projects, including
the hypotheses being tested and their potential
implications for risk assessment;
n theoretical grounds for suspecting potential risks,
even in the absence of empirical tests;
n research results pertaining to one element of a
complex system, even when little is known about
other elements more germane to a policy question;
n and known areas of ignorance–those aspects of the
problem about which it is known that nothing is
known–and their potential implications for risk in
light of what we now know about past ignorance.
This list points to a direction to follow, but it is
still too general to provide much guidance to
practical decision-making. What is needed is a
number of carefully analyzed retrospective cases,
identifying the additional sources of information that
precaution could have drawn on and the manner in
which they could have been used. Of course, for
purposes of control we should include instances in
which risks that were suspected in an earlier period
were later found to be illusory. As we perform such
analyses across a variety of potential health and
environmental impacts, biological, chemical and
physical mechanisms and levels of scientific under-
standing, we will be in a better position to formulate
precautionary procedures for the present and future.
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