The Data Renaissance: Analyzing the Disciplinary Effects of Big Data, Artificial Intelligence, and Beyond [Revised Edition]

• Land Acknowledgement Statement for the ROTEL Grant
• How to Use This Book
• Project Rationale
• Introduction
• I. Why Care About Data & Society?
• Introduction
• A Constitutional Right to Privacy?
• Little Brother
• Becoming Data
• A/B and Multivariate Testing
• Big Data
• An Open Question
• Wrap Up
• References
• II. Generative AI in the Classroom and Workspace
• Generative AI Pre-Test
• How Generative AI Works
• Differences Between ChatGPT 3 and 4
• Links to Tools
• Prompt-Writing Tips
• AI Career Research
• Hands-on Project
• Discussion or Reflection Questions
• Language, Diversity, Inclusivity, and ChaptGPT
• Post-Test and Survey
• Wrap Up
• Further Reading
• III. Case Study: "It's Perfect, Four Stars!"
• Introduction
• Human Commerce
• Living and Dying by the Algorithms
• The “Fault” in Our Stars
• Who Rates the Rater?
• The Shift to “Objective” Stars
• Who Are We Rating?
• Conclusion
• Wrap Up
• References
• IV. Media & Data Literacy
• Introduction
• Media Literacy
• Challenges with Media Literacy
• Data Literacy
• Similarities
• Understanding Data Literacy Skills
• Media Literacy & Data Literacy Skills
• Conclusion
• Wrap Up
• References
• V. The American Motion Picture Industry and Big Data
• Introduction
• Predicting Box-Office Success in the Film Industry
• Big Data in the Film Industry
• How Data Has Been Used in the Film Industry
• Into the Future
• The Advantages of Big Data in the Film Industry
• The Limitations of Big Data in the Film Industry
• Outlook
• Conclusion
• Wrap Up
• References
• VI. Data in Sports Marketing
• Introduction
• Understanding Big Data
• Sources of Data in Sports Marketing
• Data and Target Audience
• Data Used for Revenue
• Data Used for Campaigns
• The Future of Sports Marketing
• Conclusion
• Wrap Up
• References
• VII. Data in Public Relations, Social Media, and Advertising
• Key Essentials
• Big Data
• Wrap Up
• References
• VIII. Machine Learning in the Development of Video Games
• Introduction
• Types of Learning
• Modern Applications of AI in Games
• Cheat Detection
• Conclusion
• Wrap Up
• References
• IX. The Use of Matchmaking Data for Competitive Online Multiplayer Gaming
• Introduction
• The Matchmaking Process
• Analyzing Other Approaches
• Conclusion
• Wrap Up
• References
• X. Video Games, Microstransactions, and Data
• Introduction
• How Common are Microstransactions?
• A Brief History
• How Quickly Can it Add Up?
• Impact of Microstransactions
• Conclusion
• Wrap Up
• References
• XI. SOPHIA Discussion Guides
• Ethics of Search Engines
• COVID-19: Surveillance and Personal Privacy
• AI & Ethics: A Discussion
• The Ethics of Fake News
• The Ethics of Social Media Use By Children
• XII. Data Feminism: The Numbers Don’t Speak for Themselves
• Principle: Consider Context
• Wrap Up
• XIII. Algorithms in the Age of Capitalism
• What Is an Algorithm?
• Complications with Algorithmic Systems
• What is Algorithmic Accountability?
• Wrap Up
• References
• XIV. Recommended Reading (and Listening/Viewing)
• Original Contributors
• Grant Information

The Data Renaissance delves into the complexities of data's role in various industries and its broader impact on society. It highlights the challenges in investigating data practices, citing examples like TikTok, where algorithms and data handling are closely guarded secrets. The content, contributed by students under the guidance of an expert, covers a wide range of topics, including the ethical aspects of generative AI in education and the workplace, and case studies reflecting real-world experiences. This evolving text, intended to be updated with each class, serves as a dynamic resource for educators and students alike, offering insights and discussion guides for an in-depth understanding of the ever-changing landscape of data in our digital age.