This episode is completely strange to me. It seems like “they are just bad at math” and made a honest gaffe is no satisfying explanation.
There have to be at least three people who made the mistake, Brian Williams, Mara Gay and the person who did the technical work that made the Tweet appear on the monitor.
A gaffe is a term that’s commonly used to refer to mistakes by a single person.
When I watch that episode it seems to me like the hosts are careful to not say that the numbers in the tweet are true. It looks like they thought it was okay to bring up the wrong tweet and somehow they are not responsible for the factual content of the tweet but the Twitter use who made the tweet is responsible.
It seems like they made a mistake about thinking such a numeric overstatement is okay to make.
This is a large part of why COVID-19 has hit the United States so hard.
Is the United States significantly less numerate than other countries? I agree quantitative reasoning is good and we want more of it, but I’m not sure it’s the major contributor to the thing you’re trying to explain here.
A lot of what PISA results reflect is countries desire to score a certain way. The Asian countries want to score highly for prestige reasons and run the tests in schools with above average students. On the other hand countries like the US or Germany who used low scores as a justification for domestic reform.
Here’s a table sorted for math. The US is 37th out of 78 on the list, below Spain and above Israel; the tiers are “rich Asian city-state”, “small country in Asia or Europe”, and then “large country in Europe or less impressive small country,” and the US is low-ranked in that third tier. (The difference between Japan and the US is smaller than the difference between the US and Mexico.)
Being bad at quantitative reasoning is only half the problem. The rest is lack of trust and cooperation. If people weren’t trying to figure things out themselves, their innumeracy wouldn’t matter.
Great post. The political process selects for ability to construct narratives, tell stories, blame others for failures and take the credit for successes, etc. So that’s what we get. Sometimes by chance we get more, very often not. The pandemic has laid bare the incompetence of many world leaders on both sides of the political divide.
It is also a great illustration of the power of politics in filtering people’s reality.
Specifically on innumeracy we see again and again the rejection of simple measures that would reduce infectivity because they are not perfect or not high status. I am referring to some of the measures taken by Taiwan—with no lockdown and 1/1500 th the death rate per capita of the USA—such as universal use of face masks and screening people entering shops for symptoms and fever. These measures filter down the infectivity of the population as a whole such that r0(eff)<1 or close to that level, at relatively modest cost. In this podcast we hear from a doctor that masks and screening are only useful as ways of showing that we care. Really*. https://www.abc.net.au/radio/programs/coronacast/have-we-been-too-easy-on-rule-breakers/12524256
Drastic measures like lockdowns seem to be perversely popular because they seem to signal ‘strong’ leadership. Even though they are not very effective, part because you cannot lock down the whole society, and are enormously expensive. There is great faith in contact tracing, which simulations show only helps if it is very rapid and if test results come back fast and if quarantine is very strictly enforced. In many countries none of the above apply.
*Another filtering problem: The medical training system in large part filters for the ability to memorize vast amounts of material and for physical and mental stamina. And not much else. Sometimes by chance people get through this system who are statistically, mathematically and numerically literate but many get through who are not. Even researchers—as a perusal of the medical research literature quickly attests. Did you know that p>0.05 shows that there is no effect? People who took Vioxx and had a heart attack, more than 50,000 excess heart attacks in all, may disagree.
I guess a deficit in quantitative reasoning is just one of the contributing factors.
Another contributing part, I keep thinking about a lot, is the role of social media during the pandemic. Social media is making money by engaging people. The longer people are on your platform, the more data you can harvest and the more advertisements you can show them, resulting in more revenues. And the more data you have, the better you can target the ads, and so on. The best way to drive up engagement is to promote controversial posts (the more extreme the better, you like it and share it or you don’t like it and talk about it). This leads to filter bubbles. By knowing the main orientation of those filter bubbles it is easy to drive up engagement by showing each filter bubble some posts that are aligned to their views (maybe even increasing to more extreme topics and standpoints).
Of course this is not beneficial for the society as a whole and it drives division and is not improving a culture of open discussion, but it is currently a great and more or less unregulated money making machine.
Pair that with a very capitalistic society without a lot of social security nets and a situation that brings people to the edge (i.e., pandemic) and the outlined mechanics from above is running even faster/better (isolated people, increase of fear of the unknown, mental health issues, etc.).
(And hey, you can even use this technology (unofficially) to harm other parties and cause a lot of damage with a fraction of the cost of traditional operations.)
And in the end, the outlined aspect comes down to misaligned incentives.
(Note: Maybe I was reading recently too much about misinformation using natural language processing.)
This episode is completely strange to me. It seems like “they are just bad at math” and made a honest gaffe is no satisfying explanation.
There have to be at least three people who made the mistake, Brian Williams, Mara Gay and the person who did the technical work that made the Tweet appear on the monitor.
A gaffe is a term that’s commonly used to refer to mistakes by a single person.
When I watch that episode it seems to me like the hosts are careful to not say that the numbers in the tweet are true. It looks like they thought it was okay to bring up the wrong tweet and somehow they are not responsible for the factual content of the tweet but the Twitter use who made the tweet is responsible.
It seems like they made a mistake about thinking such a numeric overstatement is okay to make.
Is the United States significantly less numerate than other countries? I agree quantitative reasoning is good and we want more of it, but I’m not sure it’s the major contributor to the thing you’re trying to explain here.
The US does pretty badly in the world tables for school performance in math especially considering its GDp/capita. https://www.oecd.org/pisa/PISA-results_ENGLISH.png
A lot of what PISA results reflect is countries desire to score a certain way. The Asian countries want to score highly for prestige reasons and run the tests in schools with above average students. On the other hand countries like the US or Germany who used low scores as a justification for domestic reform.
Here’s a table sorted for math. The US is 37th out of 78 on the list, below Spain and above Israel; the tiers are “rich Asian city-state”, “small country in Asia or Europe”, and then “large country in Europe or less impressive small country,” and the US is low-ranked in that third tier. (The difference between Japan and the US is smaller than the difference between the US and Mexico.)
Being bad at quantitative reasoning is only half the problem. The rest is lack of trust and cooperation. If people weren’t trying to figure things out themselves, their innumeracy wouldn’t matter.
Great post. The political process selects for ability to construct narratives, tell stories, blame others for failures and take the credit for successes, etc. So that’s what we get. Sometimes by chance we get more, very often not. The pandemic has laid bare the incompetence of many world leaders on both sides of the political divide.
It is also a great illustration of the power of politics in filtering people’s reality.
Specifically on innumeracy we see again and again the rejection of simple measures that would reduce infectivity because they are not perfect or not high status. I am referring to some of the measures taken by Taiwan—with no lockdown and 1/1500 th the death rate per capita of the USA—such as universal use of face masks and screening people entering shops for symptoms and fever. These measures filter down the infectivity of the population as a whole such that r0(eff)<1 or close to that level, at relatively modest cost. In this podcast we hear from a doctor that masks and screening are only useful as ways of showing that we care. Really*. https://www.abc.net.au/radio/programs/coronacast/have-we-been-too-easy-on-rule-breakers/12524256
Drastic measures like lockdowns seem to be perversely popular because they seem to signal ‘strong’ leadership. Even though they are not very effective, part because you cannot lock down the whole society, and are enormously expensive. There is great faith in contact tracing, which simulations show only helps if it is very rapid and if test results come back fast and if quarantine is very strictly enforced. In many countries none of the above apply.
*Another filtering problem: The medical training system in large part filters for the ability to memorize vast amounts of material and for physical and mental stamina. And not much else. Sometimes by chance people get through this system who are statistically, mathematically and numerically literate but many get through who are not. Even researchers—as a perusal of the medical research literature quickly attests. Did you know that p>0.05 shows that there is no effect? People who took Vioxx and had a heart attack, more than 50,000 excess heart attacks in all, may disagree.
I guess a deficit in quantitative reasoning is just one of the contributing factors.
Another contributing part, I keep thinking about a lot, is the role of social media during the pandemic. Social media is making money by engaging people. The longer people are on your platform, the more data you can harvest and the more advertisements you can show them, resulting in more revenues. And the more data you have, the better you can target the ads, and so on. The best way to drive up engagement is to promote controversial posts (the more extreme the better, you like it and share it or you don’t like it and talk about it). This leads to filter bubbles. By knowing the main orientation of those filter bubbles it is easy to drive up engagement by showing each filter bubble some posts that are aligned to their views (maybe even increasing to more extreme topics and standpoints).
Of course this is not beneficial for the society as a whole and it drives division and is not improving a culture of open discussion, but it is currently a great and more or less unregulated money making machine.
Pair that with a very capitalistic society without a lot of social security nets and a situation that brings people to the edge (i.e., pandemic) and the outlined mechanics from above is running even faster/better (isolated people, increase of fear of the unknown, mental health issues, etc.).
(And hey, you can even use this technology (unofficially) to harm other parties and cause a lot of damage with a fraction of the cost of traditional operations.)
And in the end, the outlined aspect comes down to misaligned incentives.
(Note: Maybe I was reading recently too much about misinformation using natural language processing.)