Consumer Perceptions of Artificial Intelligence in Sports Betting
Start Date
2023 2:15 PM
Location
Alter Hall Poster Session 1 - 3rd floor
Abstract
In response to the tremendous growth of sports bettors in the U.S. (AGA 2019; 2022), many gambling and fantasy sports platforms have integrated artificial intelligence into their experience to provide recommendations that influence user engagement and performance (Hoffman 2021; Purser 2019). However, extant research demonstrates that despite the ability of artificial intelligence (AI) to assist individuals in decision-making, an aversion to AI emerges across a variety of domains (Longoni and Cian 2020). To date, however, we are not aware of any research that investigates the impact of AI in the context of sports betting. Further, we provide a nuanced perspective to this aversion to AI by investigating the mediating role of expertise (Jussupow et al., 2020).
Our findings suggest users are hesitant to follow AI recommendations, leading to suboptimal decision-making. Results from 6 studies suggest consumers evaluate AI as “less expert” than humans, are more averse to the AI recommendations and, thus behave (i.e., bet) in favor of the human recommendation. We demonstrate this effect experimentally using within- and between-subjects designs. The hypothesized relationship was consistently mediated by differences in perceived expertise, and independent of perceived trust, consumers’ betting and sports knowledge, and valence of information presented in the recommendation.
Consumer Perceptions of Artificial Intelligence in Sports Betting
Alter Hall Poster Session 1 - 3rd floor
In response to the tremendous growth of sports bettors in the U.S. (AGA 2019; 2022), many gambling and fantasy sports platforms have integrated artificial intelligence into their experience to provide recommendations that influence user engagement and performance (Hoffman 2021; Purser 2019). However, extant research demonstrates that despite the ability of artificial intelligence (AI) to assist individuals in decision-making, an aversion to AI emerges across a variety of domains (Longoni and Cian 2020). To date, however, we are not aware of any research that investigates the impact of AI in the context of sports betting. Further, we provide a nuanced perspective to this aversion to AI by investigating the mediating role of expertise (Jussupow et al., 2020).
Our findings suggest users are hesitant to follow AI recommendations, leading to suboptimal decision-making. Results from 6 studies suggest consumers evaluate AI as “less expert” than humans, are more averse to the AI recommendations and, thus behave (i.e., bet) in favor of the human recommendation. We demonstrate this effect experimentally using within- and between-subjects designs. The hypothesized relationship was consistently mediated by differences in perceived expertise, and independent of perceived trust, consumers’ betting and sports knowledge, and valence of information presented in the recommendation.
