Addiction by Design

By Natasha Dow Schll. 2012

816 citations recorded by the source corpus.

Recent decades have seen a dramatic shift away from social forms of gambling played around roulette wheels and card tables to solitary gambling at electronic terminals. Slot machines, revamped by ever more compelling digital and video technology, have unseated traditional casino games as the gambling industry's revenue mainstay. Addiction by Design takes readers into the intriguing world of machine gambling, an increasingly popular and absorbing form of play that blurs the line between human and machine, compulsion and control, risk and reward. Drawing on fifteen years of field research in Las Vegas, anthropologist Natasha Dow Schll shows how the mechanical rhythm of electronic gambling pulls players into a trancelike state they call the "machine zone," in which daily worries, social demands, and even bodily awareness fade away. Once in the zone, gambling addicts play not to win but simply to keep playing, for as long as possible--even at the cost of physical and economic exhaustion. In continuous machine play, gamblers seek to lose themselves while the gambling industry seeks profit. Schll describes the strategic calculations behind game algorithms and machine ergonomics, casino architecture and "ambience management," player tracking and cash access systems--all designed to meet the market's desire for maximum "time on device." Her account moves from casino floors into gamblers' everyday lives, from gambling industry conventions and Gamblers Anonymous meetings to regulatory debates over whether addiction to gambling machines stems from the consumer, the product, or the interplay between the two. Addiction by Design is a compelling inquiry into the intensifying traffic between people and machines of chance, offering clues to some of the broader anxieties and predicaments of contemporary life. At stake in Schll's account of the intensifying traffic between people and machines of chance is a blurring of the line between design and experience, profit and loss, control and compulsion.

Subfields: Clinical Psychology

View Paper: https://www.semanticscholar.org/paper/672c955c3d2993afb3a09847458ba9dbeed07d16

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In Clinical Psychology

1. Per Binde
2. U. Romild
3. R. Volberg
4. Martin Young
5. M. Fourcade
6. Arunesh Mathur
7. Karen Yeung
8. Francis Markham

Citations in the corpus

• What Makes a Dark Pattern... Dark?: Design Attributes, Normative Considerations, and Measurement Methods (2021, background): “In fact, Schüll observed that online services have created techniques such as the infinite scroll user interface, or the YouTube autoplay feature in line with those developed by the gambling industry—many of which employ a variable-rewards schedule approach to keep users engaged [31, 45].”
• ‘Hypernudge’: Big Data as a mode of regulation by design (2017, positive): “…addicts and the U.S. gambling industry, in which the latter maximises its returns by successfully harnessing the power of algorithmic analytics to adapt the design of both casino layouts and the gambling machines which they house, in order to ‘give players what they want’(Dow Schull, 2012).”
• “Big Gambling”: The rise of the global industry-state gambling complex (2015, background): “Australian company Aristocrat Leisure pioneered the development of linked jackpots and multiline games, a move that was only possible due to the transition from mechanical to electronic machines (Schüll, 2012).”
• The Society of Algorithms (2021, background): “To capture the attention of users, developers employed addictive techniques pioneered in the gambling industry (Hwang 2020, Schüll 2012, Vaidhyanathan 2018).”
• Forms of gambling, gambling involvement and problem gambling: evidence from a Swedish population survey (2017, background): “For example, and allowing a bit of speculation, the first point on the EGM curve might represent people who escape into gambling, seeking dissociation, or have become addicted to EGMs (Dow Schüll, 2013).”
• Dark Patterns at Scale (2019, background): “, they can mislead and deceive users, e.g., by causing financial loss [1, 2], tricking users into giving up vast amounts of personal data [46], or inducing compulsive and addictive behavior in adults [74] and children [21]. While prior work [31, 32, 38, 48] has provided taxonomies to describe the ex”