Chasing Luck: Data-driven Prediction, Faith, Hunch, and Cultural Norms in Rural Betting Practices

Title of the Paper

Chasing Luck: Data-driven Prediction, Faith, Hunch, and Cultural Norms in Rural Betting Practices

Bibliographic Information

• Subject Area: Human-Computer Interaction (HCI), Data-driven Decision Making, Cultural Studies, Artificial Intelligence
• Keywords: Luck, Data-driven, Faith, Hunch, Proxy Rationality, Betting, Rural HCI, Bangladesh

Research Background and Problem Statement

• Identified Problems or Challenges:

  1. Current data-driven systems and AI tools are typically grounded in scientific and economic rationality, emphasizing objectivity while neglecting users' social, cultural, and emotional values.
  2. Designing data-driven systems that coexist with collective decision-making and belief systems in rural areas is challenging, leading to unpredictability and inaccessibility of technology.
  3. There is limited research on how religion, faith, and culture influence the use of data-driven tools and how these tools are collectively utilized in developing countries.

• Significance: Studying rural betting practices can uncover ways to design data-driven tools that are more culturally attuned, thereby improving the usability and acceptance of AI and computing technologies.

• Research Motivation and Related Work:

  1. Research on the interpretability and understandability of data-driven systems often focuses on economic rationality, lacking consideration for non-scientific rationality (e.g., religious beliefs and rituals).
  2. Related work in HCI and ICTD primarily addresses issues of technological access and theory-driven design, with limited exploration of gambling and other recreational behaviors.
  3. This study fills the research gap through an in-depth ethnographic investigation of rural betting practices in Bangladesh.

Solution

• Methods or Solutions: The author conducted a ten-month ethnographic study across seven rural villages in Bangladesh, exploring how bettors integrate faith, hunches, and cultural values with the following:

  1. Probability and statistical information from online betting platforms.
  2. Community-based betting rules and agreements.
  3. Guidance from professional bettors and collective group decision-making.

• Innovative Contributions:

  1. Demonstrates how bettors integrate information and make decisions influenced by faith and cultural factors beyond scientific rationality.
  2. Proposes that HCI theories should embrace non-Western rationality perspectives (e.g., luck and faith) and explains their impact on the design of data-driven tools.
  3. Emphasizes culturally sensitive technology design to address the unique needs of societies in the Global South.

• Implementation Steps and Key Techniques:

  1. User data collection and ethnographic observation: Investigated bettors' behaviors, betting processes, tool usage, and social interactions.
  2. Analysis of betting information and outcomes: Documented how bettors processed probability information and cultural inputs.
  3. Conducted qualitative analysis using open coding and thematic analysis to extract the decision-making logic behind user betting behaviors.

Research Outcomes

• Specific Results:

  1. Described rural betting practices in Bangladesh, including types of bets, tool usage, and community-driven decision-making processes.
  2. Revealed that bettors' rationality is influenced not only by probability and statistics but also by culture, religion, and social relationships.
  3. Proposed that HCI design should incorporate faith-driven design, privacy protection, and culturally sensitive technologies to better serve communities in the Global South.

• Advantages Compared to Existing Solutions:

  1. Improved the design framework of existing data-driven systems by enhancing compatibility with social and cultural value systems.
  2. Advanced postcolonial computing and embedded design principles to balance the contradictions between technology and usage environments.

• Experimental or Evaluation Results:

  1. More rural bettors adopted community-driven rules and group decision-making, reflecting the highly socialized and culturally rooted nature of betting habits.
  2. Faith and notions of luck significantly influenced betting decisions, indicating that data-driven tools that ignore these factors may fail to fully meet user needs.

• Limitations and Future Directions:

  • Limitations:
    1. The study sample was primarily derived from the researcher's network, introducing selection bias.
    2. Data was not subjected to statistical significance testing, relying solely on ethnographic observation and user narratives.
  • Future Directions:
    1. Expand research on non-scientific rationality to design AI technologies adapted to the cultural contexts of the Global South.
    2. Strengthen quantitative analysis of collective decision-making behaviors to uncover interactions with AI recommendations.
    3. Explore faith-driven technology design to promote socially and culturally sensitive computing solutions on a global scale.