learning – Australian Data Science Education Institute

Vaccine hesitancy could literally kill, yet it’s a logical consequence of the way we teach science.

We tend to think Science is about facts and right answers. This is absolutely the way we teach it, but it’s the opposite of what Science really is. We learn the periodic table, the arrangement of subatomic particles around a nucleus, the equations for force and motion, and how to name the components of a cell. We teach with experiments where known inputs are treated with a known process, producing a known outcome. Kids who don’t get the “right” answer either fake their results or copy from their neighbours. This is not an education in Science, it’s an education in confirmation bias – in seeing what we expect to see.

Science is actually a way of exploring and understanding the world, and of solving problems. By its very nature science deals with uncertainty, and constantly proves itself wrong as new information becomes available.

Scientific theories are based on the information we have right now. Sometimes we can’t see, measure, or understand enough to explain a phenomenon fully, but we have a model we think is right, and it’s right enough to help us understand some parts of the way the world behaves.

We can see this in the way our understanding of covid19 has evolved. At first we thought it was transmitted by droplets, so that unless you were in the direct path of someone’s sneeze or cough, the main risk was touching an infected surface. As we learned more, our understanding developed. We now know that it is very easily transmitted by aerosols – in other words, virus particles can hang in the air in such quantities that we easily breathe them in and become sick.
This explains why transmission rarely happens outdoors, and why ventilation is key when we’re indoors. It also explains why hotel quarantine is so problematic – because even if there is no air transfer between rooms, an infected person walking through a corridor can leave that corridor so contaminated that it’s infectious for some time afterwards. It also explains why masks (when properly worn) are so effective at preventing transmission.

We’ve also seen our understanding of vaccines and their side effects evolve. And the fact that the story keeps changing – from “Astrazeneca is safe for everyone” to “it’s safe for everyone over 50” and now “it’s safe for everyone over 60” – makes people nervous. But it’s this rapidly changing information that should give us comfort and confidence. This is Science doing its job – adapting our understanding according to new information.

I once interviewed Cameron Neil, who at the time was head of the Fair Trade Association of Australia and New Zealand. We were talking about the fact that it’s hard to buy ethically, because the information we have keeps changing. Neil’s response is an ethical approach to consumption, but it also encapsulates an intelligent approach to Science: “With the information available to me today I make the best choice I can, knowing full well that I may get information tomorrow that means the choice I made was the wrong one, and I’ll have to do better next time.”

When it comes to vaccines, of course, we crave certainty. No-one wants to take something that might harm them. We want to know with absolute clarity what the best thing is that we can do for our health. The fear and uncertainty in the community around the Astrazeneca vaccine is palpable. Yet according to Hassan Vally, an epidemiologist at La Trobe University, the risk of dying from a blood clot due to the vaccine in Australia is 0.5 per million, while the risk of dying in a car accident in Australia in any given year is 28 per million. Compare that with the risk associated with taking aspirin or other non steroidal anti-inflammatories (NSAIDS), which is 24.8 deaths per million people, or a staggering 153 per million users of those drugs. This is where a different understanding of Science could help us.

If we truly understood how Science worked, the rapidly changing information would give us confidence that our understanding was getting better and better. If we taught Science as an exploration of the unknown, and a constantly developing set of theories, rather than a fixed set of hard facts, we would be far better prepared to understand the constantly evolving picture of covid19 and its vaccines.

It’s really hard to teach kids critical thinking skills when your toolkit is questions that all have right answers, curricula full of facts and straightforward procedures, and textbooks that leave kids floating on an uneasy sea of factoids, memorisation, and perfectly neat examples tied up with a bow.

Imagine if we taught Science by exploring the world. By trying to solve problems that have no textbook answers, where students have to rigorously test and evaluate their own work (and the work of others) in order to be confident of their results, because they can’t just look up the answer, and have the teacher mark it right or wrong.

If we grew up with this basis, knowing Science as an evolving, developing discipline, rather than a bunch of facts pinned to the unchanging pages of a textbook, we would know that our changing understanding of covid19 and its vaccines is not a threat. It’s what’s keeping us safe.

Read more about the way we teach science, and about teaching our kids to be critical thinkers, in Raising Heretics: Teaching Kids to Change the World.

This is an excerpt from Raising Heretics: Teaching Kids to Change the World, which is due out on August 1st.

I founded the Australian Data Science Education Institute in 2018 because I wanted to show kids that they are capable of working with technology, that it is relevant to them, and that they don’t have to look like Sheldon from the Big Bang Theory in order to learn to program.

It’s well known that the technology industry has a diversity problem when it comes to women, but lack of diversity goes way beyond gender. By trying to increase the number of women and girls in STEM, we are only tackling the easy part – though it’s actually not that easy, judging by the sheer volume of women in STEM programmes and the persistently stubborn failure of the numbers to actually shift.

The problem is that we consistently attract the kinds of people to tech that are already there. We are missing big chunks of the population – boys included. Boys who don’t see themselves as nerdy, or who don’t see the point of tech. Girls who don’t see it as relevant to them. Non binary and gender queer kids who don’t see themselves as represented or welcome in any of the tech programmes available to them.

If we had true diversity in technology and Data Science, we’d have a range of ethnic and cultural backgrounds, as well as people with a wide range of physical abilities. We’d have people on our design teams that are mobility compromised, vision impaired, with allergies, with varied gender identities and sexualities, with every possible skin tone and body shape. We’d have people who act differently, dress differently, think differently, and have different needs. I have headphones that don’t work well with long hair, for goodness’ sake! Guess who was on that design team?

This lack of diversity is bad for the technology industry, but it’s even worse for the rest of us, because technology is changing the shape of our world at an alarming rate, and we currently have very little say in our own future. Companies like Uber and Doordash are radically changing our working conditions and eliminating hard won entitlements and protections, while Facebook and Youtube spread misinformation and encourage radicalisation, all in the name of keeping people on their platforms and maximising their profits. Our world is being directly shaped by technology companies that are working in ways we don’t understand and have no control over.

Meanwhile we see human resources companies using AI to filter job applicants, claiming that their system eliminates “human bias”, without admitting the possibility that it introduces new forms of machine bias. We see “predictive policing” algorithms being used to predict crime and target particular communities in disturbing ways. We see a rush towards machine learning and artificial intelligence systems for their own sake, rather than for problems they can legitimately solve, and we have a wholly unwarranted confidence in the accuracy, reliability, and objectivity of their output.

It turns out that diversity in the technology industry is only a small part of the reason why teaching all kids Data Science and STEM skills matters. The big part is that we need a technology and data literate population who are trained to think critically and creatively, and, in particular, trained to believe that they can solve problems. That’s the world we need to build. And the foundation stone of world building has to be education.

We have a choice. We can train kids to be obedient process followers who don’t rock the boat, or we can train them to be challenging, critical and creative thinkers who ask difficult questions and come up with innovative solutions to our worst problems.

Above all, we need people who are prepared to be heretical.
Who ask “why?”
Who ask “how can we be sure?”
Who ask “what have we missed?”
Who ask “how can we do better?”
Who ask “who are we hurting?”
Who ask “how can we fix this for everyone?”
Who ask “how will we know how well it works?”

These questions are often heretical. By asking them, I’ve sometimes made my bosses very unhappy. They make people uncomfortable. But they are crucial to building an ethical, sustainable, positive future for all of us.

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Pre-order Raising Heretics now:

https://events.humanitix.com/raising-heretics-pre-orders-and-book-launch

Tag: learning

Vaccine hesitancy is a logical consequence of the way we teach science.

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