Human Digital Twins: Predicting Humanity's Future one Human at a time.

The question: if every human has a digital twin then would be able to model humanity and predict the outcome at all levels? and for all instances?

Reducing humanity to this equation:

Given a digital twin for each human then we would have a digital twin for humanity.

The claim in this article is that we already have a digital twin for each human, it is the content of the each mobile phone! hence the equation becomes:

We can limit the sum to humans in a city, region, country or continent to get a twin for that specific part. We can then predict what is going to happen in that part.

This has profound implications as it would support the religious arguments that all that will happen is already known, yet there is individual freedom of choice (free will).

You are free to make your choice, but given your digital twin, AI can predict what it is going to be. When two human digital twins argue in cyber space AI knows the outcome in advance as we have the history of both yet each lives through the argument as it unfolds.

Elections, political decisions, trade wars, alliances, all choices at the personal and group level would be known in advance by applying the formula above.

Human Digital Twins and Mobile Phones

The notion of and examples of digital twins for humans have been around a while and we are the point where one can use a twin for dating.

"‘AI concierge’ will soon date hundreds of other people’s ‘concierges’ for you"

https://fortune.com/2024/05/10/bumbles-whitney-wolfe-herd-dating-concierge-artificial-intelligence/

There has also been multiple demonstrations on how a GenAI can organise events or do shopping on behalf of a human.

GenAI has already digested all knowledge available to date so it is simple to also acquire the knowledge specific to a single human being, preferences, habits and manners. Medical and health history. world views and opinions.

Your content on your mobile phone is your digital twin as that content represents all that you are reading, watching, writing, ordering, travel, everything. It is just a matter to time before GenAI will have access to the totality of this information to use as a representation of who you are, what you do and your values.

Currently, each application holds one piece of information, but the mobile phone holds all the history.

The GenAI application for the phone would continuously harvest all that information to keep the digital twin in sync.

Unlike profile data entered by humans into various apps, the digital twin is a true reflection of the human as there is no profile data for the human to fake like in dating apps. You are what you do and what you say every minute of the day and your own GenAI is tracking.

Implications of Digital Twins on Free Will

Human digital twins enable GenAI to predict actions with remarkable accuracy. By analyzing patterns in browsing habits, communication, location history, and social media activity, digital twins can anticipate decisions before they are consciously made by individuals.

The capacity to predict choice intersects with the longstanding philosophical debate between free will and determinism.

• Deterministic Viewpoint: If digital twins can predict actions accurately, it suggests a deterministic universe where choices are inevitable outcomes of preceding states. This viewpoint raises questions about moral responsibility and accountability.
• Free will: Some philosophers argue that free will and determinism are compatible, suggesting that predictions do not negate freedom but enhance understanding of the choice.

Real-World Consequences

Beyond philosophical debates, the ability of digital twins to predict human behavior has significant real-world implications, affecting personal autonomy, societal norms, and ethical considerations:

• Individual Autonomy: How do individuals maintain a sense of agency when their actions can be predicted? This could lead to changes in how people perceive their own freedom and identity.
• Behavioral Nudging: Organizations might use predictive models to influence choices through targeted advertising, political campaigning, and personalized content, subtly guiding decisions without explicit coercion.
• Social and Ethical Concerns: The collection and analysis of data by digital twins raise issues about privacy, consent, and surveillance.

On the positive side, human digital twins also offer opportunities to enhance decision-making:

• Informed Decision-Making: By providing insights into personal behavior patterns, digital twins can help individuals make more conscious and deliberate choices, potentially increasing personal freedom rather than diminishing it.
• Empowerment Through Awareness: Individuals could use digital twin insights to break harmful habits, set goals, and achieve personal growth by understanding their tendencies. A summary of past decisions and resulting outcomes will for sure modify future decisions.

Future

The intersection of digital twins and free will presents a complex and evolving landscape. While the predictive power of digital twins challenges traditional notions of autonomy, it also offers new possibilities for understanding and enhancing human decision-making. As technology continues to evolve, society must navigate the philosophical, ethical, and practical implications of these advancements, seeking a balance between the benefits of prediction and the preservation of human freedom.

In the future, there will be no need to argue with anyone about politics , let the twins argue. No need to date 100 people to find the right one, let the twin do it. All annoying social interactions would be delegated to the twin and only the enjoyable ones falling back to the human. What if your soul mate happens to be is in a far away place? twins have no geographical limit. Working on a complex topic? Let your twin discuss with thousands of other twins and flush out the one person of interest.

The possibilities are wild. Humans die but their twins would live on.

Would this move humanity towards a better place? The more people we interact with the less probability we would want to destroy them?

Would we then resolve conflict in the digital realm and avoid the associated emotional reactions? Let the twin handle it, let me know the outcome !

On the other hand, will we escape such a future once the human digital twin technology goes mainstream and once GenAI has the knowledge of everything and everyone?

interesting concept? use cases?

Notes for future research:

How much memory would the phone need to have to do the onDevice training?

since learning is continuous, then processing power is a critical factor only for inferencing latency.

Jensen explained how to do it using agents in his key note

(at -1:00:00 into the keynote video)

https://www.youtube.com/watch?v=pKXDVsWZmUU

Meta already using consumer data from their apps on the phone for AI purposes. from their privacy update policy in May 2024:

"To help bring these experiences to you, we'll now rely on the legal basis called legitimate interests for using your information to develop and improve AI at Meta."

Information known by apps on the mobile phone on continuous basis:

• all shopping, where, what and how much, online and in store
• all content consumed or created, liked and disliked, games, music, text, video and image
• all financial transactions
• all social media interaction and contacts, digital and physical
• all events, personal and professional
• all chat with friends, family, work and services
• content of all email sent and received
• Health data, sleep schedule, daily routine, activity
• Home layout, plants and devices, security camera feeds, video door bell feed
• Travel data, business, personal, local and international
• all usual locations, occasional locations, commute routes
• all subscriptions to media and other services
• Political affiliation, groups and causes

Applying GenAI to all this data, onDevice, will easily, define the digital twin as we have a history of everything over many years. The twin should behave and respond accordingly in any context on behalf of the human.

Second level of details on data collected by applications on a mobile phone:

?

Personal Information

1.??? Full Name

2.??? Nicknames

3.??? Email Addresses (multiple)

4.??? Phone Numbers (multiple)

5.??? Home Addresses (multiple)

6.??? Work Address

7.??? Date of Birth

8.??? Place of Birth

9.??? Gender

10. Profile Pictures

11. Relationship Status

12. Family Members

13. Social Security Number (or equivalent)

14. Driver’s License Number

15. Passport Number

Device Information

16. Device Manufacturer

17. Device Model

18. Operating System and Version

19. Device ID (e.g., IMEI, UDID)

20. Phone Number

21. Carrier Information

22. IP Address

23. MAC Address

24. Battery Level

25. Battery Health

26. Storage Capacity and Usage

27. Screen Resolution

28. Installed Apps and Versions

29. Network Type (Wi-Fi, 4G, 5G)

30. Network Speed

Location Data

31. Current GPS Location

32. Historical GPS Locations

33. Geofencing Data

34. Wi-Fi Location Data

35. Cell Tower Location Data

36. Location History from Maps?

Usage Data

37. App Usage Statistics (frequency, duration)

38. Time Spent on Apps

39. Interaction Data (e.g., clicks, screen touches)

40. Crash Reports

41. Performance Metrics

42. In-App Purchases

43. Feature Usage (which features are used most)

44. Settings and Preferences within Apps

45. Session Duration

46. Time of Day When Apps are Used

Network Information

47. Wi-Fi Networks (connected and available)

48. Bluetooth Connections (paired devices)

49. Cellular Network Information

50. Hotspot Usage

51. Communication Data

52. Call Logs (incoming, outgoing, missed)

53. SMS/MMS Logs

54. Contacts List (including contact photos)

55. Emails (subject, sender, receiver, content)

56. Messaging App Data (e.g., WhatsApp, Messenger)

57. Voicemail Data

58. Chat History

Media and Files

59. Photos and Videos (including metadata)

60. Audio Recordings

61. Files and Documents

62. Camera Access

63. Microphone Access

64. Screenshots

65. Downloads

66. Media Playlists

App-Specific Data

67. Social Media Activity (posts, likes, shares)

68. Social Media Contacts

69. Gaming Scores and Achievements

70. Game Progress and In-Game Purchases

71. Health and Fitness Data (e.g., steps, heart rate, sleep patterns)

72. Nutrition Data (calories, meals)

73. Financial Information (e.g., bank details, transaction history)

74. Shopping History and Preferences

75. Wishlist Items

76. Search History

77. Browsing History

78. Bookmarks and Favorites

79. Reading History (e.g., eBooks, articles)

80. Travel History (e.g., flight bookings, hotel stays)

Sensor Data

81. Accelerometer

82. Gyroscope

83. Magnetometer

84. Proximity Sensor

85. Ambient Light Sensor

86. Barometer

87. Heart Rate Monitor

88. Step Counter

89. Temperature Sensor

90. Humidity Sensor

User Preferences and Settings

91. Language Preferences

92. Accessibility Settings

93. Notification Preferences

94. Theme and Display Settings

95. Do Not Disturb Settings

96. Keyboard Settings

97. Privacy Settings

Behavioral Data

98. Typing Patterns

99. Touch Pressure

100.?Scroll Speed

101.?App Installation and Uninstallation Patterns

102. Content Interaction (e.g., video watch time)

103.?Haptic Feedback Patterns

104.?Handwriting Data (from stylus use)?

Authentication and Security Data

105.?Passwords

106.?PIN Codes

107.??Biometric Data (e.g., fingerprints, face recognition)

108.?Two-Factor Authentication Data

109.?Security Questions and Answers

110.?Access Logs (login attempts, IPs)

Advertising and Analytics Data

111.? Ad Clicks and Impressions

112. User Interests and Demographics

113.?Purchase Behavior

114.?Ad Preferences

115. Third-Party Tracking Data

116.?Affiliate and Referral Data

Miscellaneous Data

117.??Voice Commands

118.?Feedback and Reviews

119.?Support and Inquiry Records

120.?Survey Responses

121.?User Generated Content (e.g., forum posts, comments)

122.?Virtual Assistant Interactions (e.g., Siri, Google Assistant)

123.?Custom Shortcuts and Automations

124.?Usage of Smart Home Devices

125.?Wearable Device Data

126.?Vehicle Data (from connected car apps)

Scenario 1:

Twin is browsing social media, enters comments as the human would have. responds to comments too.

Incoming chat, twin responds. Do not forget to bring milk on the way home. Twin would reply, ok. do we also need bread. as this is the typical sequence many times before. A notice pops up later when the car starts reminding the human to pick up the bread and milk that have already been ordered.

Twin asked to buy pants. Twin will shop many online shops and places the order. Size, colour, style already known from the history of purchases.