h a l f b a k e r yThis is what happens when one confuses "random" with "profound."
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"Loser" App
For smartphones; identifies your choice of losers | |
This app would start by using the smartphone's camera to take an image of someone you encounter at random (you have to point the camera appropriately, of course).
Then it would scan the Internet to identify that person.
Then it would seek out all the available profile information that that person
has self-posted, about self. If the app finds any of certain key items, then the the word "loser" is displayed on the screen, along with the image of that person.
The fun part is how you will have previously, when the app is installed in the smartphone, designated that certain profile info items will identify someone as being a "loser".
For example, you might designate all Creationists as losers. So, if the app finds that the person's profile indicates that he or she is a Creationist, then that suffices for the app to display "loser" upon that person's image.
More, the app can look for multiple matching things (smokes? pro-choice? Mafia-connected? etc), each of which by itself--for YOU--would be a "loser" flag, and then apply stress to the displayed word, such as:
Loser
Loser!
LOSER!
LOSER! (yellow letters)
LOSER! (orange letters)
LOSER! (red letters)
There could also be an equivalent "winner" app. Sold separately, of course!
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Annotation:
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This seems to be contingent on the assumption that
a person can be identified automatically from their
photo. Is this, in fact, the case? |
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Cheaper to do this with a stack of post-it notes. |
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[MaxwellBuchanan], there is "cloud" software that is working on that problem. For now, this Idea is Half-Baked. |
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I should mention that one possible way of identifying a photograph involves comparing the image to the image that accompanies a self-posted public profile, as on Facebook or equivalent. If trends continue, in the future just about everyone will have done that... |
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// comparing the image to the image that
accompanies a self-posted public profile// |
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I have not kept abreast (which suggests another
idea, but we shall let it pass) of facial recognition
software, but I believe we are still a very long way
from being able to correctly match two
photographs of the same face under different
circumstances, even when the number of possible
faces is quite limited. Given a hundred million
facebook images, I'd imagine that your chances of
picking the right one would be somewhere
between one in a hundred million and one in a
million. |
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In fact, I am pretty sure that if you showed me 100
million faces, I'd find a fair few that looked just
like Walter Matthau, or like my granduncle
Thaddeus (with or without his monocles). |
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Still, there's a lot of future out there waiting to
happen. |
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The app Recognizr by TAT did the part that isn't identifying
losers several years ago. |
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A local newspaper had (when it still existed) a similar idea: each friday after a food, livestock and groceries market which is scheduled every 2nd thursday they published a picture of a market visitor and declared him or her a winner. To claim their price winners had to come to the town again (loser's count: 1), locate the editor's office (2), identify themselves a the depicted persons (3) and claim their price of (if I remember right) about $20 (4). The newspaper never published if the price was ever claimed. |
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