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In his last semester at college, in between studying labor law and environmental impact assessment, Alex Elderbroom took a class on something very different: how to build a tiny house. In the class, at Paul Smith’s College in upstate New Yorka school that mixes traditional academics with more practical coursesa small group of students spent three months last fall going through each step of the construction process, from planning and purchasing materials to building basic furniture for the finished 8-by-10-foot space. Elderbroom, who just graduated, happens to already rent a tiny cabin. He was interested in learning how to build one of the homes himself. It seems like a good set of skills to have, he says. And I feel like its a type of living thats more rewarding than having a big house. [Photo: courtesy Paul Smith’s College] He had some construction experience, but others started from scratch. Sometimes, it wasn’t apparent that some of them had even held a hammer before, says associate professor Deb Naybor, who teaches the class. So we started a very basic support safety training, just showing them techniques. “It’s a life skill,” says Derek Grant, a senior majoring in natural resources management. “Anybody would benefit from learning it.” It’s not the only college with a tiny house class. Laney College, in California, also has a tiny house program. But Naybor now plans to take the idea a step farther. In a future version of the class, students will have the opportunity to buy materials so they can each build a tiny house on wheels of their ownand take it with them when they graduate. I always joke with the parents that if things don’t work out and [the students] don’t get a job right away, they can move the tiny house into their parents’ driveway and live there until they find a good job, she says. Even in the school’s remote location in the Adirondack Mountains, rents in the nearest town can be hard for students to afford, says Elderbroom. Nationally, rent is unaffordable for around half of all tenants, according to a Harvard report from January. For recent graduates who may not immediately land a lucrative job, the challenge is even greater. [Photo: courtesy Paul Smith’s College] The basic structure that students built last semester cost only around $2,800 in materials, though it didn’t include a kitchen and a bathroom. A fully livable home could potentially cost between $5,000 and $6,000, Naybor says, if students do the labor themselves. (She also notes that the cost of tiny houses varies hugely: something with luxury finishes in an expensive Bay Area city might cost as much as $300,000.) Though the houses can be cheap to build, zoning is a challenge. Some states and cities have embraced accessory dwelling units (ADUs) as part of a solution to the housing crisis. Other locations still haven’t, and only a handful of cities allow tiny houses on wheels. Finding land for a tiny house is another challenge, assuming that a recent graduate’s new job doesn’t happen to be near a relative with extra backyard space. Naybor advocates both for tiny houses as ADUs and for tiny-house villages that can host multiple homes. She also argues that more people should rethink their conception of what a home should look like, and how expensive it has to be. “The average American house is $420,000 right now,” she says. “Young people would have to be making $100,000 a year to get a 30-year mortgage, never mind coming up with the down payment . . . you could live in a tiny house and pay it off in 10 years.” She lives in a $50,000 tiny house herself, and takes her classes to visit it. “I say, ‘This could be a choice for you, rather than feeling like you have to grow into the same house you grew up with,'” she says.
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The AI landscape is rapidly evolving, with America’s $500 billion Stargate Project signaling massive infrastructure investment while China’s DeepSeek emerges as a formidable competitor. DeepSeek’s advanced AI models, rivaling Western capabilities at lower costs, raise significant concerns about potential cybersecurity threats, data mining, and intelligence gathering on a global scale. This development highlights the urgent need for robust AI regulation and security measures in the U.S. As the AI race intensifies, the gap between technological advancement and governance widens. The U.S. faces the critical challenge of not only accelerating its AI capabilities through projects like Stargate but also developing comprehensive regulatory frameworks to protect its digital assets and national security interests. With DeepSeek’s potential to overcome export controls and conduct sophisticated cyber operations, the U.S. must act swiftly to ensure its AI innovations remain secure and competitive in this rapidly changing technological landscape. We have already seen the first wave of AI-powered dangers. Deepfakes, bot accounts, and algorithmic manipulation on social media have all helped undermine social cohesion while contributing to the creation of political echo chambers. But these dangers are childs play compared to the risks that will emerge in the next five to ten years. During the pandemic, we saw the unparalleled speed with which new vaccines could be developed with the help of AI. As Mustafa Suleyman, founder of DeepMind and now CEO of Microsoft AI, has argued, it will not be long before AI can design new bioweapons with equal speed. And these capabilities will not be confined to state actors. Just as modern drone technology has recently democratized access to capabilities that were once the sole province of the military, any individual with even a rudimentary knowledge of coding will soon be able to weaponize AI from their bedroom at home. The fact that U.S. senators were publicly advocating the shooting down of unmanned aircraft systems, despite the lack of any legal basis for doing so, is a clear sign of a systemic failure of control. This failure is even more concerning than the drone sightings themselves. When confidence in the governments ability to handle such unexpected events collapses, the result is fear, confusion, and conspiratorial thought. But there is much worse to come if we fail to find new ways to regulate novel technologies. If you think the systemic breakdown in response to drone sightings is worrying, imagine how things will look when AI starts causing problems. Seven years spent helping the departments of Defense and Homeland Security with innovation and transformation (both organizational and digital) has shaped my thinking about the very real geopolitical risks that AI and digital technologies bring with them. But these dangers do not come only from outside our country. The past decade has seen an increasing tolerance among many U.S. citizens for the idea of political violence, a phenomenon that has been cast into particularly vivid relief in the wake of the shooting of United Healthcare CEO Brian Thompson. As automation replaces increasing numbers of jobs, it is entirely possible that a wave of mass unemployment will lead to severe unrest, multiplying the risk that AI will be used as a weapon to lash out at society at large. These dangers will be on our doorsteps soon. But even more concerning are the unknown unknowns. AI is developing at lightning speed, and even those responsible for that development have no idea exactly where we will end up. Nobel laureate Geoffrey Hinton, the so-called Godfather of AI, has said there is a significant chance that artificial intelligence will wipe out humanity within just 30 years. Others suggest that the time horizon is much narrower. The simple fact that there is so much uncertainty about the direction of travel should concern us all deeply. Anyone who is not at least worried has simply not thought hard enough about the dangers. The regimented regulation has to be risk-based We cannot afford to treat AI regulation in the same haphazard fashion that has been applied to drone technology. We need an adaptable, far-reaching and future-oriented approach to regulation that is designed to protect us from whatever might emerge as we push back the frontiers of machine intelligence. During a recent interview with Senator Richard Blumenthal, I discussed the question of how we can effectively regulate a technology that we do not yet fully understand. Blumenthal is the co-author with Senator Josh Hawley of the Bipartisan Framework for U.S. AI Act, also known as the Blumenthal-Hawley Framework. Blumenthal proposes a relatively light-touch approach, suggesting that the way the U.S. government regulates the pharmaceutical industry can serve as a model for our approach to AI. This approach, he argues, provides for strict licensing and oversight of potentially dangerous emerging technologies without placing undue restrictions on the ability of American companies to remain world leaders in the field. “We don’t want to stifle innovation,” Blumenthal says. “That’s why the regimented regulation has to be risk-based. If it doesn’t pose a risk, we don’t need a regulator.” This approach offers a valuable starting point for discussion, but I believe we need to go further. While a pharmaceutical model may be sufficient for regulating corporate AI development, we also need a framework that will limit the risks posed by individuals. The manufacturing and distribution of pharmaceuticals requires significant infrastructure, but computer code is an entirely different beast that can be replicated endlessly and transmitted anywhere on the planet in a fraction of a second. The possibility of problematic AI being created and leaking out into the wild is simply much higher than is the case for new and dangerous drugs. Given the potential for AI to generate extinction-level outcomes, it is not too far-reaching to say that the regulatory frameworks surrounding nuclear weapons and nuclear energy are more appropriate for this technology than those that apply in the drug industry. The announcement of the Stargate Project adds particular urgency to this discussion. While massive private-sector investment in AI infrastructure is crucial for maintaining American technological leadership, it also accelerates the timeline for developing comprehensive regulatory frameworks. We cannot afford to have our regulatory responses lag years behind technological developments when those developments are being measured in hundreds of billions of dollars. However we choose to balance the risks and rewards of AI research, we need to act soon. As we saw with the drone sightings that took place before Christmas, the lack of a comprehensive and cohesive framework for managing the threats from new technologies can leave government agencies paralyzed. And with risks that take in anything up to and including the extinction of humanity, we cannot afford this kind of inertia and confusion. We need a comprehensive regulatory framework that balances innovation with safety, one that recognizes both AI’s ransformative potential and its existential dangers. That means: Promoting responsible innovation. Encouraging the development and deployment of AI technologies in critical sectors in a safe and ethical manner. Establishing robust regulations. Public trust in AI systems requires both clear and enforceable regulatory frameworks and transparent systems of accountability. Strengthening national security. Policymakers must leverage AI to modernize military capabilities, deploying AI solutions that predict, detect, and counter cyber threats while ensuring ethical use of autonomous systems. Investing in workforce development. As a nation, we must establish comprehensive training programs that upskill workers for AI-driven industries while enhancing STEM (science, technology, engineering, and math) education to build foundational AI expertise among students and professionals. Leading in global AI standards. The U.S. must spearhead efforts to establish global norms for AI use by partnering with allies to define ethical standards and to safeguard intellectual property. Addressing public concerns. Securing public trust in AI requires increasing transparency about the objectives and applications of AI initiatives while also developing strategies to mitigate job displacement and ensure equitable economic benefits. The Stargate investment represents both the promise and the challenge of AI development. While it demonstrates America’s potential to lead the next technological revolution, it also highlights the urgent need for regulatory frameworks that can match the pace and scale of innovation. With investments of this magnitude reshaping our technological landscape, we cannot afford to get this wrong. We may not get a second chance.
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AI rivalry heats up: Glean CEO Arvind Jain replies to Sam Altmans caution to investors.
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