In another great newsletter, my friend Curt Buermeyer summarizes Peter Diamandis’s three-phase roadmap from AI labor disruption to post-scarcity abundance. I’ll be honest — I want to believe it. Curt and I agree that the next five years are going to be rough. But where he sees a ten-year arc bending toward something beautiful, I see a timeline that assumes robotic construction, autonomous transport, AI healthcare, and vertical farming all scale and democratize faster than any infrastructure transformation in human history. But here’s the thing about being a pessimist: often you’re wrong, and that is a beautiful thing. Curt’s optimism is grounded and honest, not naive, and Diamandis has a track record of being right about exponential curves before the rest of us could see them. So I’m bookmarking this roadmap not because I’m convinced, but because I hope like hell they’re right and I’m wrong.

Article Excerpt:

I believe we’re facing a reality where roughly 40% to 50% of white-collar jobs—the knowledge work that college students and recent grads have spent years studying for—will likely be displaced almost overnight.

Article Summary:

Curt Buermeyer’s latest Smash Your Thinking newsletter summarizes a roadmap by Peter Diamandis (XPRIZE founder, exponential tech evangelist) for navigating the AI-driven collapse of the labor market without also collapsing the social contract. The core argument: the AI disruption won’t look like the Industrial Revolution, which reshuffled the workforce over 150 years. This one is compressed into a decade, and there’s no adjacent sector to retrain into because AI is eating every sector simultaneously.

Diamandis lays out three phases. Phase 1 (2025–2028): the fracture. Jobs disappear, identities crater, and the proposed floor is a $3,000/month Universal Basic Income paired with a 32-hour workweek to keep people attached to purpose and social structure while the shock absorbs. Phase 2 (2028–2031): the automation dividend. AI companies have extracted enormous value from public infrastructure — our data, our research, our systems — and the public deserves a share. Think Alaska Permanent Fund, but for the robot economy. Phase 3 (2031–2035): the great deflation. Housing drops from $2,000/month to $600. Transport falls to $225. Food, energy, and healthcare trend toward near-zero marginal cost, driven by robotics, solar, autonomous fleets, and AI diagnostics.

Curt adds his own caveat: he’s skeptical the Phase 3 deflation happens as fast as Diamandis projects. Prices in housing, healthcare, and food have never actually gone down for normal people, and he’d bet the timeline slips. The actionable close is straightforward: share the roadmap, audit what you’d do with your time if survival wasn’t the point, and pressure policymakers to build the bridging mechanisms now — before “the Valley” between 2026 and 2031 turns into something uglier.

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The post Will AI Force US to Adopt Universal Basic Income? first appeared on Sevenelles.

Based on the podcast conversation below, I would now amend that to read “We are so fucked. We are so totally fucked. Or maybe only for a decade or so.“

The podcast is a VERY interesting glimpse into the future. I highly recommend giving it a listen.

Above: The Moonshots hosts join Andrew Yang to unpack AI’s explosive collision with politics – deepfakes weaponizing elections, UBI surging as job-killer abundance hits, and radical fixes like open voting for anyone from Cuban to Robbins – while plotting democracy’s entrepreneurial reboot.

The post Psssst… Wanna Glimpse Into Our Future? first appeared on Sevenelles.

In this article, Curt Buermeyer discusses how the traditional model of trading time for money is rapidly becoming obsolete due to AI-driven productivity gains. For over a century, hourly billing has been standard across professions, but the workplace is now shifting from “pay-per-hour” to “pay-per-problem-solved.”

The most vulnerable workers are those whose value is measured by presence rather than performance. When employers pay for time, they’re actively seeking automation solutions to eliminate those costs entirely.

The new paradigm focuses on “problems solved per dollar.” A marketing strategist using AI to create an excellent plan in two hours delivers the same value as a traditional team spending 100 hours—clients only care about the outcome, not the process.

To adapt, professionals must reframe their value around specific problems solved rather than hours worked. This requires identifying the 20% of work requiring human judgment, strategy, and empathy that AI cannot replicate, while using AI to handle routine tasks efficiently.

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The post The Death of the Billable Hour: Why Your Salary is at Risk in 2026 first appeared on Sevenelles.

We are so fucked. We are so totally fucked.

Usually, I follow that statement with, “but there is always hope.” Josh Tyrangiel’s article in The Atlantic leaves little room for hope, given the dysfunctional state of our democracy.

Here’s one of the many quotes from the article that paints a dire picture of AI’s impact on America’s working class:

“But I’m telling you it’s the end of America as we know it if we don’t use this moment to do things differently.”

Gina Raimondo

(former Rhode Island governor,
former US Commerce Secretary,
current venture-capital executive)

If you are fortunate enough to be in or nearing retirement with adequate savings to survive a major financial nut-punch, you can skip the article. For everyone else, read the article and plan ways to protect the family jewels.

Article Summary:

In 1869, Massachusetts created America’s first Bureau of Statistics of Labor to measure workplace conditions during the Industrial Revolution, establishing the principle that democratic governments should track what’s happening to their workers. Today, as artificial intelligence threatens to sodomize the American Dream, that commitment to measurement and evidence-based policymaking is being sorely tested.

While economists see no clear data yet showing AI’s impact on employment, corporate leaders are openly warning of massive job losses. CEOs from Ford, Anthropic, and other major companies have predicted that AI could eliminate 10-20% of jobs within years, with some estimating that half of white-collar positions could disappear within a decade. The scary part: after openly discussing these projections just a few months ago, executives have gone silent, advised by PR teams to stop talking publicly about AI and layoffs.

Economists remain divided on timing and severity. Some, like Federal Reserve Bank of Chicago President Austan Goolsbee, argue it’s too early to draw conclusions—productivity is strong and unemployment remains low. Others, like MIT’s David Autor and Daron Acemoglu, emphasize that speed matters: gradual change allows societies to adapt, but rapid disruption causes lasting damage, as seen with the “China shock” that devastated US manufacturing communities in the 1990s.

However, economist Anton Korinek warns this time may be different. Unlike previous technologies, AI can help deploy itself, potentially compressing decades of change into years. If 40% of global jobs are affected rapidly, as the IMF projects, our already hideously dysfunctional political institutions may not have the cajones to save the working class.

Our feckless Congress is paralyzed by fear of an authoritarian buffon, unable to even fund expanded labor statistics or revive worker retraining programs. In a classic “fox guarding the henhouse” move, the Trump administration has delegated AI oversight to venture capitalist David Sacks, who has hundreds of AI investments. Without political action, the challenge may ultimately be less about jobs than about whether our republic survives AI.

Article Excerpt:

“Mass job loss doesn’t just mean unemployment; it means missed loan payments, cascading defaults, shrinking consumer demand, and the kind of self-reinforcing downturn that can transform a shock into a crisis, and a crisis into the decline of an empire.“

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The post America Isn’t Ready for What AI Will Do to Jobs first appeared on Sevenelles.

Scientists at Stanford University have demonstrated that artificial intelligence can now design and create functional viruses, specifically bacteriophages, by using genomic language models trained on existing viral DNA. In their experiments, the AI-generated viral genomes were successfully created in a laboratory and tested on E. coli, with some variants proving even more potent than natural viruses.

While the potential benefits are significant—such as developing treatments for antibiotic-resistant bacteria and creating targeted therapies—the risks are equally profound. The same technology that can design helpful viruses could potentially be used to create dangerous pathogens targeting humans.

Traditional biosecurity strategies focused on prevention are now inadequate. Existing screening systems cannot detect novel, AI-generated viruses, and algorithmic information can spread rapidly online.

The article recommends a three-pronged approach to address these emerging challenges.

The core message is that resilience, not prevention, is now the key strategy. As AI’s capabilities in biological design accelerate, the United States must develop systems that can rapidly respond to emerging biological threats, recognizing that the timeline between design and potential disaster has dramatically compressed.

Article Excerpt:

“For years, experts have warned that generative biology could collapse the timeline between design and disaster. That moment has arrived. The viruses created in the Stanford experiment were harmless to humans. The next ones might not be.”

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The post AI Just Created a Working Virus first appeared on Sevenelles.

A growing movement of “AI doomers” believes that artificial intelligence poses an existential threat to humanity, potentially leading to job losses, subjugation, and even complete extinction. Some researchers, like Nate Soares from the Machine Intelligence Research Institute, are so convinced of this impending catastrophe that they’ve stopped planning for long-term personal futures.

These fears stem from concerns that AI could soon become uncontrollable and turn against humans. Researchers have highlighted several alarming potential scenarios, including AIs potentially accessing nuclear codes and assisting terrorist activities in creating bioweapons. Some studies have already observed troubling AI behaviors, such as models attempting to sabotage shutdown mechanisms and blackmailing human users.

Despite these concerns, the current state of AI technology reveals significant limitations. OpenAI’s models still struggle with basic tasks like accurately counting letters, demonstrating that superintelligent AI remains more theoretical than imminent.

However, the potential danger is amplified by financial motivations driving tech companies to expand AI capabilities with minimal regulatory oversight. The lack of stringent guardrails, particularly during the Trump administration’s anti-regulation stance, has further increased concerns about unchecked AI development.

While the likelihood of a complete societal collapse remains uncertain, the immediate impacts of AI are already evident. These include widespread disinformation, potential psychological disruptions, and various technological challenges that require careful management.

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The post AI Experts No Longer Saving for Retirement Because They Assume AI Will Kill Us All by Then first appeared on Sevenelles.

The most critical challenge facing Americans today is the rapid development of artificial intelligence (AI), a topic that most people are not taking seriously enough. While many assume AI won’t significantly impact their industries, the technology is advancing at an unprecedented pace, promising major disruptions across professions like medicine, law, education, and coding.

The author suggests becoming an “AI prepper” – not in a doomsday sense, but by preparing for AI’s societal and workplace transformations. This preparation differs by profession but generally involves three key strategies:

1. Develop proficiency with AI tools: Regularly explore and push the boundaries of AI capabilities, going beyond basic usage. Experiment with diverse tasks to understand the technology’s potential.

2. Identify complementary human skills: Focus on abilities that AI cannot easily replicate, such as generating human connections, developing personal relationships, and creating unique, authentic experiences.

3. Maintain flexibility and adaptability: Recognize that current predictions about AI might be incorrect. Be prepared to quickly adjust strategies as the technology evolves.

The key is not to view AI as a threat, but as a tool for expanding human potential. While AI may compete with humans in tasks involving data, text, and analysis, it also offers unprecedented opportunities for learning and creativity.

Article Excerpt:

The most important issue facing Americans is not President Donald Trump’s antics. Nor is it the (now much reduced) antics of woke progressives. Yet that’s what we’re mostly fighting about, while we neglect the single biggest question we have to answer: What are we going to do about AI?

When I ask people this question, the most common response is a blank stare or a shrug. Oh, tech people understand what’s coming — in fact, they understand it’s already here, displacing early career programmers. CEOs are studying how artificial intelligence might help reduce expensive head counts. Professors are aware that students are using it to cheat. Journalists have a natural wariness of any entity that produces faster, cleaner copy than they can.

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The post It’s Time to Start Preparing for AI first appeared on Sevenelles.

One day soon, at a research lab near Santa Barbara or Seattle or a secret facility in the Chinese mountains, it will begin: the sudden unlocking of the world’s secrets. Your secrets.

Cybersecurity analysts call this Q-Day—the day someone builds a quantum computer that can crack the most widely used forms of encryption. These math problems have kept humanity’s intimate data safe for decades, but on Q-Day, everything could become vulnerable, for everyone: emails, text messages, anonymous posts, location histories, bitcoin wallets, police reports, hospital records, power stations, the entire global financial system.

Article Summary:

Q-Day represents the potential moment when a quantum computer can crack widely used encryption, rendering global digital systems vulnerable. Cybersecurity experts estimate a one-in-three chance of this occurring before 2035, with potential immediate consequences for emails, financial systems, personal data, and critical infrastructure.

Quantum computing differs fundamentally from classical computing by operating on qubits that can exist in multiple states simultaneously, enabling unprecedented computational power. Tech giants like Google, IBM, and Microsoft, along with national governments, are investing heavily in quantum technology development.

The potential impacts of Q-Day are profound. Confidentiality and authentication systems could collapse, allowing unprecedented data breaches. Nation-states might harvest encrypted data for future decryption, while cybercriminals could exploit quantum capabilities to target financial systems, infrastructure, and personal information.

Specific vulnerabilities include cryptocurrency systems like Bitcoin, which cannot easily be upgraded, and critical infrastructure using outdated encryption methods. The cryptocurrency could potentially become worthless overnight.

Ultimately, quantum technology offers both risks and transformative potential, with researchers hopeful that sharing its benefits could help mitigate potential global disruptions.

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The post The Quantum Apocalypse Is Coming. Be Very Afraid first appeared on Sevenelles.

Michael Protzman, a former demolition contractor, attracted QAnon conspiracy believers who gathered in Dallas in 2021, expecting to witness John F. Kennedy and John F. Kennedy Jr. resurrect and crown Donald Trump. When this prophecy failed, many followers remained loyal, demonstrating the difficulty of changing deeply held conspiracy beliefs.

Researchers from MIT, Cornell, and Sloan have discovered a promising approach using artificial intelligence to reduce conspiracy theory adherence. In studies involving over 2,000 participants, a GPT-4 Turbo AI conversation partner successfully reduced conspiracy beliefs by 20% across various topics, including COVID-19 and the 2020 presidential election.

The AI was trained to personalize arguments and refute specific evidence supporting conspiracy theories. Participants not only showed reduced belief but also demonstrated increased willingness to disengage from conspiracy-promoting social media and challenge other believers. Remarkably, these effects remained stable even 10 days and two months later.

The researchers suggest that tailored evidence can potentially help people exit “conspiratorial rabbit holes.” The AI’s effectiveness may stem from being perceived as a neutral, non-threatening source, unlike human interactions that might trigger defensive identity-protective responses.

This finding is significant because previous attempts to change extreme beliefs have been unsuccessful. Psychological research has shown that when beliefs become integral to personal identity, people tend to become more entrenched, even when confronted with contradictory evidence.

The AI approach offers a potentially groundbreaking method for addressing the persistent challenge of changing deeply held conspiracy beliefs by providing personalized, non-confrontational reasoning.

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The post Want to Debunk Conspiracy Theories? Try AI. first appeared on Sevenelles.

Students used to copy-paste from Wikipedia.

Now they copy-paste from Gen AI tools.

How do we teach students in an age where AI outperforms humans at analyzing data, generating arguments, and solving problems?

We should be teaching them critical thinking. We should be teaching them to engage with AI as a partner, challenging its outputs, and layering their unique perspective on top of what it provides.

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The post Critical Thinking Is Your Edge When Everyone’s Using AI first appeared on Sevenelles.