Precision and Ethics in Sports Betting
Evaluating the Impact of AI on Prediction Accuracy and User Trust
My Role: Lead Researcher
In this project, I served as the lead researcher, focusing on the role of AI in enhancing accuracy, user experience, and ethical transparency in sports betting apps. The goal was to explore how AI-driven prediction tools can promote responsible gambling by providing reliable, data-driven insights. Through a combination of observational studies, simulations, and user interviews, I investigated the informatics principles that contribute to effective and ethical AI in sports betting, aiming to offer insights that could shape best practices in the industry.
An in-depth 8-page project report is available for download below.
Summary of Research
Abstract
This research examines AI-driven sports betting apps to determine the informatics principles that enhance prediction accuracy, efficiency, and ethical transparency. Focusing on popular U.S. sports leagues and betting platforms, the study aims to identify how AI tools can promote responsible gambling while delivering accurate, user-friendly predictions. Through a mixed-method approach, including observational studies, interviews, and simulation analysis, the research provides a foundation for developing ethical AI tools for the sports betting industry.
Introduction
The integration of AI in sports betting has transformed the industry by making betting predictions more accessible and data-driven. This study centers on how AI can improve the betting experience by enhancing prediction accuracy and promoting responsible usage on platforms like DraftKings and FanDuel. Focusing on U.S. sports leagues and a 21-35 age demographic, the research examines the dual impact of AI technology and ethical considerations in the sports betting market.
Literature Review/Prior Work
AI's potential in sports betting lies in its ability to reduce bias and improve prediction reliability, as shown by companies like Stratagem and Stats Perform. Studies highlight AI's superiority in accuracy over human decision-making, while ethical principles such as transparency and fairness are essential to fostering trust. This review outlines existing gaps in the field, especially regarding informatics principles that support effective, responsible, and ethical AI applications.
Research Questions
The central research question focuses on identifying the informatics principles that improve AI-driven sports predictions in accuracy, efficiency, and trustworthiness. Additionally, the study explores how user interface design impacts user engagement and trust, aiming to uncover design factors that facilitate responsible betting practices.
Research Design
A mixed-method design combines observational studies, interviews, and simulation analysis to analyze AI's role in sports betting. The observational study captures real-world behavior with AI-based apps, while interviews provide insights into user trust and satisfaction. Simulations further assess each app's predictive accuracy, enabling a comprehensive analysis of informatics principles impacting betting behavior and prediction reliability.
Generating Data
Data is generated from three sources: quantitative data from the observational study, qualitative data from user interviews, and accuracy data from simulations. These combined datasets offer a holistic view of how different informatics principles and AI features affect user behavior, ethical engagement, and the predictive success of betting apps.
Analyzing Data
The analysis process involves cross-referencing data from all research methods, using statistical techniques for quantitative data and coding for themes in qualitative data. This approach identifies trends in user trust, prediction accuracy, and user experience, isolating informatics principles that significantly contribute to effective and ethical AI in sports betting.
Ethical considerations
Ethics are central to the study due to gambling’s addictive potential, with participants informed of risks and provided support resources. Financial coverage for losses up to $1,000 and access to rehabilitation services are offered, ensuring a safe environment for participants. The research is conducted in regions where third-party AI betting is legal, maintaining compliance with local laws.
Discussion
This study extends beyond evaluating AI's predictive accuracy, addressing the ethical implications of AI-driven betting. By focusing on informatics principles, the research aims to inspire industry guidelines for safer, responsible betting practices. The findings may bridge knowledge gaps in balancing prediction accuracy with user well-being, supporting ethical standards in AI.
Conclusions
This research seeks to pinpoint informatics principles that boost AI accuracy, efficiency, and trustworthiness in sports betting apps, also examining the influence of UI design on user engagement. By integrating data from multiple methods, the study offers valuable insights for designing ethical, user-centered AI tools, shaping future advancements in responsible sports betting technology