Using “Markers of Harm” to Track Risky Gambling in Two Cohorts of Online Sports Bettors

McAuliffe, William H.B.; Louderback, Eric R.; Edson, Timothy C.; LaPlante, Debi A.; Nelson, Sarah E.

doi:10.1007/s10899-021-10097-0

Cited by 7 publications

(6 citation statements)

References 47 publications

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“…The high percentage of problem gamblers in self-report studies is in stark contrast to previous studies classifying problem gamblers using pure behavioral tracking data. McAuliffe et al ( 2022 ) reported that less than 1% of players were regarded as high-risk based on the Senet Group’s markers of harm. They also reported that Entain , which was part of the group of companies which defined the markers of harm, identified less than 6% of players as being high risk.…”

Section: Discussionmentioning

confidence: 99%

“…As a result of a number of meetings between five major gambling operators – 888 Holdings, GVC Holdings (now called Entain ), Sky Betting & Gaming, William Hill , and Paddy Power – the Senet Group developed a set of nine markers of harm to identify problematic gambling (McAuliffe et al, 2022 ). The Senet Group is an organization which was established in 2014 by the leading high-street bookmakers in the UK which was then taken over by the Betting and Gaming Council (Narayan, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…In the peer-reviewed literature, McAuliffe et al ( 2022 ) used two datasets from bwin’s online sportsbook (one covering 2005–2007, and another covering 2015–2017) to evaluate the prevalence of gambling markers of harm, as well as their intercorrelations, inter-individual and intraindividual stability, and correlations with extreme betting activity, demographic variables, and gambling harm proxies. The authors found that on an average day, less than 1% of players had risk scores high enough to trigger an intervention.…”

Section: Introductionmentioning

confidence: 99%

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Using artificial intelligence algorithms to predict self-reported problem gambling with account-based player data in an online casino setting

Auer¹,

Griffiths

2022

J Gambl Stud

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In recent years researchers have emphasized the importance of artificial intelligence (AI) algorithms as a tool to detect problem gambling online. AI algorithms require a training dataset to learn the patterns of a prespecified group. Problem gambling screens are one method for the collection of the necessary input data to train AI algorithms. The present study’s main aim was to identify the most significant behavioral patterns which predict self-reported problem gambling. In order to fulfil the aim, the study analyzed data from a sample of real-world online casino players and matched their self-report (subjective) responses concerning problem gambling with the participants’ actual (objective) gambling behavior. More specifically, the authors were given access to the raw data of 1,287 players from a European online gambling casino who answered questions on the Problem Gambling Severity Index (PGSI) between September 2021 and February 2022. Random forest and gradient boost machine algorithms were trained to predict self-reported problem gambling based on the independent variables (e.g., wagering, depositing, gambling frequency). The random forest model predicted self-reported problem gambling better than gradient boost. Moreover, problem gamblers showed a distinct pattern with respect to their gambling based on the player tracking data. More specifically, problem gamblers lost more money per gambling day, lost more money per gambling session, and deposited money more frequently per gambling session. Problem gamblers also tended to deplete their gambling accounts more frequently compared to non-problem gamblers. A subgroup of problem gamblers identified as being at greater harm (based on their response to PGSI items) showed even higher values with respect to the aforementioned gambling behaviors. The study showed that self-reported problem gambling can be predicted by AI algorithms with high accuracy based on player tracking data.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using artificial intelligence algorithms to predict self-reported problem gambling with account-based player data in an online casino setting

Auer¹,

Griffiths

2022

J Gambl Stud

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“…After screening the titles and abstracts, we deemed 44 records as potentially eligible for inclusion. From these, we excluded 26 for not meeting the eligibility criteria: 17 were not sufficiently related to the gambling field (e.g., Kim & Werbach, 2016;Uusitalo et al, 2021), 7 lacked a discussion of risks and/or ethical concerns (e.g., Auer & Griffiths, 2023;McAuliffe et al, 2022), and 4 were unidentified duplicates. We selected 16 studies to include in the final review.…”

Section: Resultsmentioning

confidence: 99%

Identifying Risks and Ethical Considerations of AI in Gambling: A Scoping Review

Ghaharian,

Binesh

2024

Preprint

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The proliferation of data and artificial intelligence (AI) throughout society has raised concerns about its potential misuse and threats across industries. In this paper we explore the risks and ethical considerations of AI applications in gambling, an industry that makes significant contributions to many tourism destinations and local economies around the world. We conducted a scoping review to collect the breadth of literature and to understand the current state of knowledge. Our search yielded 2,499 potentially relevant documents, from which we deemed 16 as eligible for inclusion. A content analysis revealed convergence around six main themes: (1) Explainability, (2) Exploitation, (3) Algorithmic Flaws, (4) Consumer Rights, (5) Accountability, and (6) Human-in-the-Loop. We found that these gambling-specific themes largely overlap with broader AI principles. Most records focused on algorithmic strategies to reduce gambling-related harm (n = 12/16), thus we call for more attention to be turned to commercially driven AI applications. We provide a theoretical evaluation that illustrates the challenges involved for stakeholders tasked with governing AI risks and associated ethical considerations. As a globally reaching product, gambling regulators and operators need to be cognizant, not just of philosophical principles, but also of the rich tapestry of global ethical traditions.

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“…In other work, a consortium of gambling operators developed the Markers of Harm system (i.e., an algorithm) to identify problematic sports-betting behaviors. Although some markers were positively associated with gambling engagement and proxies of problem gambling, researchers suggested that further adjustments should be made to improve the algorithm's group classification and risk thresholds ( McAuliffe, Louderback, Edson, LaPlante, & Nelson, 2022 ). Table 5 summarizes these studies.…”

Section: Resultsmentioning

confidence: 99%

Sports betting around the world: A systematic review

Etuk

Abarbanel

et al. 2022

JBA

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Background and aims This systematic review examines whether sports betting behaviors differ among and between sports bettors in different countries, evaluates psychosocial problems related to sports betting behaviors and how problems may vary by country, and lastly, summarizes the current regulatory guidelines for sports betting. Methods We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and included peer-reviewed articles from PubMed, Web of Science, and PsycINFO. Studies on sports betting behavior were included if they were published in English or Chinese between January 1, 2010 and March 28th, 2022. We gathered regulatory information from peer-reviewed articles, legal acts, and relevant websites. Of 2,450 articles screened, 65 were included in the final review. Results Marketing and promotion of sports betting were more prominent for sports betting in Australia and the United Kingdom. Interviews with sports bettors demonstrated that sports betting is persuasive and normalized. Psychosocial problems do not appear to differ greatly by country, and sports betting appears to be associated with elevated levels of problem gambling. Responsible gambling approaches have helped address risky sports betting behaviors. China and South Korea have imposed more strict regulations and restrictions on sports betting access in comparison to countries such as Australia or the United States. Discussion and conclusions Currently, sports betting is easy to access, normalized, and contains many attractive features for sports bettors. Psychoeducation about potential risks of sports betting and encouragement of responsible gambling strategies could help lessen risky sports-betting behaviors, though cross-cultural adaptations should be explored.

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Using “Markers of Harm” to Track Risky Gambling in Two Cohorts of Online Sports Bettors

Abstract: Using "Markers of Harm" to Track Risky Gambling in Two Cohorts of Online Sports BettorsPlease note that this is a non-peer-reviewed pre-print that is currently under review.

Cited by 7 publications

References 47 publications

Using artificial intelligence algorithms to predict self-reported problem gambling with account-based player data in an online casino setting

Using artificial intelligence algorithms to predict self-reported problem gambling with account-based player data in an online casino setting

Identifying Risks and Ethical Considerations of AI in Gambling: A Scoping Review

Sports betting around the world: A systematic review

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