Science, Technology & Health: December 2007 Archives
For whatever it's worth, here's a neat chart displaying jobs by IQ distribution.
(HT: Tom Smith and Glenn Reynolds.)
I loved my Roomba Discovery while it lasted, but unfortunately that was only about a month. Two days ago the motor that drives the counter-rotating brushes stopped working (though it still makes noise) and I've been unable to fix it.
I knew it was too good to be true :(
I just got an email from the creator of a website called Out of Pocket that is attempting to collect and disseminate ("expose") information about the true costs of various medical treatments and procedures.
As you know from my recent posts on health care, I'm a big proponent of market-based solutions and the cornerstone of the free market is freely available information. Unfortunately, it's often very difficult to compare prices between health care providers because they know a lot more than we do and most of their patients pay indirectly through insurance rather than directly out-of-pocket.
I'm very excited to see this site, and I'll be checking it before I go to the doctor -- even if just to know what my health insurance is actually doing for me.
I've been thinking more about the health care/insurance article I linked to yesterday and I want to add one qualification to my general agreement with the authors. They write in their conclusion:
Finally, we must repeal HIPAA and all other government regulations involving health insurance or medical care. It is immoral for doctors to be subject to criminal penalties for documentation errors that violate no rights and have nothing to do with the quality of patient care. ...
As I considered the article, the phrase I bolded above stood out to me. I won't defend HIPAA, but I don't agree that "all other government regulations involving health insurance or medical care" should be eliminated. In particular, I think a very important role of government is to mandate transparency from experts in the commercial sector. There's no way that I as a health care consumer can ever know as much as the doctors who treat me, but the final decision for any treatment I undergo still lies with me and not with them. To that end, the government should require the disclosure of treatment information from medical professionals.
I'm thinking of a medical equivalent of the nutrition information that's mandated on food packaging. I don't want the government to tell me how many Fritos I can eat, but if it weren't for government-enforced transparency I wouldn't know what goes into Fritos and I wouldn't be able to make an informed decision about how many to eat. The government already requires drug manufacturers to disclose the potential side-effects of their products (do we need them in every commercial though?) and I think there should be similar transparency in other medical arenas.
It is a legitimate role for government to prevent experts from harming or defrauding consumers with their information advantage.
Paul Hsieh (of GeekPress) and Lin Zinser explain the American health care system, including how we got where we are and how we should move forward. You'll learn something.
If you're confused, like me, by meteorology terminology, here's another definition you may have wondered about: what are heating/cooling degree days?.
What are heating degree days and cooling degree days?Heating degree days are indicators of household energy consumption for space heating. It was found that for an average outdoor temperature of 65 degrees Fahrenheit, most buildings require heat to maintain a 70 degree temperature inside. Similarly, for an average outdoor temperature of 65 degrees or more, most buildings require air-conditioning to maintain a 70 degree temperature inside.
How heating and cooling degree days are computed
Take the high and low temperature for the day, and average them. If this number is greater than 65 F, then we have (Average temperature - 65) cooling degree days. If the average temperature is less than 65 degrees, then we have (65 - Average temperature) heating degree days. Running totals are kept for these units over a time period of a year so fuel distributors and power companies can assess average demands.
So it appears that the number of heating/cooling degree days accumulated on a single calendar day can be used to estimate how much energy will be required for heating/cooling a building on that day. By adding these up over time, you can figure out how much energy has been or will be used in a season. I think.
So the "Winter Weather Watch" has been canceled, the "Freezing Rain Watch" is in effect, and the "Ice Storm Warning" is off. Is it just me, or is meteorology a very imprecise science? Not only can't they predict the weather tomorrow, but their technical terminology is vague, ambiguous, and follows no logic I can discern.
Maybe it's just so complex that us untrained weather laymen should just mind our own business!
The holographic principle is fascinating: basically, the maximum entropy in a region of space is proportional to the area of the boundary of the region rather than its volume.
Suppose I took you to an acre of prairie and told you about a family of field mice who lived there. You eye would wander over the contours of the ground and vegetation and notice a myriad of details: potential shelter in holes or under bushes; insects to eat; puddles of water to drink; a vast expanse of territory that the mice could never exhaust; and generally everything the mice would require to live happy, fulfilled, and productive lives. (Such as they are.)
But suppose instead that I led you to the same acre of prairie and told you that it was home to some grizzly bears. Your eye would consider the land in a completely different manner: no shelter; no food; no water; and far too small for giant bears to enjoy.
As is probably obvious to you, the difference is scale. Mice can life in a hole in the dirt and drink from a puddle, but bears require a cave and a river full of trout. When I show you a field and tell you about mice your attention is turns to the mouse-sized details of the terrain; when I tell you about bears you see bear-sized features. Your brain automatically chunks the whole of what it observes into components at the scale of whatever it is considering.
When you write a word, the chunks are letters -- though after we learn how to spell we rarely consciously think of words as composites of letters. When you write sentences, the chunks are words (and many people spend a great deal of time choosing the right ones). When you write paragraphs, the chunks are sentences. When you write essays, the chunks are paragraphs, connected together to serve a common theme. Essays or chapters may be put into books, books into libraries, libraries into bureaucracies, and bureaucracies into governments. And so forth. At each level, from author to librarian to bureaucrat to elected official, each person considers the same terrain at a different scale and acts appropriately.
And no one really has any idea how we do it. We know that our handling of scale is dependent on chunking, because humans can only hold five to nine items in our short-term memory. However, by combining and dividing information into chunks we can fit more into those slots. For example, when you hear a sentence your comprehension isn't limited by the number of letters in each word, but rather by the number of words in the sentence -- the letters are chunked together. When you hear a lecture you're unlikely to remember many specific sentences, but you'll be able to remember a handful of points made by the speaker. At the end of the semester you won't remember many of the lectures, but you will have incorporated the main ideas of the class into your long-term memory.
All made possible by chunking, and all completely inscrutable to artificial intelligence researchers. We have no idea how the brain makes such smart decisions about how to divide the world into chunks and then recombines those chunks into knowledge.
One of the side effects of chunking is the ability to generalize. Sometimes generalizations get a bad rap (e.g., racial discrimination), but the ability to generalize is an essential component of our intelligence. Our brains can take an observation, break it into chunks, and then later recombine some of those chunks with chunks taken from another observation. Sometimes the recombinations are faulty (e.g., superstitions) but most of the time they're incredibly useful (e.g., getting hit by a red car is just as bad as getting hit by a blue truck).
Developing artificial intelligence that can generalize from prior experience is the holy grail of the field, but it won't be accomplished without chunking, and we've got no idea how to make a computer do that well because no one knows how we do it.
Via my brother is this article about a vast salt flat in Bolivia being used to calibrate satellites.
A precise topographical map has been made of one of the flattest places on Earth: the salar de Uyuni, a vast plain of white cemented salt in the mountains of Bolivia. The ground survey, aided by global positioning systems (GPS), shows variations in elevation of less than a metre across an area almost half the size of Wales.Intriguingly, the work reveals bumps in the salt that lie above lumps of dense rock buried several kilometres below, just as water will bulge over a bump on the ocean floor. Knowing exactly where these bumps lie will help researchers to use the flat as a giant calibration device for satellite-based radar and laser altimeters.
The place is huge. If the comparison to Wales doesn't mean anything to you, consider that the salar de Uyuni is 4,085 square miles:
- Washington, DC: ~70 square miles
- New York City: ~470 square miles
- Delaware: ~2,490 square miles
- Island of Hawai'i: ~4,028 square miles
