Sciencedebate.org, which is backed by about a bazillion scientific organizations has published the answers of the presidential candidates on twenty questions that revolve around issues that are on the border of science and politics (for example climate change.) You can find all the answers here, although I don’t think any of them are going to surprise anyone. Clinton’s answers look like they were put together by a PhD policy wonk committee and Trump’s look pretty much like his tweets. But that you could already figure out.
In his last answer, Trump says something that at first seems jaw droppingly stupid, but turns out to be quite a conundrum. Here is the question and answer:
20. Scientific Integrity
Evidence from science is the surest basis for fair and just public policy, but that is predicated on the integrity of that evidence and of the scientific process used to produce it, which must be both transparent and free from political bias and pressure. How will you foster a culture of scientific transparency and accountability in government, while protecting scientists and federal agencies from political interference in their work?
Science is science and facts are facts. My administration will ensure that there will be total transparency and accountability without political bias. The American people deserve this and I will make sure this is the culture of my administration.
“Science is Science and facts are facts” at first seems so self evident (and so opposite of Trump’s problems with actually relating to facts) that it is laughable. But hiding underneath that is a problem that philosophers have been struggling with for millennia and I am currently trying to get across to my critical thinking students, epistemology.
Epistemology is a big word (which Trump is probably unfamiliar with) which deals with the question of how we know what we know and what is knowledge. And it turns out that, after all is said and done, “science” is not Science and “facts” are not Facts.
When I was in high school, I was taught the “solar system” model of the atom, which at once a simplification of the current theory and an older theory (Google images for “general science” and see how many solar system atoms you see!). The electron cloud model has replaced this.
Was the former model (and my knowledge of it) a “fact?” Is the new model a “fact?” Some years from now will a science website put of a picture of an electron cloud with the legend, “This is what an electron is not!”? Philosophers debate endlessly about what all this means, but I can assure you that almost nobody (other than religious philosophers) are willing to argue that there is something call Truth with a capital “T.”
And the same is true with “science.” For the moment, I won’t quibble about the difference between science as a method and the results (and infrastructure) of that method. For the moment, I am referring to science as the latter: people in white coats, collecting and publishing data and drawing conclusions.
The scientific method is certainly a wondrous thing, but what we call “science” is certainly not Science! (with a capital S). The scientific method has many safeguards built in which are supposed to reduce or eliminate various kinds of bias, but because science is done by actual humans, we find many clever ways to allow that bias right back in and even create new biases.
Publication bias is a perfect example of a new bias that the infrastructure that is “science” has created. Positive (and newsworthy!) results get published and negative results get set aside. In a similar way, more research is probably done on profitable drugs than unprofitable. Money, politics, ego and who knows what else introduce biases that prevent “science” from ever being Science!
From the other end of the spectrum, Neil deGrasse Tyson said that what we need is a country where all decisions are “data driven.” His idea was roundly booed from all sides, and rightly so. What even counts as “data?” Trying to determine what the “real” unemployment rate is turns out to be a very thorny problem. Yes, some methodologies are much more defensible than others, but none is perfect. How do we make “data driven” decisions when the data itself is subject to doubt?
Here is a minor example I came across today — the harm to humans from wind farms (Say what? you might ask…). Here is a report that says wind turbines can be harmful to human health, and here is another which reaches pretty much the opposite conclusion: “the scientific evidence available to date does not demonstrate a direct causal link between wind turbine noise and adverse health effects.” They both look very “scientific,” So which data should we heed?
This is not to say that complete skepticism is a useful position either. Philosophers say that “knowledge” is a “justified, true belief.” Even if we allow that there may be no such thing as “absolute truth” we can effectively substitute “corresponds with reality” for “truth” in the above formulation, which we can say conforms with our current understanding of the world.
So, then we can say that while the jury may be out on how much harm wind farms cause humans, there is pretty good data that shows it is more dangerous to live next to an oil refinery than to a wind turbine. Or at least I would hope so. Using the best available information is the “justified” part of the definition above, even as we concede that such “knowledge” is by definition imperfect.
So, while it is not really true that “science is science and facts are facts” we can move forward on various issues on the basis of scientific consensus. When a vast amount research, using a variety of methods from different disciplines point in the same direction we are clearly “justified” in calling that knowledge and moving forward with that “knowledge,” even if it might be overturned later. Business forecasting is notoriously unreliable, but businesses push forward with their plans all the time none the less with the best information at hand. Society and government should do the same as well.
A classic example of this is the case for human caused climate change. Do we have a ton of information, from a wide variety of sources and disciplines that are all pointing in the same direction? Indeed we do. Given that the predicted outcomes of these trends are unfavorable in the long term, should we take action? That is clearly a justified “scientific” belief. Well, except for the guy who said that “Science is science and facts are facts.”
Trump has famously said that climate change science is a hoax invented and perpetrated by the Chinese. So, even when he spews what look like innocuous platitudes, Trump is both lying and straddling both sides of the issue.
Trump doesn’t believe that “science is science” but not in the way that philosophers would object. What he really means is “Science I like is real science and the rest of it is crap that we don’t need to listen to.” Which, unfortunately is a view that many people hold about science and no amount of philosophizing on epistemology or transparency on the part of scientists is ever going to change.