The fork in the road: science versus denialism and conspiracy theories

The world is awash in information. Never before have people had as much access to humanity’s collective knowledge as we do today. You want to know when the Normans conquered England? How many people use Weibo? Or what Machu Picchu would have looked like in its glory days? Simply pull out your phone and ask Siri. 

 

This cornucopia of knowledge should mean that people are in the position to make the best decisions possible. From the insurance plans that best fit their needs to voting for candidates or political parties that support policies that return optimal outcomes for individuals and society as a whole. Beyond individuals, this wealth of information should mean that evidence-based policy would be easy to pursue and outcomes for nations continually improving.

 

However, this is clearly not the case. The availability of knowledge doesn’t mean that evidence, fact and truth are utilized. Preconceived belief and ideology are important filters through which evidence is evaluated. Yet, what is really disheartening about the use of knowledge and evidence is how others (individuals and organizations) with political and economic agendas filter and manipulate what is channelled to various audiences.

 

While we might naively refer to the modern era as one based on information and the democratization of evidence and knowledge, the reality is that we live in the era of disinformation. Disinformation is the active and knowing creation and spread of false information, like politicians saying a fair election was stolen. Misinformation is the cancerous offspring of disinformation, where this false information is shared by those unaware of its nefarious origins. Disinformation and misinformation have the power to derail robust democracies and motivate atrocities.

 

The study of the origins and valuation of knowledge is a complex, convoluted and challenging area to say the least. But it is not esoteric nor just academic. Knowledge and understanding are the cornerstone of societal well-being, technological development and ultimately underpin democracy. Public policy driven by misinformation and dismissal of basic facts is simply ill-equipped to deal with many of the problems we face. This is easily showcased by the dismal, and frankly embarrassing, chaotic COVID-19 response in the United States -a clear failure for proponents of evidence-based policy.

 

Knowledge and belief arise through a number of different endeavours that span social influences, logic and reasoning, and, importantly, the empirical claims of science. Science is the process by which we assess testable claims about the world. Scientists use accumulated knowledge and evidence to formulate questions or predictions and then ultimately assess these against experiments and observation. We commonly ascribe science to the scientific method, but what scientists actually do and how they go about developing explanations and testing them is actually quite a bit more complicated. Philosophers of science, from Popper to Kuhn to Lakatos and on to Lauden have argued about what demarcates science from other knowledge-gaining exercises and these debates have, in some ways, been mired by the reliance on a scientific method that may or may not exist (see Lee McIntyre’s The Scientific Attitude for a wonderful overview).

 

The best way to think about science is to use McIntyre’s lead, where science is both a process and worldview. It is a process because it has rules in place to guide how we assess claims about the world. Perhaps more importantly, as a worldview that scientists subscribe to, we are willing to test our explanations against fair and unbiased evidence and are willing to alter our belief in light of countervailing evidence. Explanation and belief are constantly assessed and refined, or in some cases completely dropped, because we allow the real world to correct us. I’ve certainly gone through this process and have changed my thinking about the theories that I work on. More than once.

 

 

As the figure above indicates, there are multiple avenues to gain knowledge and empirical science is one of them. I take a broad view of science, so that it would include a lot of what is done in social sciences. Economics, for example, can certainly answer the question, based on more than 80 years of empirical evidence from neoliberal policies, of whether tax cuts or infrastructure investment result in greater economic growth (it’s the latter).

 

Science is one route to knowledge, insight and introspection about ourselves and our place in the universe. However, on matters of the observable world, it is the most important. Science starts with testable questions which necessitate the collection and assessment of evidence (‘facts’), but something can go wrong here. People who don’t follow the rules of science (like objectivity, honesty and transparency) and have a pre-ordained conclusion can simply use only evidence that confirms their belief (confirmation bias) while downplaying damning evidence that shoots their theory full of holes (refutation bias). Once we hit this fork, we go down the path to denialism, pseudoscience and conspiracy theory.

 

We throw around these last three terms a lot when talking about anti-science and anti-fact movements like QAnon, anti-vaccine movements and flat-Earth proponents, but they are not actually synonyms. Though these three terms are clearly interrelated, and many irrational movements invoke all three.

 

Denialism refers to the refusal to believe empirical evidence that casts doubt on one’s belief or ideology. No amount of negative evidence can change the mind of an adherent. Positive evidence is given extremely high weight, often without critically examining the origins of evidence.  But evidence is often not an important ingredient, it is just convenient when it reinforces belief. 

 

Pseudoscience uses the language of science and even purports to uses empirical evidence and experimentation. However, the preferred explanation is assumed to be true, and all that is required is the evidence support it. Opposing explanations are assumed to be wrong, regardless of empirical support. A classic example was the shift from young-Earth creationism (which usually fell firmly in the Denialism camp) to intelligent design (ID). ID attempted to avoid the language of creationism and instead used technical-sounding concepts like ‘irreducible complexity’ to conclude that a creator was a necessary ingredient to explain life. Unfortunately, for ID, proponents’ claims have not been able to withstand rigorous testing, but proponents will still cling to fragile evidence to support their beliefs. 

 

Finally, conspiracy theory has much in common with denialism, and it can be argued that you need to be a denialist in order to truly be a conspiracy theorist. However, in order to support their claims, they go a step further and see a vast collusion of nefarious actors whose primary agenda is to undermine the ‘truth’. Take for example the recent claims of election fraud in the USA. Adherents to this conspiracy theory are willing to believe that dead dictators, Democrat leaders and a vast network of thousands of election volunteers are all part of an organized attempt to change the outcome of an election. Without e-mails. Or social media posts. Or any other evidence. Compare this to the fact that average people could easily figure out the identities of members of the mob that stormed Congress because of extensive social media threads and verbal communication with friends and neighbours. This strange juxtaposition can only lead us to one of two conclusions. Either there was no election rigging conspiracy, or those who stormed the Capital are idiots and the thousands of election stealers are just so much smarter.

 

In all three of these cases, some form of authority or ideology is given more weight than reality. I have a couple of hypotheses why this happens, and especially in the USA, where the nationalistic hubris creates a large gap between the belief about how great one is compared to their reality, and so instead of accepting reality, feelings and scapegoats trump fact.

 

The dismissal of evidence has become commonplace in political life. No one said it better than Newt Gringerich. He basically says that conservative voters believe America is more dangerous today than in the past, and when the newsperson confronts him with the fact that crime has been on a downward trajectory for a long time and that we are statistically safer today than a couple of decades ago, he responds that ‘Liberals’ might have facts that are theoretically true, but his facts are true too. Remember Sean Spicer’s ‘alternative facts’, and this thinking has been around for a while. Have conclusion, need fact.

 

Christmas day 2020, Wisconsin pharmacist Steven Brandenburg purposely destroyed hundreds of dosesof the Moderna COVID19 vaccine. Turns out that Mr. Brandenburg believes that the world is flat and that the Moderna vaccine was designed to harm people and also includes microchips for tracking. While we might chuckle at the absurdity of these believes, there is a deeper, more troubling issue at play. Mr. Brandenburg is a pharmacist. Meaning that he not only has scientific training, but also needs to make evidence-based decisions to help patients. As a supposedly scientifically literate person, he could have easily devised ways of testing his claims. For example, take a plane to Asia, then another to Europe, and then back to the USA. There, the world is not flat. As for microchips in vaccines, a simple compound microscope ought to be enough to observe these.

 

So, if a pharmacist is not willing to put the effort into testing easily refutable claims, why would we expect our bank teller, auto mechanic or Ted Cruz? This goes to the core of the problem. Given the politics of Truth and fact, science and scientists no longer have any authority for many people. In fact, just being a scientist might be enough to get you dismissed as an agenda peddler or a member of some number of absurd conspiracy theories.

 

There is no doubt that vaccines have saved more lives than almost any other medical technology. Yet no other medical treatment or intervention has elicited more skepticism and outright rage than vaccines. And yet there is no rational reason for this, the evidence is very clear. But, there is a denialist and alarmist reason that plays on parents’ anxiety about the health of their children and mistrust of science. 

 

In 1998, Andrew Wakefield published a paper in the prestigious journal, Lancet, in which he reported a link between MMR vaccines and autism. This paper should have never been published. It was based on a sample size of 12 children, and from which there was evidence that Wakefield altered data and records. This paper was retracted by the journal, which is pretty much the worst public humiliation a scientist can experience. It is a recognition that you broke the sacred rules of science and it is a shame you wear for the rest of your career. Despite this public shaming, non-scientific audiences gravitated to his messaging in books and paid lectures.

 

Today, many thousands of people believe that vaccines are bad for children and might cause autism. Of course, these same people would probably have no problem taking antibiotics for an infection, receiving chemotherapy for cancer or eating a hotdog when hungry, despite the fact they probably can’t tell you what exactly is in these. Why vaccines? That is an interesting question. Maybe it’s just serendipity that this was the fraud target of Wakefield, or maybe it’s because of the violation of having a needle pierce your skin, or maybe it is because of the undeniable success of vaccines.

 

This vaccine denialism not only resulted in the re-emergence of nearly eradicated childhood diseases in places like Paris and Los Angeles, but it wasted money and time that could have been put to better use research new therapies. The response required ever increasing numbers of studies to show that there were no links between vaccines and autism. In one of the largest assessments, Anders Hviid and colleagues examined and analyzed the health records of more than 650,000 Danish children for more than 10 years and they simply didnot find any links between MMR vaccines and autism.

 

If you happen to be one that doubts the safety and efficacy of vaccines, ask yourself why, and where you are getting your information from. Then ask yourself if you were, unfortunately, diagnosed with cancer, would you trust your doctor’s request that you start radiation or chemotherapy? If so, despite not really understanding what constitutes ‘chemotherapy’, you’d trust your doctor's knowledge and expertise. Why would you dismiss this same doctor when it came to vaccine advice? You can’t have it both ways, that is irrational.

 

So, where does this leave us? In a quagmire for sure. But it also means that those of us who practice, use or teach empirical science have the knowledge and scientific understanding to engage in dialogues about important issues, whether that is about climate change or vaccines. It doesn’t mean we need to be political (but we should engage with political structures), and we don’t need to be dismissive. We can ask questions to understand peoples’ mistrust or where they are getting their information from. I find that the best way to engage is to be affirmational and dispassionate (which can be hard for me). I recently engaged in a conversation with someone who wasn’t going to get a COVID vaccine and asked a bunch of ‘why’ questions and then started my statements with phrases like “I can understand why you’d be unsure…” and I laid out the medical and public health facts about vaccines.

 

The only way to counter disinformation is with the light of evidence. Not everyone will abandon their conspiracy theories, but many have been fed misinformation, and scientific understanding and fact can really help people make better decisions for themselves.

Guest Post: You teach science, but is your teaching scientific? (Part I)

The first in a series of guest posts about using scientific teaching, active learning, and flipping the classroom by Sarah Seiter, a teaching fellow at the University of Colorado, Boulder. 

As a faculty member teaching can sometimes seem like a chore – your lectures compete with smartphones and laptops. Some students see themselves as education “consumers” and haggle over grades. STEM (science, technology, engineering, and math) faculty have a particularly tough gig – students need substantial background to succeed in these courses, and often arrive in the classroom unprepared. Yet, the current classroom climate doesn’t seem to be working for students either. About half of STEM college majors ultimately switch to a non-scientific field. It would be easy to frame the problem as one of culture – and we do live in a society that doesn’t always value science or education. However, the problem of reforming STEM education might not take social change, but rather could be solved using our own scientific training. In the past few years a movement called “scientific teaching” has emerged, which uses quantitative research skills to make the classroom experience better for instructors as well as students.

So how can you use your research skills to boost your teaching? First, you can use teaching techniques that have been empirically tested and rigorously studied, especially a set of techniques called “active learning”. Second, you can collect data on yourself and your students to gauge your progress and adjust your teaching as needed, a process called “formative assessment”. While this can seem daunting, it helps to remember that as a researcher you’re uniquely equipped to overhaul your teaching, using the skills you already rely on in the lab and the field. Like a lot of paradigm shifts in science, using data to guide your teaching seems pretty obvious after the fact, but it can be revolutionary for you and your students.

What is Active Learning:

There are a lot of definitions of active learning floating around, but in short active learning techniques force students to engage with the material, while it is being taught. More importantly, students practice the material and make mistakes while they are surrounded by a community of peers and instructors who can help. There are a lot of ways to bring active learning strategies to your classroom, such as clicker response systems (handheld devices that allow them to take short quizzes throughout the lecture). Case studies are another tool: students read about scientific problems and then apply the information to real world problems (medical and law schools have been them for years). I’ll get into some more examples of these techniques in post II; there are lots of free and awesome resources that will allow you to try active learning techniques in your class with minimal investment.

Formative Assessment:

The other way data can help you overhaul your class is through formative assessment, a series of small, frequent, low stakes assessment of student learning. A lot of college courses use what’s called summative assessment – one or two major exams that test a semester’s worth of material, with a few labs or a term paper for balance. If your goal is to see if your students learned anything over a semester this is probably sufficient. This is also fine if you’re trying to weed out underperforming students from your major (but seriously, don’t do that). But if you’re interested in coaching students towards mastery of the subject matter, it probably isn’t enough to just tell them how much they learned after half the class is over. If you think about learning goals like we think of fitness goals, this is like asking students to qualify for the Boston marathon, without giving them any times for their training runs.

Formative assessment can be done in many ways: weekly quizzes or taking data with classroom clicker systems. While a lot of formative assessment research focuses on measuring student progress, instructors have lots to gain by measuring their own pedagogical skills. There are a lot of tools out there to measure improvement in teaching skills (K-12 teachers have been getting formatively assessed for years), but even setting simple goals for yourself (“make at least 5 minutes for student questions”) and monitoring your progress can be really helpful. Post III will talk about how to do (relatively) painless formative assessment in your class.

How does this work and who does it work for:

Scientific teaching is revolutionary because it works for everyone, faculty and students alike. However, it has particularly useful benefits for some types of instructors and students.

New Faculty: inexperienced faculty can achieve results as good or better than experienced faculty by using evidence based teaching techniques. In a study at the University of Colorado, physics students taught by a graduate TA using scientific teaching outperformed those taught by an experienced (and well loved) professor using a standard lecture style (you can read the study here). Faculty who are not native English speakers, or who are simply shy can get a lot of leverage using scientific teaching techniques, because doing in-class activities relieves the pressure to deliver perfect lectures.

Test scores between a lecture-taught physics section
and a section taught using active learning techniques.

Seasoned Faculty: For faculty who already have their teaching style established, scientific teaching can spice up lectures that have become rote or help you address concepts that you see students struggle with year after year. Even if you feel like you have your lectures completely dialed in, consider whether you’re using the most cutting edge techniques in your lab, and if you your classroom deserves the same treatment.

Students also stand to gain from scientific teaching, and some groups of students are particularly poised to benefit from it:
Students who don’t plan to go into science: Even in majors classes, most of the students we teach won’t go on to become scientists. But skills like analyzing data, and writing convincing evidence based arguments are useful in almost any field. Active learning trains students to be smart consumers of information, and formative assessment teaches students to monitor their own learning – two skills we could stand to see more of in any career.

Students Who Love Science: Active learning can give star students a leg up on the skills they’ll need to succeed as academics, for all the reasons listed above. Occasionally really bright students will balk at active learning, because having to wrestle with complicated data makes them feel stupid. While it can feel awful to watch your smartest students struggle, it is important to remember that real scientists have to confront confusing data every day. For students who want research careers, learning to persevere through messy and inconclusive results is critical.

Students who struggle with science: Active learning can be a great leveler for students who come from disadvantaged backgrounds. A University of Washington study showed that active learning and student peer tutoring could eliminate achievement gaps for minority students. If you partially got into academia because you wanted to make a difference in educating young people, here is one empirically proven way to do that.

Are there downsides?

Like anything, active learning involves tradeoffs. While the overwhelming evidence suggests that active learning is the best way to train new faculty (the white house even published a report calling for more of it!), there are sometimes roadblocks to scientific teaching.

Content Isn’t King Anymore: Taking time to work with data, or apply scientific research to policy problems takes more time, so instructors can cover fewer examples in class. In active learning, students are developing scientific skills like experimental design or technical writing, but after spending an hour hammering out an experiment to test the evolution of virulence, they often feel like they’ve only learned about “one stupid disease”. However, there is lots of evidence that covering topics in depth is more beneficial than doing a survey of many topics. For example, high schoolers that studied a single subject in depth for more than a month were more likely to declare a science major in college than students who covered more topics.

Demands on Instructor Time: I actually haven’t found that active learning takes more time to prepare –case studies and clickers actually take a up a decent amount of class time, so I spend less time prepping and rehearsing lectures. However, if you already have a slide deck you’ve been using for years, developing clicker questions and class exercises requires an upfront investment of time. Formative assessment can also take more time, although online quiz tools and peer grading can help take some of the pressure off instructors.

If you want to learn more about the theory behind scientific teaching there are a lot of great resources on the subject:

These podcasts are a great place to start:
http://americanradioworks.publicradio.org/features/tomorrows-college/lectures/

http://www.slate.com/articles/podcasts/education/2013/12/schooled_podcast_the_flipped_classroom.html

This book is a classic in the field:
http://www.amazon.com/Scientific-Teaching-Jo-Handelsman/dp/1429201886

By Sarah Seiter

40% believe in evolution, but only 25% do not!

Gallup released a poll, that coincides with Darwin's birthday, which examines American's belief in biological evolution. It is a great poll, breaking down belief patterns across education attainment, age , religiousness, etc.

However, several reports and blogs about this poll disparage Americans for their lack of scientific sophistication, but I think that the results are far more positive then I would have guessed. Only 25% outright deny evolution! I would have thought a clear majority would take this stance as was shown in 2005. A further 36% do not have an opinion, and as scientists and educators, these folks are the reason why we educate and hold events like Darwin Day. Thank you to all those who work so tirelessly promoting science education and literacy, like those at NCSE.