AI Helps Magicians Perform Mind Reading Tricks – IEEE Spectrum

Illustration: iStockphoto Computer algorithms can help magicians create magic tricks that exploit human psychology

You are presented with two decks, one with images and the other with words. The magician shuffles and distributesthe decks into piles of four cards. You get to choose twopiles, one from the word deck and one from the image deck, to make a hand of eight cards. Then youre invited to picka word card and and an imagecardfrom yourhand.Once youve selected a pair, youwatch the magician reveal a previously written prediction about the cards youve chosen. The prediction is correct!

That kind of mind-reading magic trick could benefitfrom new AI computer algorithms. These algorithms are designed to exploithuman psychology andhelpmagicians choosethe best card combinations.

Thisassociation magic trickrelies upon making a spectator believe that the magician hasmanaged to predict his or herfree choice from a random combination ofshuffled cards. In reality, the magician has preselected two decks of cards that together containa category of card pairs that triggera particularly powerful mental association for most people. To help pull off this mind-reading illusion, computer scientists created a computer algorithm that can automatically help find compellingword and image combinations.

First and foremost its an entertaining magic trick we have built, but it does potentially allow insight into the processes that humans use to decide associations, saysPeter McOwan, a professor of computer science at Queen Mary University London in the UK.There are a range of mentalism tricks that use associations to accomplish their effects and similar computational frameworks could be applied across that range, he said.

McOwan began practicing magic as a hobby in his teens. He has since used magic tricks to teach computer algorithms and haswrittenfree e-books on the intersection between the two subjects. In recent years, McOwan has teamed up withHoward Williams, another computer scientistat Queen Mary University London, to develop computer algorithms that can help create new magic tricks. Their latest study on the association magic trick was published in the 9 Aug 2017 issue of the journal PLOS One.

The association magic trick takes advantage of how the human subconscious tends to formstrong mental associations between certain concepts. For example, people may quickly make food associations between images of burgers or fruitand related words such asbites,treats,snack andfeast. The human subconscious can quickly recognize and process such associations in a way that appears almost automatic to the conscious mind.

Another key part of the trick involves an appreciation of two psychological systems that underlay our decision making, as described byDaniel Kahneman, a psychologist and Nobel Prize-winner. System 1 covers the swift and seemingly automatic mental processing. System 2 refers to the more active, conscious thinking involved in planning, puzzle solvingor calculations.

The magician wants the spectator participating in the magic show to use the first system and make the automatic association because it makes his or her choice predictableespecially when the decks of cards are organized and shuffled in a way that ensures a matched pair of cards that belongto a certain category will always be among the choices. So the magician adds time pressure by asking the spectator to make a quick decision. That pressure typically ensures the spectator makes the predictable choice rather than making a more idiosyncratic pairingbased on the more conscious thought processes of the second system.

To collect relevant data in making the magic trick, the Queen Mary University London researchersperformed an online psychology experiment by showing human participants various selections of 10 trademarks from a pool of 100 of the most famous trademarks. The researchers then askedparticipantsto write down any words about how the trademarks made them feel, along with any otherassociations they had with each mark.

But theresearchers alsodeveloped an AI to help themfindstrong associations for the magic trick. First, their computer algorithm ran Internet searches on popular trademarks and plucked words from the webpages linked by the top ten search results for each trademark. Second, itused a previously developed search algorithm, called BM25, to organizeand rank the collecteddata according to certain association categories (such as food-related words). Additional AI techniques called word2vec and Wordnet helpedby providingsimilarity scores for certain word pairings.

The AI by itself was not necessarily able to find the strongest or most useful associations for the magic trick without human help. But suchautomated data gathering and organization could prove a handy time-saving tool for complementing data collected from the more time-consuming experimental surveys, according to Williams at Queen Mary University London. He described the tradeoff as follows:

Automated data gathering is useful as it is quick and can gather large sets of data. Experiments take longer to organize, perform, process data, etc., but provide more specific and targeted data. [Its] essentially a tradeoff between quality and quantity. Though quantity provides broadness, and is useful in its own right.

That process led Williams and McOwan to create image and word card decks that contained the food category as the likeliest choice. Theytested out their association magic trick on 143individuals during theBig Bang 2013 science fair in Birmingham, UK, where it succeeded in all but 15 cases. Those more unusual word and image pairings chosen in the unsuccessful cases could potentially be excluded by the computer algorithm or by hand in the future.

Even though there is a fairly clear pathway we have created in the trick for them to follow in the performances, some people just had left field associationsprobably influenced by their life experiences, McOwan says.Its an area worth looking at more.

Magicians could eventually makeuseof popular AI techniques such as machine learning and deep learning that can automatically find and learn from patterns in data. McOwan speculated that such techniques could prove useful in cold reading, which is when a magician uses psychological tricks and a data-driven understanding of population trends to pretend to divine personal details about a stranger.

The researchers have already commercialized magic tricks that were created with the help of computer algorithms. In 2014, they used a computer algorithm to help create a magic jigsaw puzzle that makes certain shapes seem to disappear upon reassembly based on certain geometric principles. That jigsaw puzzlesold out two production runs in a well known London magic shop, McOwan says.

The idea of computer algorithms helping create magic tricks may lack the emotional drama ofChristopher Nolans film The Prestige,where rival magicians vie to perfecttheir magic illusions. But even some of thefictional wizards in the magical world of Harry Potter might appreciate muggle AI technology that can help magicians seem toperform mind reading without wands and spells.

Of course a trick is only as good as the performer and our work is simply giving new tools to create new methods to perform with, McOwan says.The real magic still lies with the magician.

IEEE Spectrums general technology blog, featuring news, analysis, and opinions about engineering, consumer electronics, and technology and society, from the editorial staff and freelance contributors.

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AI Helps Magicians Perform Mind Reading Tricks - IEEE Spectrum