The Role of Computational Systems in Magic Trick Design

Introduction

As the President of the FISM International and CEO & founder of ab studio, I am continually fascinated by the intersections between magic, psychology, and technology. 

A recent study published in PLOS ONE, "The magic words: Using computers to uncover mental associations for use in magic trick design," by Howard Williams and Peter W. McOwan, delves into these intersections in a way that is both groundbreaking and deeply insightful. 

This research presents a novel approach to magic trick design by leveraging computational systems to uncover and utilize mental associations, thereby enhancing the magician's ability to create compelling and surprising effects.

The Intersection of Magic and Technology

Magic, at its core, relies heavily on psychological principles.

The magician's goal is to manipulate the spectator's perception and cognitive processes, creating experiences that defy logical explanation. Traditionally, this has been achieved through sleight of hand, misdirection, and a deep understanding of human psychology. However, Williams and McOwan's research introduces a new dimension to this practice: the use of computer technology to analyze and exploit mental associations.

Gilbreath Principles and Card Tricks

One of the fundamental techniques explored in the study is the use of the Gilbreath principles in card tricks. The Gilbreath principles, discovered by Norman Gilbreath in 1958, involve mathematical properties of a deck of cards that remain consistent even after shuffling. These principles allow magicians to predict and control the arrangement of cards in a seemingly shuffled deck. By integrating these principles with computational systems, the researchers developed a card trick that combines human cognitive patterns with algorithmic precision.

Associative Thinking and Mentalism

Mentalism, a branch of magic that focuses on creating the illusion of mind reading (and not only), often relies on associative thinking.

Mentalists predict choices or behaviors based on common mental associations. For instance, when asked to quickly name a flower, many people will say "rose" due to its strong associative presence in our minds. The study explores how computational systems can identify and utilize these associations, enhancing the magician's ability to predict and influence spectator choices.

Automatic Thinking and Cognitive Systems

The research also draws on Daniel Kahneman's theory of cognitive systems, which differentiates between automatic (System 1) and effortful (System 2) thinking.

System 1 operates quickly and effortlessly, while System 2 requires conscious, deliberate thought. In magic, magicians aim to engage System 1, as it is more susceptible to deception.

By designing tricks that leverage automatic thinking, magicians can create more convincing illusions. 

The computational system developed by Williams and McOwan aids in this process by analyzing linguistic and visual data to find patterns that are likely to trigger automatic responses.

The Association Trick: A Case Study

The culmination of this research is the development of a new magic trick, referred to as the "Association trick."

This trick uses two decks of custom playing cards, one containing words and the other containing images. These decks are designed based on pre-defined conceptual categories that are derived from crowd-sourced psychological data. During the performance, the spectator is asked to quickly choose a word and an image that "go really well together."

The magician's prediction of this choice, seemingly made in advance, is based on the strong mental associations identified by the computational system.

Psychological Data Bank and Automated Processing

The creation of the Association trick relies on a psychological data bank gathered through online experiments.

Participants provided words and images associated with well-known trademarks, creating a repository of mental associations. This data was then processed using computational techniques to identify distinct conceptual categories.

By automating the data gathering and analysis process, the researchers significantly reduced the effort required for human designers to sift through and categorize the data.

Implications for Magic and Beyond

This study not only advances the field of magic trick design but also has broader implications for understanding human cognition and the potential of computational systems in creative disciplines. The integration of this technology in magic opens up new possibilities for designing tricks that are more sophisticated and psychologically compelling. It also highlights the importance of interdisciplinary research, combining insights from psychology, computer science, and the performing arts.

Anecdote

In 1984, I was a young Computer Science student at the University of Bologna and an active member of the city's magic club, which was presided over by the late Alberto Sitta. During that time, I wrote an article for the association's periodical titled "Computermagia".

Although 40 years have passed since then, the topic remains incredibly relevant today. For those curious to read that article (in Italian), here is the link., 

Conclusion

As magicians, we are always looking for new ways to surprise and delight our audiences.

The work of Williams and McOwan represents a significant step forward in this quest. By using computational systems to uncover and exploit mental associations, we can create more powerful and memorable magic tricks. This research not only enriches our understanding of the cognitive processes underlying magic but also demonstrates the exciting potential of technology to enhance our art.

As we continue to explore these intersections, we can continue look forward to a future where magic will be (as in the past) innovation and discovery. 

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