The Data Renaissance

by J.J. Sylvia IV

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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.

Description from LibreTexts.

Publisher
Fitchburg State University
Subjects
Engineering, Artificial Intelligence
Licence
CC BY-NC-SA 4.0, as LibreTexts states it. Non-commercial use only.
Who can read
Tweens profiles and older, judged from its title and subjects

Contents

LibreTexts writes equations in TeX, and here they show as TeX; the PDF has them typeset.

  1. Front Matter
  2. TitlePage
  3. InfoPage
  4. Table of Contents
  5. Licensing
  6. 22: Land Acknowledgement Statement for the ROTEL Grant
  7. 20: How to Use This Book
  8. 20: Project Rationale
  9. 1: Why Care About Data and Society?
  10. 1.1: Introduction
  11. 1.2: A Constitutional Right to Privacy?
  12. 1.3: Little Brother
  13. 1.4: Becoming Data
  14. 1.5: A/B and Multivariate Testing
  15. 1.6: Big Data
  16. 1.7: An Open Question
  17. 1.8: References
  18. 2: Generative AI in the Classroom and Workspace
  19. 2.1: Generative AI Pre-Test
  20. 2.2: How Generative AI Works
  21. 2.3: Differences Between ChatGPT 3 and 4
  22. 2.4: Links to Tools
  23. 2.5: Prompt-Writing Tips
  24. 2.6: AI Career Research
  25. 2.7: Hands-on Project
  26. 2.8: Discussion or Reflection Questions
  27. 2.9: Language, Diversity, Inclusivity, and ChaptGPT
  28. 2.10: Post-Test and Survey
  29. 2.11: Wrap-up
  30. 2.12: Further Reading
  31. 3: Case Study- "It's Perfect, Four Stars!"
  32. 3.1: Human Commerce
  33. 3.2: Living and Dying by the Algorithms
  34. 3.3: The “Fault” in Our Stars
  35. 3.4: Who Rates the Rater?
  36. 3.5: The Shift to “Objective” Stars
  37. 3.6: Who Are We Rating?
  38. 3.7: Conclusion
  39. 4: Media and Data Literacy
  40. 4.1: Introduction
  41. 4.2: Media Literacy
  42. 4.3: Challenges with Media Literacy
  43. 4.4: Data Literacy
  44. 4.5: Similarities
  45. 4.6: Understanding Data Literacy Skills
  46. 4.7: Media Literacy and Data Literacy Skills
  47. 4.8: Wrap Up
  48. 4.9: References
  49. 5: The American Motion Picture Industry and Big Data
  50. 5.1: Introduction
  51. 5.2: Predicting Box-Office Success in the Film Industry
  52. 5.3: Big Data in the Film Industry
  53. 5.4: How Data Has Been Used in the Film Industry
  54. 5.5: Into the Future
  55. 5.6: The Advantages of Big Data in the Film Industry
  56. 5.7: The Limitations of Big Data in the Film Industry
  57. 5.8: Outlook
  58. 5.9: Conclusion
  59. 5.10: Wrap up
  60. 5.11: References
  61. 6: Data in Sports Marketing
  62. 6.1: Introduction
  63. 6.2: Understanding Big Data
  64. 6.3: Sources of Data in Sports Marketing
  65. 6.4: Data and Target Audience
  66. 6.5: Data Used for Revenue
  67. 6.6: Data Used for Campaigns
  68. 6.7: The Future of Sports Marketing
  69. 6.8: Conclusion
  70. 6.9: Wrap Up
  71. 6.10: References
  72. 7: Data in Public Relations, Social Media, and Advertising
  73. 7.1: Key Essentials
  74. 7.2: Big Data
  75. 7.3: Wrap Up
  76. 7.4: References
  77. 8: Machine Learning in the Development of Video Games
  78. 8.1: Introduction
  79. 8.2: Types of Learning
  80. 8.3: Modern Applications of AI in Games
  81. 8.4: Cheat Detection
  82. 8.5: New Page
  83. 8.6: New Page
  84. 8.7: New Page
  85. 9: The Use of Matchmaking Data for Competitive Online Multiplayer Gaming
  86. 9.1: Introduction
  87. 9.2: The Matchmaking Process
  88. 9.3: Analyzing Other Approaches
  89. 10: Video Games, Microtransactions, and Data
  90. 10.1: Introduction
  91. 10.2: How Common are Microtransactions?
  92. 10.3: A Brief History
  93. 10.4: How Quickly Can it Add Up?
  94. 10.5: Impact of Microtransactions
  95. 10.6: New Page
  96. 10.7: New Page
  97. 10.8: New Page
  98. 11: Artificial Intelligence in Strategic Communication
  99. 11.1: Introduction
  100. 11.2: AI and Society
  101. 11.3: Enhancing Creativity and Productivity with AI
  102. 11.4: AI for Image Creation and Decision Making
  103. 11.5: AI Tools and Applications for Social Media
  104. 11.6: Legal and Social Implications of AI
  105. 11.7: AI Ethics- Privacy, Security, and Bias
  106. 11.8: The Future of AI and Jobs
  107. 11.9: New Page
  108. 12: SOPHIA Discussion Guides
  109. 12.1: Ethics of Search Engines
  110. 12.2: COVID-19- Surveillance and Personal Privacy
  111. 12.3: AI and Ethics- A Discussion
  112. 12.4: The Ethics of Fake News
  113. 12.5: The Ethics of Social Media Use By Children
  114. 13: Data Feminism- The Numbers Don’t Speak for Themselves
  115. 13.1: Principle- Consider Context
  116. 13.2: Wrap Up
  117. 14: Algorithms in the Age of Capitalism
  118. 14.1: What Is an Algorithm?
  119. 14.2: Complications with Algorithmic Systems
  120. 14.3: What is Algorithmic Accountability?
  121. 14.4: New Page
  122. 14.5: New Page
  123. 15: Recommended Reading (and Listening/Viewing)
  124. 15.1: Original Contributors
  125. 15.2: Grant Information
  126. 15.3: Version History
  127. Back Matter
  128. Index
  129. Glossary
  130. Detailed Licensing