CPThe Defense Against DeepFakes: Blue Checkmark with Decentralized ID
In today’s AMA on X.com, I was asked again about defending against deepfakes, particularly those posing as family members or colleagues to defraud unsuspecting people. While we may be unable to stop the creation of Taylor Swift deepfakes, we can build a defense against real-time or published content using blockchain technology. In my “Due Diligence in Web3” talk at ETH Denver 2024, I addressed the disinformation age, where generated content blurs the line between reality and fiction. I propos...
CPThe Contextual Knowledge Gap Theory (CKGT)
A Generative Framework for Closing Systemic Gaps in Learning, Work, Commerce, the Influencer Economy — and BeyondI. Introduction: Defining the Core SystemAt the heart of human inefficiency lies a systemic mismatch — not of access, but of alignment. We have more information than ever, yet the friction to apply it remains high. To understand why, we turn to systems thinking. In this view:Knowledge Gap is a stock — the accumulated deficit between what someone knows and what they need to know to ...
Creator of Molecule Protocol, Credit3, and Claimable.
CPThe Defense Against DeepFakes: Blue Checkmark with Decentralized ID
In today’s AMA on X.com, I was asked again about defending against deepfakes, particularly those posing as family members or colleagues to defraud unsuspecting people. While we may be unable to stop the creation of Taylor Swift deepfakes, we can build a defense against real-time or published content using blockchain technology. In my “Due Diligence in Web3” talk at ETH Denver 2024, I addressed the disinformation age, where generated content blurs the line between reality and fiction. I propos...
CPThe Contextual Knowledge Gap Theory (CKGT)
A Generative Framework for Closing Systemic Gaps in Learning, Work, Commerce, the Influencer Economy — and BeyondI. Introduction: Defining the Core SystemAt the heart of human inefficiency lies a systemic mismatch — not of access, but of alignment. We have more information than ever, yet the friction to apply it remains high. To understand why, we turn to systems thinking. In this view:Knowledge Gap is a stock — the accumulated deficit between what someone knows and what they need to know to ...
Creator of Molecule Protocol, Credit3, and Claimable.
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Your data is in the hands of Big Tech. They profit billions from you, and your choice is either to use their services or be left out. They keep the majority of the cut—also known as the “take rate”—and you’re lucky if you get any of the pie.
Moreover, your privacy is at their mercy. Why do such powerful Big Tech companies still experience breaches that irreversibly leak your social security, addresses, and other personal information? Have you ever been fairly compensated for mistakes they make, which only you suffer?
In the age of AI, they monetize not only your digital footprint but also your knowledge and expertise—of course, without compensating you. As we all anxiously await the next big release or the arrival of AGI, so do the lawyers from big IP owners. But who’s suing on your behalf?
Why are Big Tech companies problematic? Look at how some of the most powerful ones squeeze their supply chains (PDD, Shein, and Temu) and how gig-economy platforms exploit their workers (MeiTuan and Uber). Also, consider how big platforms have the power to manipulate public information (Meta and TikTok).
“Centralized AI in the hands of Big Tech could lead them to build the most powerful and dangerous tool for controlling humanity ever built. Big Tech already does deeply concerning things, and great things too, but imagine Big Tech, social networks of today, knowing everything about you and everything about everything else and continuing to have the profit motive or a power motive as primary. So the bigger AI projects of the future must be built as largely open source, transparently built, and with decentralized governance, and hopefully with decentralized mechanisms for sourcing data, for compute, for storage.” — Joe Lubin, Co-founder of Ethereum and founder and CEO of ConsenSys, Edcon 2024
To build the transparent AI project that Joe Lubin suggests, we first need to figure out how to reclaim ownership of our data. Before we do that, let’s look at the types of data and how we should own our data.
There are many types of data and many ways to categorize them. Here are the four types of data I’ve identified, which I first presented in July 2024 at Edcon.
Proprietary Data includes any data you create, such as social media posts, diary entries, notes, or content you produce within a company. This also includes first-party data—the data you provide to research institutions, publicly or anonymously. This is where Big Tech profits from you in the AI era.
Behavioral Data includes your browsing history, map records, health device data, metadata from your photos, in-game behavior, etc. Big Tech capitalizes on this data by pushing targeted ads to you or selling your personal data to entities that profile you as potential targets.
Verifiable Credentials are data about you, such as your government-issued identity, passport, birth certificate, diploma, Olympic medals, course completion certificates, etc. Typically, entities pay issuers to verify this data.
Derivative Data includes stories generated from your map data or photos, personalized interpretations of your health data through aggregation and benchmarking, your financial risk profile (a.k.a. credit scores), etc. This is where we usually pay to obtain insights.
While I would typically dive into the technical implementation details of achieving data ownership for each type of data—which I intend to do in separate articles—there are more important and simple steps that every one of us can take.
Here are FOUR (4) clear and simple steps to follow:
Aware —> Act —> Migrate —> Own
Aware: Recognize how you’ve been exploited and the urgency of reclaiming ownership of your data.
Act: Demand that existing platforms grant you access to your own data and provide export options.
Migrate: Support and use decentralized services or apps that allow you to retain control over your data and offer a fair “take rate.” Back the (nascent) decentralized platforms that are available or coming soon.
Own: Consciously take ownership of your data and only use services that respect your data rights and offer fair financial splits.
References
Your data is in the hands of Big Tech. They profit billions from you, and your choice is either to use their services or be left out. They keep the majority of the cut—also known as the “take rate”—and you’re lucky if you get any of the pie.
Moreover, your privacy is at their mercy. Why do such powerful Big Tech companies still experience breaches that irreversibly leak your social security, addresses, and other personal information? Have you ever been fairly compensated for mistakes they make, which only you suffer?
In the age of AI, they monetize not only your digital footprint but also your knowledge and expertise—of course, without compensating you. As we all anxiously await the next big release or the arrival of AGI, so do the lawyers from big IP owners. But who’s suing on your behalf?
Why are Big Tech companies problematic? Look at how some of the most powerful ones squeeze their supply chains (PDD, Shein, and Temu) and how gig-economy platforms exploit their workers (MeiTuan and Uber). Also, consider how big platforms have the power to manipulate public information (Meta and TikTok).
“Centralized AI in the hands of Big Tech could lead them to build the most powerful and dangerous tool for controlling humanity ever built. Big Tech already does deeply concerning things, and great things too, but imagine Big Tech, social networks of today, knowing everything about you and everything about everything else and continuing to have the profit motive or a power motive as primary. So the bigger AI projects of the future must be built as largely open source, transparently built, and with decentralized governance, and hopefully with decentralized mechanisms for sourcing data, for compute, for storage.” — Joe Lubin, Co-founder of Ethereum and founder and CEO of ConsenSys, Edcon 2024
To build the transparent AI project that Joe Lubin suggests, we first need to figure out how to reclaim ownership of our data. Before we do that, let’s look at the types of data and how we should own our data.
There are many types of data and many ways to categorize them. Here are the four types of data I’ve identified, which I first presented in July 2024 at Edcon.
Proprietary Data includes any data you create, such as social media posts, diary entries, notes, or content you produce within a company. This also includes first-party data—the data you provide to research institutions, publicly or anonymously. This is where Big Tech profits from you in the AI era.
Behavioral Data includes your browsing history, map records, health device data, metadata from your photos, in-game behavior, etc. Big Tech capitalizes on this data by pushing targeted ads to you or selling your personal data to entities that profile you as potential targets.
Verifiable Credentials are data about you, such as your government-issued identity, passport, birth certificate, diploma, Olympic medals, course completion certificates, etc. Typically, entities pay issuers to verify this data.
Derivative Data includes stories generated from your map data or photos, personalized interpretations of your health data through aggregation and benchmarking, your financial risk profile (a.k.a. credit scores), etc. This is where we usually pay to obtain insights.
While I would typically dive into the technical implementation details of achieving data ownership for each type of data—which I intend to do in separate articles—there are more important and simple steps that every one of us can take.
Here are FOUR (4) clear and simple steps to follow:
Aware —> Act —> Migrate —> Own
Aware: Recognize how you’ve been exploited and the urgency of reclaiming ownership of your data.
Act: Demand that existing platforms grant you access to your own data and provide export options.
Migrate: Support and use decentralized services or apps that allow you to retain control over your data and offer a fair “take rate.” Back the (nascent) decentralized platforms that are available or coming soon.
Own: Consciously take ownership of your data and only use services that respect your data rights and offer fair financial splits.
References
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