Ed3 Weekly Issue #198: Welcome to the Machine Economy
Blockchain and smart contract are helping use move towards autonomous sytems of operation
Hello blockchain enthusiasts,
We are starting the transition into what some have dubbed the “machine economy.” The financial ecosystem is made up not just of moving money, but also of moving trusted data.
While the last decade was about digitizing information, this next phase is about digitizing trust. In a machine economy, assets, from autonomous vehicles to the very buildings we stand in, become programmable. In addition to existing in the physical world, they also possess a digital identity that enables them to transact, verify their status, and interact with global capital markets in real time.
The idea for the “machine economy” came from Matthew Schneider (CEO of Building, Inc.) as part of one of our resources for this week, “Blockchain and Smart Infrastructure: Exploring Use Cases and Potential.” We chatted on LinkedIn, and he offered to share some more insights into where this idea came from.
Some of blockchain’s most important use cases are also the least understood. Faster payments through stablecoins are widely recognized; using cryptography to verify and preserve real-world data is not. Yet this second use case may matter more in the long run.
Financial systems are already efficient and well developed. The digital infrastructure behind real estate and the built environment is not. It remains fragmented, manual, and slow. Faster payments are helpful, but reducing back-office work, audits, and transaction timelines in real estate and infrastructure from months to weeks changes how projects actually get built.
Construction teams will move faster and capital will be put to work sooner. More buildings—where people live, work, and gather—can be completed, and at a higher standard. Real estate and infrastructure are long-lived systems. When they improve, the benefits compound over decades. That is the opportunity.
To bridge the gap between Matthew Schneider’s vision and the weekly resources, we need to show how this “Machine Economy” isn’t just a future concept—it’s already being built in classrooms, stock exchanges, and construction sites.
This transition requires a new kind of literacy, one that combines institutional finance with technical engineering. We are moving away from a world of manual ‘trust but verify’ toward a world of ‘verify then automate.
The following resources highlight this shift in real-time: from students managing live capital to global exchanges testing the limits of their legacy infrastructure
St. John’s University students learn about cryptocurrencies by managing blockchain fund
Why the New York Stock Exchange’s big blockchain plans might be pie in the sky
Blockchain and Smart Infrastructure: Exploring Use Cases and Potential
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📚 Education + Society
St. John’s University students learn about cryptocurrencies by managing blockchain fund
🔗 Offering immersive educational opportunities in investment management is “what we’re all about” at St. John’s University, said Chief Investment Officer Steven Keating. Read
📊 Markets + News
Why the New York Stock Exchange’s big blockchain plans might be pie in the sky
🔗 It came as big news last week when the NYSE announced it planned to implement a dramatic technology upgrade by putting thousands of stocks on the blockchain—a nod to the growing influence of the crypto industry, which is already selling tokenized versions of equities. Read
📈 Trends + Innovation
Blockchain and Smart Infrastructure: Exploring Use Cases and Potential
🔗 Blockchain technology is moving beyond cryptocurrency to reshape how cities manage contracts, verify materials, and maintain critical infrastructure records. Read
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🤿 Deep Dive
Is AI schooling the future of education — or a risky bet?
🔗 This CNN article explores AI-based schooling models like Alpha. These schools align closely with the “machine economy” by shifting focus away from human-led teaching. Instead, they prioritize the high-speed processing of trusted data and automated metrics.
Our world is already trending toward this model of verifying real-world progress to release capital. In these classrooms, AI tutors verify student mastery in real-time. This approach compresses years of academic work into high-efficiency, two-hour bursts. It treats learning as a series of programmable milestones. While software manages the critical path of knowledge, human “guides” oversee the system to provide motivation and support.
As the article shares, some families report “zombie-like” student burnout and a lack of independent verification. This highlights the tension between the machine economy offering unprecedented speed, but risking prioritizing systemic throughput over human needs. These schools are a live experiment in automated social infrastructure where we can see both the potential and the concern. Read
Thank you for stopping by for another issue of my newsletter on emerging technology in education. Link to all my work by checking out my website, or give me a follow on the X platform.