Week 4: Risk and values in science Flashcards
Should values play a role in science? yes and no
Yes: Scientists should be honest in reporting their results, they should be open to criticism
Scientists have a moral and professional responsibility not to threaten the integrity of scientific practice.
No: Science is the pursuit of objective knowledge about matters of fact. There is no room for subjective attitudes in science
Integer scientific practice requires that scientists put their social and political attitudes aside in scientific reasoning.
Should values play a role in science. middle ground
Scientists have a moral and professional responsibility to put their social and political attitudes aside in scientific reasoning.
Science aims at producing knowledge. Therefore, only epistemic values should play a role in research practice.
Views from the 20th century: Popper, Lakatos and Kuhn
Matters of fact are objective. We can make empirical statements about them.
Feelings and preferences are subjective. We can express our attitudes towards them.
Popper and Lakatos argued likewise that there is no room for values in science. They argued that there had to be unambiguous rules of scientific reasoning that, when followed, would result in ever more empirically accurate theories.
Kuhn disagreed. According to Kuhn, science is not a rule- governed process. He was mocked for this by Lakatos and others.
Kuhn on values in science
Actually, Popper, Lakatos and others are relying on values. They appeal to a value for determining ‘good’ science: pursuing empirical accuracy.
But accuracy is not the only value scientists in fact rely on (and should rely on) when choosing between theories/ paradigms. Other relevant values include consistency, scope, simplicity, and fruitfulness.
Kuhns values list
Accuracy
Consistency
Scope
Simplicity
Fruitfulness
Accuracy
Results from experiments and observations should be in agreement with the predictions a theory makes
Consistency
A theory should be consistent with other theories in the same area of science
Scope
A theory should have a broad scope. We should be able to apply it in a range of conditions beyond those for which it was initially designed
Simplicity
A simpler theory is typically preferred over a more complex one
Fruitfulness
A theory should be able to disclose new phenomena or to uncover new relations between facts that were previously only understood in isolation
Choose between competing theories depends on two factors according to Kuhn
Objective: The values as such (accuracy, consistency, simplicity, etc). These are objective indicators of how close a scientific theory is to the truth
Subjective: The weighting of values. Scientists can make different judgement calls about which, or combination of, values is more important in their choice between theories/paradigms
Should values play a role according to philosophers?
Positivists: no
Popper: no
Lakatos: no
Kuhn: yes
Two kinds of values
Epistemic and non-epistemic
Epistemic: The ones Kuhn discuss. There are values that we have reason to believe will help us attain knowledge and understanding of the world. A theory that ‘scores high’ on epistemic values is more likely to be correct.
Non-epistemic: Social, ethical or political values. Non-epistemic values do not contribute directly to the pursuit of knowledge about the world.
Vavilov
Russian botanist and geneticist. Contributions to science led to major improvements in crop breeding practices.
Driven by desire to improve food security of the poor
Imprisoned bc his theoretical work was considered anti-soviet.
He was clearly motivated by values, but does not imply that his reasoning about evidence was distorted by values
The soviet regime did reject theory and evidence based on political values
Vavilov
Russian botanist and geneticist. Contributions to science led to major improvements in crop breeding practices.
Driven by desire to improve food security of the poor
Imprisoned bc his theoretical work was considered anti-soviet.
He was clearly motivated by values, but does not imply that his reasoning about evidence was distorted by values
The soviet regime did reject theory and evidence based on political values
Epistemic values (popper and Kuhn)
Knowledge-related values such as accuracy, consistency, fruitfulness, explanatory power and predictive capacity.
These values help us identify theories that yield knowledge about the world.
Epistemic values play a role in evaluating evidence. They are guides to the truth
Popper and the logical positivists focused on one criterion in judging the ‘goodness’ of a theory: empirical accuracy.
Kuhn argued that there is room for different criteria in deciding between two theories (or paradigms).
These criteria should be considered values, since scientists can have a preference for certain values over others.
For example, one scientist might prefer a more accurate theory, another a theory that is more consistent with other theories.
Non-epistemic values
socio-economic, ethical, political
pursuing these does not directly help contribute knowledge about the world
Used when looking at a given theory/hypothesis and looking to figure out whether it should be accepted or not. - where do we put the standard? when is there enough information?
Further distinction between values
Epistemic values are guides to the truth. Cognitive values indicate how easy it is “to think with” a theory.
* Simplicity and consistency with other theories make theories easier to think with, but don’t necessarily point to the theory being true.
* Accuracy and internal consistency are genuine epistemic values.
Kind of values
Epistemic:
- empirical adequacy
- internal consistency
- predictive capacity
- explanatory power
Cognitive:
- Simplicity
- Scope
- Fruitfulness
Non-epistemic:
- Political values
- Ethical values
- Economic values
Value free ideal for science
Non-epistemic values are allowed to play a role in the selection and formulation of problems to study, or in setting ethical constraints on a research project.
But, according to the value-free ideal for science, non-epistemic values
should not be allowed to play a role in evaluating scientific evidence.
The argument from inductive risk
Scientific evidence is always incomplete and uncertain. There is always a chance that the evidence speaks in favor of [or against] the hypothesis, but that the hypothesis turns out to be false [or true] nonetheless.
Given the incompleteness of evidence, scientists need to go beyond the evidence when deciding to accept or reject the hypothesis they are testing.
Since we should expect scientists to be responsible citizens like everyone else, they should make responsible decisions when making the leap from evidence to acceptance or rejection.
Therefore, scientists should balance the risk of accepting a false hypothesis and rejecting a true one in light of the societal consequences of their decision.
Two examples of inductive risk
Covid and inductive risk
In the first months of the pandemic, there was widespread uncertainty about whether
face masks would be effective against spreading SARS-CoV-2.
* If scientists were to mistakenly underestimate the effectiveness of masks, the virus could spread rapidly.
* If scientists were to mistakenly overstate their effectiveness, supplies for health workers might be depleted.
Insects, insecticides, and inductive risk
Wild bee populations have declined steeply in recent years.
Neonicotinoids (used in insecticides) have been shown to cause memory and navigation problems under lab conditions.
It is unclear what these studies tell us about the role of neonicotinoids in depleting wild populations.
✴ What should scientists tell policy makers?
Bullshit in science
It is impossible for someone to lie unless he thinks he knows the truth … Producing bullshit requires no such conviction.
By virtue of this, bullshit is a greater enemy of truth than lies are.
Bullshit of the isolated fact
cherry-picking results and taking them out of context.
Exposing this form of bullshit requires scientific expertise in a particular scientific domain.
Bullshit of universal standards
appealing to an objective yardstick for determining how much evident is sufficient.
Exposing this form of bullshit requires the philosophical insight that there is no context-independent criterion of sufficient evidence.
Denialism
Bullshit + harm = denialism
To deliberately challenge a robust scientific consensus in a context where this is likely to harm science and/or society.
Denialists often use ‘bullshitting’ strategies of cherry-picking or requiring unreasonably high standards of evidence.
But when do we speak of there being a scientific consensus? And when are standards of evidence unreasonable?
Invasive species: denialism or disagreement?
The IUCN definition of invasive species is value-laden: “species introduced by man [sic] into places out of their natural range of distribution, where they become established and dispersed, generating a negative impact.”
Predictions about whether an introduced species will likely be harmful are steeped in uncertainty.
The notion of ‘invasive species’ is itself value-laden. Is that a problem?
Ecologists’ predictions about the effects of invasive species involve many uncertainties.
There is ample room for disagreement about how to best navigate inductive risks
How do the two cases in Elliott’s chapter show that values can either conflict with or advance science?
Conflict:
- Scientists wanted to improve agriculture during a time when Russians where starving. The Russian regime wanted soviet science based on soviet ideas and so they rejected Vavilov and accepted Lysenko’s views. It’s an example of science being hijacked by ideologies.
- The Soviets persecuted science that didn’t fit with their soviet ideologies. Lysenko’s experiments and results were not described carefully.
Advance:
- In Colborn’s case however, values seemed to play a mostly positive role in her research. Her strong environmental values (passion to protect the environment) led her to discover the hormonal disruptions in animals due to the toxins she was researching.
- Critics complained that she tended to leap ahead of the results and drew stronger conclusions than necessary”
- She had rather overstate the risk than not informing the public.
Why does Douglas believe that researchers have a duty to relate to social and ethical values?
Non-epistemic values should be included because Douglas thinks they play an important role in the selection and formulation of the problems being studied. Also they should be used as a method for setting ethical constraints on the research project.
“No universal answer to this question is available because the contexts in which these judgments must be made vary so widely. Whether the evidence available is sufficient depends in large measure on what the risks are of getting it wrong.” - s.12
Social and ethical values need to be used to properly measure the risks of getting something wrong.
“Yet hypothesis formation and testing are not sufficient for something to be an acceptably strong scientific underpinning for a policy decision. The crucial issue is usually how much evi- dence and testing there has been, what kinds of testing have been done, and whether the available evidence is enough. Deciding that it is enough is in part a political decision, as it requires the weighing of the acceptability of uncertainty”
‘the bullshit of universal standards’
we have a universal standard of evidential support which all claims must meet in order to be “scientific”. however, douglas says there is no such standard (especially when evidence is from multiple sources) and any appeal to such standard is pure bullshit
universal-standards bullshit assumes that there is a threshold that any body of evidence must meet before it is “scientific” and “proven”, only then can we act on it
douglas says we should not want one, only standard we should have is that we consider ALL available evidence, instead of aiming to reach a universal standard
What does Douglas understand by the expression ‘cherry-picking facts’ and why does she see it as problematic?
“Cherry-picking one’s facts, thus producing bullshit of the isolated fact, is particularly problematic in the case of the climate change debate” - s. 3
In complex cases one must have as much of the available data as possible to be able to see the full picture. With cherry picking Douglas points to the fact that it can be very time consuming, both collecting and presenting this big amount of data therefore it is much easier to pick and choose one’s facts.
“It is little wonder that with such a complicated issue and such high stakes, the lure of selecting particular facts, even true ones, that in isolation prove totally misleading, is so tempting” - s. 4
- picking the circumstances that fit your hypotheses/view/opinion
- only amounts to cherry picking when there is a scientific consensus
- can be hard to determine when cherry picking is going on, which is why there needs to be a scientific consensus to identify it.
