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filThe Art of Forecasting
Comparing Polymarket and prediction markets with traditional public opinion channels.Polymarket has emerged as a rising star in consumer crypto, especially driven by the upcoming U.S. presidential election and the related events. Many crypto experts have praised Polymarket’s success in achieving product-market fit, notably without relying on tokens or external incentives. As of this writing, Polymarket has once again hit an all-time high in daily and monthly active users, as well as in daily ...
filPolymarket’s Post-Election Resilience
The 2024 US elections were not just a pivotal moment in American politics—they also became a defining catalyzer for Polymarket, the most successful blockchain-based prediction market. In the lead-up to November 5th, Polymarket experienced an unprecedented surge in activity, with its main election market and numerous secondary markets fueling a meteoric rise in user engagement and trading volumes. Some anticipated a steep and definitive decline following the resolution of these election-relate...
filThe Future of Blockchain: Modular Design and Intent-Based Systems
ModularityBlockchain technology is undergoing a significant shift - transitioning from the monolithic model, where a single blockchain handles all functions including execution, consensus, settling, and data availability (as seen in Ethereum), to a modular design. This paradigm envisions a plug-and-play architecture, where each component of the blockchain stack is outsourced to a marketplace of third-party providers, enabling different blockchains to combine distinct elements for various func...
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filThe Art of Forecasting
Comparing Polymarket and prediction markets with traditional public opinion channels.Polymarket has emerged as a rising star in consumer crypto, especially driven by the upcoming U.S. presidential election and the related events. Many crypto experts have praised Polymarket’s success in achieving product-market fit, notably without relying on tokens or external incentives. As of this writing, Polymarket has once again hit an all-time high in daily and monthly active users, as well as in daily ...
filPolymarket’s Post-Election Resilience
The 2024 US elections were not just a pivotal moment in American politics—they also became a defining catalyzer for Polymarket, the most successful blockchain-based prediction market. In the lead-up to November 5th, Polymarket experienced an unprecedented surge in activity, with its main election market and numerous secondary markets fueling a meteoric rise in user engagement and trading volumes. Some anticipated a steep and definitive decline following the resolution of these election-relate...
filThe Future of Blockchain: Modular Design and Intent-Based Systems
ModularityBlockchain technology is undergoing a significant shift - transitioning from the monolithic model, where a single blockchain handles all functions including execution, consensus, settling, and data availability (as seen in Ethereum), to a modular design. This paradigm envisions a plug-and-play architecture, where each component of the blockchain stack is outsourced to a marketplace of third-party providers, enabling different blockchains to combine distinct elements for various func...
Share Dialog
Share Dialog
The transformative landscape of AI, set to contribute $15 trillion to the global GDP by 2030, presents a complex web of interconnected issues like data access, compensation, and evolving work dynamics. As we disentangle it and analyze each component, a logical progression unfolds that ultimately underscores blockchain potential in addressing data utility, individual economic value, and ownership.
Data utility (1): Data is the new oil, as it’s become the most important resource to power our technology and economies. For over a decade, companies have been hunting for as much data as possible to maximize profit from ad monetization. This process was almost seamless since users voluntarily give away their data whenever they sign in for a new application or service. With AI, companies’ hunger for more data as raw material/fuel for AI models has been getting more voracious, and even more than before, it’s happening without data creators’ approval. The New York Times suing ChatGPT for utilizing thousands of its articles without permission underscored the necessity of establishing consent and attribution in data usage for AI training purposes.
Data Utility (2): Balancing privacy with the desire to harness value from one's data is a crucial consideration. While safeguarding privacy remains non-negotiable, there is a potential pitfall wherein individuals, in their pursuit of privacy preservation, may overlook the strategic and purposeful management of their data assets. Data, unlike oil, increases value as it is shared and used. Whether contributing to AI dataset training, supporting marketing initiatives, or aiding pharmaceutical research, individuals should aspire to extract value while upholding privacy and maintaining control over their personal information. Recognizing that an open data flow can yield tangible benefits that enhance individuals' lives is essential.
The transformative landscape of AI, set to contribute $15 trillion to the global GDP by 2030, presents a complex web of interconnected issues like data access, compensation, and evolving work dynamics. As we disentangle it and analyze each component, a logical progression unfolds that ultimately underscores blockchain potential in addressing data utility, individual economic value, and ownership.
Data utility (1): Data is the new oil, as it’s become the most important resource to power our technology and economies. For over a decade, companies have been hunting for as much data as possible to maximize profit from ad monetization. This process was almost seamless since users voluntarily give away their data whenever they sign in for a new application or service. With AI, companies’ hunger for more data as raw material/fuel for AI models has been getting more voracious, and even more than before, it’s happening without data creators’ approval. The New York Times suing ChatGPT for utilizing thousands of its articles without permission underscored the necessity of establishing consent and attribution in data usage for AI training purposes.
Data Utility (2): Balancing privacy with the desire to harness value from one's data is a crucial consideration. While safeguarding privacy remains non-negotiable, there is a potential pitfall wherein individuals, in their pursuit of privacy preservation, may overlook the strategic and purposeful management of their data assets. Data, unlike oil, increases value as it is shared and used. Whether contributing to AI dataset training, supporting marketing initiatives, or aiding pharmaceutical research, individuals should aspire to extract value while upholding privacy and maintaining control over their personal information. Recognizing that an open data flow can yield tangible benefits that enhance individuals' lives is essential.
Individual Economic Value: Although AI has the potential to empower individuals, it also poses the risk of accelerating unemployment and exacerbating social inequality. According to MIT Sloan School of Management professor Erik Brynjolfsson, technological advancement has led to productivity growth without a proportional increase in employment or income, a trend accelerated by AI. While there is disagreement among experts about whether AI will lead to mass unemployment, there is a growing consensus that it will worsen social inequality. This could occur through the displacement of middle-class jobs and the erosion of median income.
The potential loss of jobs places individuals at risk of diminished economic value. This matters because preserving citizens' economic value has been a driving force behind societal reforms throughout history. For instance, social welfare programs were introduced in Bismarck's Germany partly to ensure a robust and capable workforce and military. The absence of economic value may diminish the governments’ incentive to implement such policies, potentially ushering in a cyberpunk dystopia where private corporations wield significant power while governments play a marginal role.
Proving Ownership (1): In such a scenario, citizens' economic worth may be reduced to the value of the data they generate. To harness this value, however, it’s key that individuals can prove and exercise ownership over them. To address these concerns, data trusts emerged as a system and legal entity designed to manage individuals' data on their behalf. This approach aimed to safeguard data ownership, making it easier for individuals to retain control over their digital footprint and extract value from them.
Proving Ownership (2): However, as technology advances, a more robust solution has come to the forefront—blockchain technology. Blockchain not only satisfies the fundamental functionalities of data trusts but also provides a superior infrastructure that ensures data ownership, privacy, and full control. By establishing an open, transparent, and trustless data ledger and marketplace, blockchains solve the attribution problem by establishing a clear and transparent proof of ownership. Smart contracts replace third-party middlemen and become the enforcers of data agreements, ensuring users maintain complete control over their data. Furthermore, thanks to technologies like encryption and zero-knowledge proof, users can decide whether and under what conditions they wish to sell their data without revealing anything about it. This revolutionary system can streamline the data-sharing process, allowing individuals to systematically share and sell their data at a granular level with selected parties, all under their specified terms and conditions while preserving full control.
By capturing economic value and redistributing it to data providers, blockchain creates a robust financial instrument acting like a universal basic income, reducing the need for taxation or reliance on a welfare state and mitigating economic inequalities stemming from AI-driven transformation. Speaking about AI, data ownership, and value, Chris Dixon wrote in his recently released book Read Write Own:
in the long run, we are still going to need an economic covenant between AI systems and content providers. Al will always need new data to stay up to date. The world evolves: tastes change, new genres emerge, things get invented. There will be new subjects to describe and represent. The people who create content that feeds AI systems will need to be compensated.
Just in the same days, Jacob from Zora wrote a compelling article echoing this idea:
AI is a fundamental breakthrough technology, and with that comes disruption of incumbent systems. However, when paired with crypto that disruption can very well be a massively positive unlock in value capture for a lot of the entities it is disrupting.
Ocean Protocol is an open-source protocol with the mission to spread the benefits of AI by equalizing the opportunity to access and monetize data. Ocean Protocol leverages a few primitives to enable on-ramp for data services into crypto ecosystems, which then any application can use. This composability enables crypto wallets to behave like data wallets, crypto exchanges as data marketplaces, DAOs as data coops, datatoken-backed stable assets, and more. Overall, Ocean protocol enables the monetization of private data while preserving privacy.
Víctor González et al. propose a Blockchain-based IoT Data Marketplace (BIDM) where Internet of Things (IoT) data producers and consumers can share data in a decentralised and trustworthy manner. In such a marketplace, owners of IoT infrastructures can expose the observations that their devices generate while retaining control over who accesses each observation and directly getting revenues according to the price they have set.
The Tony Blair Institute For Global Change recently proposed an NHS Data Trust to: “capitalise on the opportunities of health data. Owned and controlled by the NHS in collaboration with trusted external partners, the NHSDT would treat NHS data as a competitive asset whose value can be realised for the benefit of the public. This would involve providing anonymised data to research entities, including biotech companies, in return for financial profit that would then benefit our health service. A transparent governance model would ensure that our data remain safe and that NHSDT’s operations align with public-health objectives, not private capital’s.”
Besides adopting an off-chain and trusted architecture, this last application introduces a different method for realizing value for individuals. Instead of letting private companies purchase data directly from individuals, data generated within the public sector, like healthcare data, is here sold and monetized by the public sector itself. This allows the public sector to become self-sustaining, offering free and high-quality services to citizens and potentially reducing the need to pay taxes to fund these services. The attainment of this objective would be significantly enhanced through the use of blockchain and zero-knowledge technology, where citizens would have the option to participate, receiving a tax cut, or opt out, maintaining the existing taxation cost.
In contrast to the current scenario where users give up ownership and control of their data to a few corporations, or a scenario where data flow is halted for privacy reasons, and even a future where third-party middlemen manage and monetize data on individuals’ behalf, blockchain emerges as the most effective and fair solution for addressing concerns related to data privacy and usage. The unlock brought by blockchain would benefit individuals by ensuring fair economic compensation at one’s conditions; the private sector by opening up extensive data in an unprecedented categorized manner, enhancing data indexing and extraction efficiency; and the public sector as streamlined and straightforward access to vast datasets would expedite research and enhance the quality of public policy and governance.
Leaders in both private and public sectors can support the adoption of blockchain to reshape the future of data ownership and AI:
Explore Data Sharing Use Cases: Cultivate collaborations that leverage blockchain for secure data sharing, consumption and monetization.
Establish Blockchain Data Cooperatives: Utilize blockchain to create cooperatives within professional associations, trade unions, and smart cities, allowing members to collectively manage and monetize their data.
Enshrine Data Property Rights in Law: Recognize blockchain as a cornerstone for data property rights, emphasizing mutual ownership for a decentralized AI economy.
Create a Regulatory Framework for Blockchain Data Assets: Develop clear regulations allowing the tokenization of datasets as tangible assets, using blockchain to create new digital assets for data trusts that can be traded in regulated exchanges.
In conclusion, standing at the crossroads of AI, data, and society, blockchain emerges as the catalyst for a more inclusive, transparent, and user-centric approach to data ownership and consumption. By enabling open data flow while guaranteeing privacy and removing unnecessary intermediaries, blockchain lays the foundation for a future where individuals have greater control over their data, fostering a more equitable and collaborative AI-driven economy.
Individual Economic Value: Although AI has the potential to empower individuals, it also poses the risk of accelerating unemployment and exacerbating social inequality. According to MIT Sloan School of Management professor Erik Brynjolfsson, technological advancement has led to productivity growth without a proportional increase in employment or income, a trend accelerated by AI. While there is disagreement among experts about whether AI will lead to mass unemployment, there is a growing consensus that it will worsen social inequality. This could occur through the displacement of middle-class jobs and the erosion of median income.
The potential loss of jobs places individuals at risk of diminished economic value. This matters because preserving citizens' economic value has been a driving force behind societal reforms throughout history. For instance, social welfare programs were introduced in Bismarck's Germany partly to ensure a robust and capable workforce and military. The absence of economic value may diminish the governments’ incentive to implement such policies, potentially ushering in a cyberpunk dystopia where private corporations wield significant power while governments play a marginal role.
Proving Ownership (1): In such a scenario, citizens' economic worth may be reduced to the value of the data they generate. To harness this value, however, it’s key that individuals can prove and exercise ownership over them. To address these concerns, data trusts emerged as a system and legal entity designed to manage individuals' data on their behalf. This approach aimed to safeguard data ownership, making it easier for individuals to retain control over their digital footprint and extract value from them.
Proving Ownership (2): However, as technology advances, a more robust solution has come to the forefront—blockchain technology. Blockchain not only satisfies the fundamental functionalities of data trusts but also provides a superior infrastructure that ensures data ownership, privacy, and full control. By establishing an open, transparent, and trustless data ledger and marketplace, blockchains solve the attribution problem by establishing a clear and transparent proof of ownership. Smart contracts replace third-party middlemen and become the enforcers of data agreements, ensuring users maintain complete control over their data. Furthermore, thanks to technologies like encryption and zero-knowledge proof, users can decide whether and under what conditions they wish to sell their data without revealing anything about it. This revolutionary system can streamline the data-sharing process, allowing individuals to systematically share and sell their data at a granular level with selected parties, all under their specified terms and conditions while preserving full control.
By capturing economic value and redistributing it to data providers, blockchain creates a robust financial instrument acting like a universal basic income, reducing the need for taxation or reliance on a welfare state and mitigating economic inequalities stemming from AI-driven transformation. Speaking about AI, data ownership, and value, Chris Dixon wrote in his recently released book Read Write Own:
in the long run, we are still going to need an economic covenant between AI systems and content providers. Al will always need new data to stay up to date. The world evolves: tastes change, new genres emerge, things get invented. There will be new subjects to describe and represent. The people who create content that feeds AI systems will need to be compensated.
Just in the same days, Jacob from Zora wrote a compelling article echoing this idea:
AI is a fundamental breakthrough technology, and with that comes disruption of incumbent systems. However, when paired with crypto that disruption can very well be a massively positive unlock in value capture for a lot of the entities it is disrupting.
Ocean Protocol is an open-source protocol with the mission to spread the benefits of AI by equalizing the opportunity to access and monetize data. Ocean Protocol leverages a few primitives to enable on-ramp for data services into crypto ecosystems, which then any application can use. This composability enables crypto wallets to behave like data wallets, crypto exchanges as data marketplaces, DAOs as data coops, datatoken-backed stable assets, and more. Overall, Ocean protocol enables the monetization of private data while preserving privacy.
Víctor González et al. propose a Blockchain-based IoT Data Marketplace (BIDM) where Internet of Things (IoT) data producers and consumers can share data in a decentralised and trustworthy manner. In such a marketplace, owners of IoT infrastructures can expose the observations that their devices generate while retaining control over who accesses each observation and directly getting revenues according to the price they have set.
The Tony Blair Institute For Global Change recently proposed an NHS Data Trust to: “capitalise on the opportunities of health data. Owned and controlled by the NHS in collaboration with trusted external partners, the NHSDT would treat NHS data as a competitive asset whose value can be realised for the benefit of the public. This would involve providing anonymised data to research entities, including biotech companies, in return for financial profit that would then benefit our health service. A transparent governance model would ensure that our data remain safe and that NHSDT’s operations align with public-health objectives, not private capital’s.”
Besides adopting an off-chain and trusted architecture, this last application introduces a different method for realizing value for individuals. Instead of letting private companies purchase data directly from individuals, data generated within the public sector, like healthcare data, is here sold and monetized by the public sector itself. This allows the public sector to become self-sustaining, offering free and high-quality services to citizens and potentially reducing the need to pay taxes to fund these services. The attainment of this objective would be significantly enhanced through the use of blockchain and zero-knowledge technology, where citizens would have the option to participate, receiving a tax cut, or opt out, maintaining the existing taxation cost.
In contrast to the current scenario where users give up ownership and control of their data to a few corporations, or a scenario where data flow is halted for privacy reasons, and even a future where third-party middlemen manage and monetize data on individuals’ behalf, blockchain emerges as the most effective and fair solution for addressing concerns related to data privacy and usage. The unlock brought by blockchain would benefit individuals by ensuring fair economic compensation at one’s conditions; the private sector by opening up extensive data in an unprecedented categorized manner, enhancing data indexing and extraction efficiency; and the public sector as streamlined and straightforward access to vast datasets would expedite research and enhance the quality of public policy and governance.
Leaders in both private and public sectors can support the adoption of blockchain to reshape the future of data ownership and AI:
Explore Data Sharing Use Cases: Cultivate collaborations that leverage blockchain for secure data sharing, consumption and monetization.
Establish Blockchain Data Cooperatives: Utilize blockchain to create cooperatives within professional associations, trade unions, and smart cities, allowing members to collectively manage and monetize their data.
Enshrine Data Property Rights in Law: Recognize blockchain as a cornerstone for data property rights, emphasizing mutual ownership for a decentralized AI economy.
Create a Regulatory Framework for Blockchain Data Assets: Develop clear regulations allowing the tokenization of datasets as tangible assets, using blockchain to create new digital assets for data trusts that can be traded in regulated exchanges.
In conclusion, standing at the crossroads of AI, data, and society, blockchain emerges as the catalyst for a more inclusive, transparent, and user-centric approach to data ownership and consumption. By enabling open data flow while guaranteeing privacy and removing unnecessary intermediaries, blockchain lays the foundation for a future where individuals have greater control over their data, fostering a more equitable and collaborative AI-driven economy.
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