Ars Technica are holding a competition for people to make a science video up to 3 minutes long "to explain a scientific concept in terms that a high school science class would not only understand, but actually be interested in watching". Prizes in three categories: biology, physics, and mathematics. Deadline is December 25. More details here.
Anyone want to have a go at Bayes' theorem? Cognitive bias? Defeating death? Invisible purple dragons?
To the best of my recall, the shortest Khan Academy video is twelve minutes. Ars Technica ought to multiply their time span by four or five if they want to get good entries.
The best part of the "Manufacturing Consent" movie is when Chomsky says he makes a crappy television guest because the topics he is interested in cannot be compressed into topical television show sound bite length.
I suck at making videos and I hate my spoken voice, but here's an approximate transcript of what I would tell the kids.
Imagine that some terrible illness kills most of the men affected by it, but spares most of the women. Also assume that most affected women take a certain drug, while most men don't. And on top of that, assume that the drug is completely useless: it doesn't affect your chances of survival either way. Men die from the illness more because of some tiny physiological difference between men and women. And women take the drug more just because it's marketed toward women more.
In this situation, if you didn't get the lucky guess of counting men and women separately and instead counted them together, you'd arrive at the conclusion that the drug is pretty damn effective because taking it is very correlated with survival! So, just by splitting people into groups in clever ways, you may make apparent relationships of cause and effect appear and vanish. This is known in statistics as Simpson's paradox. It is often observed in practice, like in the famous Berkeley sex bias case of 1973 when the university as a whole was found to be biased toward admitting men, while every individual department was found to be biased toward admitting women.
Sometimes you may get around the problem by making experimental tests. If you change the cause and it affects the outcome, you can be sure you're looking at a real relationship, not a statistical illusion. But it's hard to imagine an ethical way to test the hypothesis that smoking kills. In such situations, if you can only observe real-world trends, your best bet is to use many "control variables", like counting men and women separately in my original example.
It is often observed in practice, like in the famous Berkeley sex bias case of 1973 when the university as a whole was found to be biased toward admitting men, while every individual department was found to be biased toward admitting women.
This seems impossible, and checking the data (posted on wikipedia) that isn't what happened.
[edit] Hm, I appear to not have been thinking clearly. See comment below.
This seems impossible, and checking the data (posted on wikipedia) that isn't what happened.
That is not exactly what happened, as 2 departments exhibited a small bias towards men, but it is not impossible, and the reason is that more women applied to the more competitive departments, and so their total acceptance rate represented the departments with low overall acceptance rate more than the men's total acceptance rate.
I'm sure it's not impossible. Consider the extreme case:
| Dept | Male Applications | Males Accepted | Female Applications | Females Accepted |
|---|---|---|---|---|
| A | 100 | 80% | 10 | 100% |
| B | 10 | 10% | 100 | 20% |
Female accepted in total: 30/110 ~ 27%. Males in total 81/110 ~ 74%.
Cognitive bias has a much higher chance of being selected than those other three. Bayes' theorem, love it though I do, just isn't going to be something that grabs people's attention. Defeating death isn't science and neither is invisible purple dragons.
Agreed. The whole notion of "You can't trust your brain, and here's why and how" is probably the most likely to catch people's interest.
What category would that fall into? I guess "biology" would be the closest, but do we know if topics in cognitive science would be accepted?
Quite important:
The contest is open only to legal residents of the 50 United States, the District of Columbia and Canada (except the Canadian province of Québec) who are at least 18 years old as of the date of entry.
Though in a pinch you could have a North American LWer submit your entry for you and give you credit and eventual prizes, since the rules seem to allow third-party collaboration.
Defeating death
Please elaborate on what you think the author intended by those words, or whether you are responding to the literal interpretation.
The argument/idea that we should concentrate resources on preventing old age (and therefore age-associated diseases that kill) thereby dramatically increasing the human life span with an eye toward increasing it indefinitely is not a scientific concept.
Agreed, that's more of a moral/political argument. But it is only one aspect of the topic "defeating death". For example: "aging can be cured" and "cryonics can delay death" are legitimate scientific concepts.
Maybe I could make one but I'd need some memetic assistance. What are high school science classes interested in watching?
If I recall correctly, mine seemed to like watching Walter Lewin's MIT video lectures, Bill Nye the Science Guy episodes, a bunch of recent Blockbusters on DVD, and Jeff Dunham's act.
More seriously, one thing I remember that that got student's attention in high school pretty quickly was cool and/or surprising experimental results shown to them. My chemistry teacher got everybody excited by performing a precipitation reaction for us, because seeing liquids combine and result in some dust forming and falling down to the bottom of the beaker with our own eyes was awesome. When watching Lewin's videos, nothing got more praise than his dramatic demonstration of the conservation of mechanical energy (the drama was important; my physics professor in university did the same thing, but didn't get nearly as much of a reaction because he didn't play it up like it could be his last lecture, despite doing the demonstration live). And people in my psychology class were very fond of both the selective attention test / awareness test videos and a practical demonstration of the sunk cost fallacy (he had 4 of us bid on a dollar bill with the highest 2 results paying but only the highest result getting the dollar; needless to say, both top bidders ended up losing money).
That's mostly for high school boys (I expect that at High School level, science classes aren't boys-only yet).
A how-to-swear video would be entertaining, but I suspect it would not meet their criteria.
I'd be fascinated by one that did, though. At least, it seems plausible that there's interesting cognitive structure underlying the common linguistic and emotional aspects of swearing (the culture-bound specifics, less so).
I suck at making videos and I hate my spoken voice, but here's an approximate transcript of what I would tell the kids.
Imagine that some terrible illness kills most of the men affected by it, but spares most of the women. Also assume that most affected women take a certain drug, while most men don't. And on top of that, assume that the drug is completely useless: it doesn't affect your chances of survival either way. Men die from the illness more because of some tiny physiological difference between men and women. And women take the drug more just because it's marketed toward women more.
In this situation, if you didn't get the lucky guess of counting men and women separately and instead counted them together, you'd arrive at the conclusion that the drug is pretty damn effective because taking it is very correlated with survival! So, just by splitting people into groups in clever ways, you may make apparent relationships of cause and effect appear and vanish. This is known in statistics as Simpson's paradox. It is often observed in practice, like in the famous Berkeley sex bias case of 1973 when the university as a whole was found to be biased toward admitting men, while every individual department was found to be biased toward admitting women.
Sometimes you may get around the problem by making experimental tests. If you change the cause and it affects the outcome, you can be sure you're looking at a real relationship, not a statistical illusion. But it's hard to imagine an ethical way to test the hypothesis that smoking kills. In such situations, if you can only observe real-world trends, your best bet is to use many "control variables", like counting men and women separately in my original example.
This seems impossible, and checking the data (posted on wikipedia) that isn't what happened.
[edit] Hm, I appear to not have been thinking clearly. See comment below.