More on the theme of “using AI to prove data is not generated by AI”. Rather than away from strategies with that particular focus, I intend to create a towards strategy for the value and lifespan of human-generated data.  Here is a new podcast from my writings for the Human DataBit and the associated ecosystem using NotebookLM.

The LLM generated a fascinating conversation from my notes. I specifically like how the generated content from my work, discusses the key concepts of the ecosystem. The conversation covers a lot of ground on the subjects that I am presenting in a format that makes sense to me. It creates a nicely directed conversational flow about my ideas.

AI is a ubiquitous presence in nearly every aspect of our individual lives. Technology is moving faster than most people can process, understand, or develop deep knowledge experiences. The ecosystem creates Engagement, Education, and Enculturation for everyone participating in the emerging data-value economy.

Please listen and enjoy the conversation and let me know what you think.

https://www.youtube.com/watch?v=v9iSJ3EHe1k

Audio and notes generated using NotebookLM from original content developed and produced by a human being.

NOTES:

Main Theme: This conversation explores the concept of the Human DataBit (HDB) and the Holographic Patent Office (HPO) as solutions for establishing provenance and ownership of human-generated data in the age of AI and Web3.

Key Ideas and Facts:

Ambient General Intelligence: The rise of ambient general intelligence, driven by Web3, IoT, and AI, necessitates new frameworks for managing vast amounts of data, particularly those generated by humans.

The Human DataBit (HDB): The HDB aims to identify and label data created by biological intelligence at its source, establishing clear attribution and ownership. This concept draws parallels with “SynthID” for AI-generated content and the “Quantified Self” movement.

“The Human DataBit (HDB) is the entry point for the economies of the minds to gather and engage in creating the methods to identify biologically generated data at the point of creation.”

Holographic Patent Office (HPO): The HPO envisions a user-centric platform built on open-source principles where individuals can manage and control their HDB-labeled data. This platform would enable Data Ownership and Control: Empowering individuals to own their data and dictate its use.

Licensing and Monetization: Allowing users to license their data with granular precision and potentially benefit financially.

Community Building: Fostering an online community for developers, creators, and data enthusiasts to collaborate and innovate.

Quantum Patent Office (QPO): This concept explores the potential for managing the totality of a person’s data, extending ownership rights even beyond their lifespan.

Greek Mythology and Metaphor: The author leverages Greek mythology, specifically the Horae (goddesses of seasons and natural order), Moirai (Fates), and Erinyes (Furies) to illustrate different aspects of the HDB ecosystem:

Horae: Representing the HPO’s role as guardians of data order and natural flow.

Moirai: Reflecting on the concept of data destiny and the need to shape its trajectory.

Erinyes: Highlights the need for safeguards and ethical considerations to prevent data misuse.

Key Partnerships: The success of the HDB ecosystem relies on collaboration with:

AI & Machine Learning Experts: For developing algorithms for accurate human provenance identification.

Web 3 Developers & Infrastructure Providers: To integrate blockchain or DePIN solutions.

I have purposely avoided publishing any of my writings on the internet related to my project: The Human DataBit. Rather, I have chosen to publish meta-content generated by LLM-based AIs, trained from my original material. Mostly to avoid the insane web scraping that is feeding the LLM rush (see my post-https://www.linkedin.com/pulse/end-internet-toolifyai-ai-content-farms ). Second, to prove the point of Ambient General Intelligence & The Human DataBit (HDB), we need AI to prove what is and, what is not generated by AI.

I uploaded 40-50 pages of my notes on The HDB to Google’s NotebookLLM and used the deep dive conversation function to check out the feature. I must admit I was surprised by the output of the LLM, the conversation is weirdly interesting, and slightly engaging, and is the AI version of bad hype content. Better ways to sell you, Shaklee.

How much meta-content constitutes real content

It is bizarre to hear a two-way conversation about my ideas. Having an algorithm collate and organize a perspective and analysis of my writing and then discuss it, takes some getting used to it at first. It is sort of like the painter who turns the painting upside down and steps back to gain a new perspective, I guess. I did find a few ideas for how I can be clearer in my content.

As for the output by Google, it is cute, shallow, and syrupy in delivery with a bunch of circular and reductive statements, yet an impressive feat of technology. More important to me, is the input by me into the pantheon of data used for AI training. As I give new info to the LLMs from the original content, there is a meta-training that happens as a function of the “exchange”.

Overall, I am intrigued by the podcast content. It does a good basic job of explaining some of the content I uploaded. It has some value in planting the seeds into the data stream. I created a Soundcloud page and uploaded it as an introduction to The Human DataBit, along with other centralized systems. I watch the crawlers hit the website in the hours after posting anything to the data broker sites (LinkedIn, IG, FB, X, etc.),

The sum of most knowledge and content created before the current AI boom has been incorporated into the “training” of the models we now interact with as LLMs. Each interaction creates new paths of training information available to the AIs. AIs & Algorithms feed us content and each interaction we have with it creates new training data for the AIs/A’s, to feed us more content. Ruled by reductive (predictive) logic.

“In all chaos, there is a cosmos, in all disorder a secret order.” ― Carl Gustav Jung

The fabrication capacity of current AI models should serve as an alarm for everyone, awareness of this “brave new world” is an adaptive strategy. Being an informed consumer of content is now more important than at any other time in our history.

AI needs data. AGI needs even more data. As a species what differentiates artificial intelligence from biological intelligence is our ability to generate data the AI can’t. The ability to generate Curated & Quantified personal data is the new economy.

AI is ubiquitous and pervasive, AI driven Personal Data Strategies are a new territory and a new social-value, data-value economy. An economy based on using AI to prove what is, and is not created by biological intelligence. The value of data provenance and clear attribution for human personal data should be a basic right.

Quantity over quality/accuracy of AI remains to be improved and remember Artificial Super Intelligence is on the horizon.  For more details, please listen to the NotbookLLM deep dive conversation on Soundcloud. It provides an interesting perspective of The Human DataBit.

Link to SoundCloud

LinkedIn