sabotaging – Earlybirds Invest

The Promise of Stablecoins for Europe

Stablecoins are digital money on blockchains – dollars, euros, or sterling as cryptographic coins. They are the new “killer app” of fintech, programmable cash which moves peer-to-peer without intermediaries – instantly at virtually no cost – powering global payments and applications such as automated lending and securities trading.

Stablecoins allow fintechs to build new applications faster and cheaper than ever before. They enable “open banking on steroids” twice over by unbundling money from banks, payment providers, and their closed, proprietary fintech technologies. They are “room-temperature superconductors for financial services” which remove barriers to the flow of money, significantly boosting GDP.

Stablecoins are more than an abstract financial innovation. They let a Polish worker in France send their euros home instantly for cents instead of paying several euros and waiting up to two days. They enable German start-ups to raise capital efficiently through automated issuance of compliant digital shares and debt instead of slow, expensive, and inflexible manual paperwork.

To unlock the potential of stablecoins, Europe’s currencies must be accessible domestically and internationally as euros, zloty, and krona onchain. The good news is that Europe has a tried and tested legal framework for digital cash called e-money, introduced in 2000. The bad news is that Europe has hobbled itself by wrapping e-money issued onchain with a thick layer of unnecessary red tape.

How MiCA Creates Unfair Barriers for Innovation

E-money is a terrific regulatory innovation. It is a digital cash bearer instrument for payments. Dozens of companies, including PayPal, Revolut, and Wise, have successfully used e-money to serve millions of customers in billions of online, mobile and card transactions. E-money is the ultimate form of stablecoin, as if made for the onchain economy.

The newly passed EU Market in Crypto-Assets regulations (MiCA) require stablecoins to be e-money. This makes a lot of sense because e-money pre-dates blockchains and MiCA as a “technically neutral” form of digital cash.

However, MiCA violates the technical neutrality of e-money and imposes tariffs and anti-competitive restrictions by creating additional requirements for e-money onchain.

For example, MiCA turns banks into gatekeepers for issuers of e-money onchain. Unlike regular e-money which can be 100% safeguarded directly in high-quality liquid assets such as government bonds, MiCA requires stablecoin issuers to safeguard at least 30% of their customers’ funds with banks, requiring them to share their income with the banks. That’s a direct tariff payable to the banks.

The MiCA bank safeguarding requirement also makes e-money onchain more risky because it inserts the banks and their balance sheets where they need not be. The higher risk of holding money with banks is a tariff because it requires e-money issuers to hold larger reserves.

The MiCA bank safeguarding requirement is also illegal. It directly violates the European e-money directive which explicitly states that one of its key goals is to ensure “fair competition” and a “level playing field” between e-money issuers and banks. The MiCA bank safeguarding requirement does exactly the opposite: it shifts the playing field in favor of the banks.

Leveling the Playing Field

Americans like bashing European regulations and have no stablecoin regulations in place. Nevertheless, the Trump administration has prioritized passing a stablecoin bill mirroring European e-money to “ensure American dollar dominance internationally [and] to increase the usage of the US dollar digitally”.

Meanwhile, the EU is hobbling itself by making the tried and tested e-money regulations more anti-competitive, costly, and risky for European stablecoins. Like Draghi says: “A fundamental change in mindset” is needed.

The solution is simple. Firstly, the EU should remove all the blockchain specific requirements for e-money and rip the unnecessary red tape out of the otherwise mostly sensible MiCA regulations.

Secondly, the ECB (and other EU central banks) should further level the playing field between banks and e-money issuers.

How? The ECB has recently granted non-bank fintechs, including e-money issuers, direct access to ECB payment systems. This helps e-money issuers by giving them direct access to the same core payment systems as the banks.

The ECB should take one more step and give e-money issuers direct access to its safeguarding facilities. Leading IMF economists have already proposed this idea. That would remove all unnecessary gatekeepers and tariffs between the ECB and the issuers of euro stablecoins and help unlock the full potential of the onchain economy for Europe and the euro.

The following is a guest post and opinion from Ahmad Shadid, Founder of O.xyz.

Under the flimsy pretext of efficiency, the Department of Government Efficiency (DOGE) is gutting its workforce. An independent report suggests that DOGE has slashed around 222,000 job cuts in March alone. The cuts are hitting hardest in areas where the U.S. can least afford to fall behind — artificial intelligence and semiconductor development.

Now the bigger question is beyond gutting the workforce – it is that Musk’s Department of Government Efficiency is using artificial intelligence to snoop through federal employees’ communications, hunting for any whiff of disloyalty. It is already creeping around the EPA.

DOGE’s AI-first push to shrink federal agencies feels like Silicon Valley gone rogue—grabbing data, automating functions, and rushing out half-baked tools like the GSA’s “intern-level” chatbot to justify cuts. It’s reckless.

Besides that, according to a report — DOGE “technologists” are deploying Musk’s Grok AI to monitor Environmental Protection Agency employees with plans for sweeping government cuts.

Federal workers, long accustomed to email transparency due to public records laws, now face hyper-intelligent tools dissecting their every word.

How can federal employees trust a system where AI surveillance is paired with mass layoffs? Is the United States quietly drifting towards a surveillance dystopia, with artificial intelligence amplifying the threat?

AI-Powered Surveillance

Can the AI model trained on government data be trusted? Besides that, using AI into a complex bureaucracy invites classic pitfalls: biases—issues GSA’s own help page flags without clear enforcement.

The increasing consolidation of information within AI models poses an escalating threat to privacy. Besides that, Musk and DOGE are also violating the Privacy Act of 1974. The Privacy Act of 1974 came into effect during the Watergate scandal which aimed to curb the misuse of government-held data.

According to the act — no one, not even the special government employees—should access agency “systems of records” without proper authorization under the law. Now the DOGE seems to be violating the privacy act in the name of efficiency. Is the push for government efficiency worth jeopardizing Americans’ privacy?

Surveillance isn’t just about cameras or keywords anymore. It’s about who processes the signals, who owns the models, and who decides what matters. Without strong public governance, this direction ends with corporate-controlled infrastructure shaping how the government operates. It sets a dangerous precedent. Public trust in AI will weaken if people believe decisions are made by opaque systems outside democratic control. The federal government is supposed to set standards, not outsource them.

What’s at stake?

The National Science Foundation (NSF) recently slashed more than 150 employees, and internal reports suggest even deeper cuts are coming. The NSF funds critical AI and semiconductor research across universities and public institutions. These programs support everything from foundational machine learning models to chip architecture innovation. The White House is also proposing a two-thirds budget cut to NSF. This wipes out the very base that supports American competitiveness in AI.

The National Institute of Standards and Technology (NIST) is facing similar damage. Nearly 500 NIST employees are on the chopping block. These include most of the teams responsible for the CHIPS Act’s incentive programs and R&D strategies. NIST runs the US AI Safety Institute and created the AI Risk Management Framework.

Is DOGE Feeding Confidential Public Data to the Private Sector?

DOGE’s involvement also raises a more critical concern about confidentiality. The department has quietly gained sweeping access to federal records and agency data sets. Reports suggest AI tools are combing through this data to identify functions for automation. So, the administration is now letting private actors process sensitive information about government operations, public services, and regulatory workflows.

This is a risk multiplier. AI systems trained on sensitive data need oversight, not just efficiency goals. The move shifts public data into private hands without clear policy guardrails. It also opens the door to biased or inaccurate systems making decisions that affect real lives. Algorithms don’t replace accountability.

There is no transparency around what data DOGE uses, which models it deploys, or how agencies validate the outputs. Federal workers are being terminated based on AI recommendations. The logic, weightings, and assumptions of those models are not available to the public. That’s a governance failure.

What to expect?

Surveillance doesn’t make a government efficient, without rules, oversight, or even basic transparency, it just breeds fear. And when artificial intelligence is used to monitor loyalty or flag words like “diversity,” we’re not streamlining the government—we’re gutting trust in it.

Federal workers shouldn’t have to wonder if they’re being watched for doing their jobs or saying the wrong thing in a meeting.This also highlights the need for better, more reliable AI models that can meet the specific challenges and standards required in public service.