{"id":2622,"date":"2017-10-13T00:38:42","date_gmt":"2017-10-13T00:38:42","guid":{"rendered":"https:\/\/wisehost.ca\/fr\/?p=2622"},"modified":"2017-10-11T05:46:39","modified_gmt":"2017-10-11T05:46:39","slug":"artificial-intelligence-improving-magic-tricks","status":"publish","type":"post","link":"https:\/\/wisehost.ca\/fr\/artificial-intelligence-improving-magic-tricks\/","title":{"rendered":"How Artificial Intelligence Is Improving Magic Tricks"},"content":{"rendered":"
By\u00a0Joshua Rapp Learn<\/div>\n
SMITHSONIAN.COM\u00a0<\/span><\/div>\n
<\/div>\n
Computer scientists have designed a trick that uses an algorithm to search the internet for the words most associated with images<\/strong><\/div>\n

Forget lightning speed calculations, technological superiority and machine-like precision. Thanks to the efforts of some researchers, artificial intelligence can now create magic.<\/p>\n

\u201cWe\u2019ve done a number of different tricks involving artificial intelligence,\u201d says Peter McOwan, a computer science professor at Queen Mary University of London.<\/p>\n

McOwan and his coauthor, Howard Williams, recently published a\u00a0study\u00a0in\u00a0PLOS ONE\u00a0<\/em>on using search algorithms to scour the internet to find the hidden mental associations magicians can use to astound their spectators.<\/p>\n

\u201cA piece of software is like a magic trick in that it has something that seems amazing,\u201d McOwan says.<\/p>\n

McOwan says he first got into magic when his father bought him a trick he picked up at a shop while on a business trip. He got hooked, but the hobby kind of dropped away later when he went to university. As he got into computer science, he realized that some of the same algorithms you can use to develop mathematically based card tricks were used to develop software and applications.<\/p>\n

\u201cI combined my passion for magic tricks with my passion for computer science,\u201d he says, adding that what started off as a childhood hobby ended up as a whole field of research in artificial intelligence.<\/p>\n

\u201cMagic as a hobby is a fantastic thing to get into. It gives you self-confidence, it gives you the ability to learn communication skills\u2014it\u2019s a really good hobby to have.\u201d<\/p>\n

While the term \u201cartificial intelligence\u201d is often misconstrued to mean a whole assortment of robot apocalypse scenarios, much of what\u2019s considered AI today is really born from algorithms. But using numbers to create tricks isn\u2019t anything new\u2014in fact many magic tricks involve math.<\/p>\n

Jason Davison, a mathematical magician based in London, uses a minor sleight of hand and a few calculations to pull tricks like getting a given card you\u2019ve chosen at any point in a deck you tell him just by\u00a0shuffling the cards.<\/p>\n

Another trick involves using a much more complex understanding of patterns and a little deck fixing to ensure that any way the spectator shuffles a deck, the cards will appear to have an\u00a0uncanny order\u00a0in which every set of four cards pulled from the top represent each of the four suits.<\/p>\n

\u201cThere are many others with algebra and formulaic self-working tricks,\u201d Davison says.<\/p>\n

He has even designed a simple computer program that appears to be able to guess the correct color of a given card in a deck fixed in the same way as the latter trick. He gets the spectator to shuffle the cards as above, then divides the deck into two piles. He asks the spectator to guess the color of the cards in one pile one by one before revealing them and enters the answers into the program.<\/p>\n

The robot then predicts the other pile, and (un)naturally gets it all right. But what might seem like robot mind-reading is really just a programmatic sleight of hand. Davison knows which colors the cards will be in that pile because they will be the opposite of the spectator\u2019s pile based on the way the deck is shuffled. So when the spectator gets one wrong, he inserts an extra space before the answer he types. This cues the program that the answer is wrong.<\/p>\n

So rather than controlling something we can\u2019t comprehend, the program is merely a slave to Davison\u2019s own knowledge of the pack. \u201cThe computer \u2018guesses\u2019 the coloring of the other pile using this information I have fed to it,\u201d he said in an email.<\/p>\n

McOwan has taken algorithms to the next level, though.<\/p>\n

His trick works like this. A custom deck will have cards with words, and another pile of cards will have images. Spectators will be asked to instantly choose word cards that associate most closely with an image. (The researchers invite you to\u00a0download\u00a0the cards and instructions.)<\/p>\n

The real magic in this trick comes in determining how far off the wrong meanings can be without seeming fixed. You might have a picture of a hamburger, for example. But if you have five words\u2014hungry, fish, cat, boat and tree\u2014it will be obvious to anyone which card the spectator will associate with the photo.<\/p>\n

If the words instead are hungry, tray, lettuce, bun, and ketchup, the ability to guess the right answer seems much more uncanny though.<\/p>\n

McOwan says that in order to determine the precise difference, he used a complex algorithm that searches the internet to find the words most often associated with particular images. The algorithm specifically looks at the words that popular commercial brands use to accompany their products\u2014so in a sense he\u2019s harnessing all the work of decades of marketing research to figure out which word associations we are most likely to make with an image. So even though it seems like you have a choice, your unconscious decision is locked in fate.<\/p>\n

\u201cThis is basically a new probe into looking at how people\u2019s brains work,\u201d McOwan says, adding that a magician could do this without a program but it would take a huge amount of trial and error before figuring out the most likely answers.<\/p>\n

Other tricks he has created with the help of a computer include the design of a\u00a0jigsaw puzzle\u00a0that appears to lose simple lines if you put it together a different way. It\u2019s based on a type of illusion in which an algorithm has calculated the amount of changes you can make to shapes without people noticing anything is amiss.<\/p>\n

This would be incredibly difficult for a human to design, but a computer program makes it quite easy.<\/p>\n