Decentralized Data: have your cake and eat it too.

By the year 2033, there are several things I expect to see, and several that I hope to see.

Data privacy & encryption mechanisms are maturing.

The emergence of information capitalism makes the creation of user data protection solutions necessary. A method for sharing just the data people choose to share—rather than all of their information—must be developed.

Blockchain is a reliable solution for the required security and privacy of information exchange, but raw data exposure is a disadvantage. As a consequence, Zero Knowledge Proof (ZKP) has become one of the most often used strategies for guaranteeing transaction anonymity.

ZKP is a cryptographic technique that, at its most basic level, allows one party to verify its identity to another without having to reveal the identifying data itself. You only prove your truthfulness - or your qualification to move from point A to point B.

Federated Learning allows smart devices to develop a common prediction model while maintaining all training data on device, divorcing machine learning from cloud storage. This goes beyond local model predictions on smart devices by bringing model training to the device.

Your smart device gets the current model, improves it using data from your smart devices, and then updates it. This model update is encrypted and transferred to the cloud, where it is averaged with other user changes to enhance the shared model. No updates or training data are saved on the cloud.

Smart devices tailor the model to your use (A). After aggregating several users' modifications (B), a consensus change (C) is made to the common model (C). Federated Learning ensures privacy, sharper models, reduced latency, and less power use. The upgraded model on your smart devices may also be utilized instantly to power customised experiences based on how you use them.

On-device training utilizes TensorFlow. Careful scheduling ensures training only occurs while the device is idle, plugged in, and on a free wifi connection, so it doesn't affect performance. Federated Learning is only used when it won't affect your experience. The system must then securely, efficiently, scalable, and fault-tolerantly transmit and aggregate model changes.

Distributed Ledger Technology (DLT) refers to the protocols and associated architecture that enable computers in various places to synchronize transactions and data across a network. A distributed ledger is a shared record of activities across several computers.

Such ledgers are utilized by companies (e.g. grocery chains) with branches or offices in many countries. In a conventional distributed database, a system administrator performs crucial activities to preserve ledger consistency. The system administrator updates and shares a master copy of the ledger with all network participants.

Bitcoin and Ethereum, two DLT-based platforms, operate without a trusted authority. Bitcoin uses consensus-based validation and cryptographic signatures to create a decentralized database. Peer-to-peer transactions are broadcast to all participants, who verify them in "blocks." This sort of DLT is called "blockchain technology" because the ledger is organized into independent but linked blocks.

Changes

New connections are being made between people, governments, and companies already. Blockchain and ZKPs have the ability to significantly transform how individuals, organizations, and governments interact in the near future. Zero-knowledge proof may be used to authenticate people, institutions, transactions, supply chains, etc - without revealing any more information. Users no longer need to depend on trust. ZKP can be used to replace passwords, as well as to secure mobile networks, and Internet of Things (IoT) devices & ecosystems.

This raising of the cybersecurity baseline for any systems built atop Distributed Ledger Technology generally, and Proof-of-Stake specifically - along with the increase of access to the majority of both developed and emerging markets will dramatically impact our global economy.

10 Year Vision

• Medical Research: licensing one's health, behavioral, and consumptive data - protected by ZkProof data treatment and leveraged by privacy & efficiency-centric federated learning mechanisms and ML model markets - has the potential to produce an emergent universal basic income (UBI) by making the truly anonymized and fully permission-controlled data available to medical researchers - currently paying as much as $1M per medical record due to the scarce supply and high friction modes of access. This unprecedented availability of protected but research-ready health records can only accelerate the pace of medical discovery and science - yielding better quality and quantity of life. BioNFTs are an experimental path into this space, currently underway.
• Alternative Data & IP markets and use cases: Beyond medical research, the commodification and security of data is entering its next generation via the multiplicity of smart contract configurations to tokenize and protect: intellectual property, business intelligence, human and social / market data with unprecedented encryption access, onramps to publish, and genealogical mechanisms for attribution and remuneration.
• Carbon-neutral data: By reducing data duplication to 1:1 and applying server farms to more productive purposes, we can achieve a carbon-neutral data footprint - vs the nearly 20% of all carbon being emitted from inefficient tech stacks today. Further, if we swap server farms throughout the country with housing, local manufacturing, and vertical farming - the most significant source of carbon emissions - transportation - can be significantly reduced -- but only if those server farms are rendered unnecessary.
• Data DAOs, Personal IP & ZKP KYC: A decentralized data stack support decentralized and fluid talent pools that can replace most W2s with Wallet-to-Wallet smart contractor agreements. Further, we can imagine an evolution of professional collaborations with an eye toward the minting and licensing of IP on the individual level - allowing for independent production of models, methods, networks, and engineering - available for global licensing, permissioned by the producer's specifications (ie. ZKP KYC validated use cases - and elimination of usage for ends not specified or desired).
• Augmented Discovery > Interruptive Advertising: Part of the reason advertising is more often than not inaccurately targeted, and interruptively served - is because, for the most part, we apply learnings on (poorly stewarded, almost never proactively consented) data in a slow and expensive, one-size-fits-all fashion. By onboarding global data scientists and markets for machine learning models that can be reactively deployed with feedback loops as fast as TikTok's feed algorithm. We can imagine tools and services being presented to us exactly as we would best benefit and augment our experiences - with data training and personalized as we can achieve with a mature decentralized data stack.

There's much, much more potential here, to be made clear as global innovators join the discussion and ability to contribute & participate directly.

Dominos

What needs to happen in order to realize this piece of the 'mature decentralization' vision? What is likely to happen between now and then, and across what critical milestones?

3 Years

Frontier Adoptors: The early adoptors of Federated Learning and Zero-Knowledge data treatment, brokerage, and licensing will be those that [1] have greater capacity for the adoption of leapfrog technology - ie, less existing infrastructure; and [2] the transaction cost of adoping high friction, early ux solutions is less than the gain from baseline DLT adoption like [a] self-sovereign banking; [b] mesh and IoT networked infrastructure; [c] privacy and agency securing data licensing opportunities for supplementary income.

6 Years

SME - The Next Generation Market: The UX and early stage systems have matured to the point where adoption nears ubiquity to the same level social media did at around the same year mark. Major web2 platforms begin moving data, financial, marketing, and even operational systems to distributed ledger technology - without breaking their ESG mandates, and keeping compliant in an environment with consumer protections only continue to increase beyond the scope of terms and conditions via 'dumb contracts' alone.

9 Years

Institutional Adoption at Scale: As municipalities scale digital central banking currencies from the municipal to the national level - regulatory frameworks, beyond the frontier special economic zones, are bound to catch up. It will become impossible to operate a public company or municipal budget by pinkie-promise and excel files as law and constituent parties demand immutable, trustless, censorship & therefore falsification-proof accounting and compliance.