Trade tensions between the United States and Canada have escalated dramatically as U.S. President Donald Trump announced a 50% tariff increase on Canadian steel and aluminum. This measure was a response to Canada’s retaliatory electricity export tax, showcasing a new phase in the tariff war between the two countries. The announcement of the tariff increase and subsequent developments have significant implications for international trade relations and the economy.
Background and Announcement of the Tariff Increase
On March 11, 2025, President Trump announced via his social media platform Truth Social that he would increase tariffs on Canadian steel and aluminum from the existing 25% to 50%. Specifically, he instructed Commerce Secretary Wilbur Ross to impose an additional 25% tariff, which was scheduled to take effect on the morning of March 12. This represents a doubling of the 25% tariff rate that Trump had previously announced.
This sharp tariff increase was a direct retaliatory measure against the decision by Canada’s Ontario province to impose a 25% surcharge on electricity exported to the United States. President Trump explained, “Based on Ontario imposing a 25% tariff on electricity entering the United States, I have directed the Secretary of Commerce to add a 25% tariff on all steel and aluminum coming from Canada, bringing it to 50%.”
Given that Canada’s electricity export tax was a response to the Trump administration’s initial announcement to impose a 25% tariff on Canadian imports, this can be seen as a chain of retaliatory measures between the two countries.
Additional Threats and Pressure
President Trump announced additional pressure measures beyond the steel and aluminum tariff increase. First, he stated that he would soon declare an “electricity national emergency” in states such as New York, Michigan, and Minnesota, which Canada had warned about electricity export taxes. Through this, he explained that “the United States will be able to quickly take necessary measures to mitigate Canada’s unfair threats.”
Furthermore, Trump demanded that “Canada must immediately reduce its ‘anti-American farmer tariffs’ of 250%-390% on various American dairy products, which have long been considered outrageous.” He then threatened to significantly increase tariffs on Canadian automobiles from April 2 if Canada did not abolish these tariffs. Trump warned that such measures “would result in the permanent closure of the Canadian automobile manufacturing industry.”
Rapid Change and Easing of the Situation
Interestingly, immediately after the tariff increase announcement, the situation changed rapidly. Doug Ford, the Premier of Ontario, Canada, announced that he would temporarily suspend his electricity export tax measure. Ford stated that after a “productive conversation” with the U.S. Secretary of Commerce, he would temporarily suspend the 25% additional fee burden on electricity exported to the United States.
In response, President Trump also adjusted his position. When asked at a White House meeting with reporters whether he could cancel the plan to impose 50% tariffs on steel and aluminum since Canada had eased its tariff response, he replied, “We’re looking at it, and probably will.” This demonstrates that Trump is strategically using tariffs as a means to pressure other countries.
Economic Ripple Effects
Trump’s tariff policies and the conflict between the two countries are already causing significant market shocks. Due to the uncertainty caused by the tariff imposition announcement, U.S. stock markets fluctuated greatly, with the NASDAQ index plunging 4% on the 10th. This was the largest drop recorded in 2 years and 6 months since September 13, 2022.
In the aluminum market, in particular, an immediate price increase was observed. The aluminum premium including tariffs in the U.S. Midwest market soared to about $990 per ton (approximately 1.44 million won) on March 11, nearly 20% higher than the previous day and more than 70% higher compared to the beginning of the year.
Additionally, due to the effects of President Trump’s tariff war, gold holdings at the Commodity Exchange (COMEX) in New York reached record high levels. As of March 5, COMEX’s gold inventory was 39.7 million ounces, recording the highest level since the start of statistics in 1992, amounting to approximately $115 billion. The increase in gold inventory was due to the prospect that gold could be included in tariff measures, along with the rise in U.S. gold prices compared to the global benchmark.
Trump’s Tariff Policy in a Broader Context
This tariff increase on Canada is part of President Trump’s broader tariff policy. Trump had already announced in February that he would impose a 25% tariff on all steel and aluminum imported into the United States. Tariffs are central to Trump’s economic vision, as he expects them to grow the U.S. economy, protect jobs, and increase tax revenue.
However, economists are increasingly expressing concerns that such tariff policies could lead to a recession. According to a small business survey, confidence has weakened completely after Trump’s election victory on November 5, 2024, with sentiment weakening for three consecutive months.
Conclusion
President Trump’s announcement of a 50% tariff increase on Canadian steel and aluminum has heightened tensions in U.S.-Canada trade relations, but the crisis appears to be calming down due to the rapid response and negotiations between the two countries. However, this case clearly demonstrates the Trump administration’s strategy of pressure through tariffs, the responses of trade partner countries, and the possibility of rapid expansion and mitigation of international trade tensions.
Such tariff wars lead to market instability in the short term, but in the long term, they can influence the reorganization of the world trade order and economic relations between countries. It is necessary to pay attention to how the direction of the Trump administration’s tariff policy and the responses of trade partner countries will affect the international economy in the future.
Elon Musk’s Neuralink has filed trademarks for ‘Telepathy’ and ‘Telekinesis’ with the United States Patent and Trademark Office (USPTO), making a move to secure its position in the brain-computer interface (BCI) technology market. This trademark filing is being regarded as a significant step that signals more than just name protection, forecasting fundamental changes in human cognitive capabilities and physical interaction methods.
Telepathy: Controlling Digital Devices with Thoughts Alone
According to documents submitted to the USPTO, ‘Telepathy’ is defined as a “software and hardware communication control system through implantable brain-computer interface.” The technology’s core consists of the N1 electrode array and neural signal processing algorithm, where an implant with 1,024 electrodes integrated into polymer threads of 4-6μm diameter detects neural activity in the motor cortex at a 200Hz sampling rate.
Nolund Arvo, who received the first human implant surgery in January 2024, achieved a 75% win rate in chess games using only his thoughts after 8 weeks of surgery, while the second patient, Alex, showed improved productivity by generating 12 design elements per hour in 3D modeling work. These achievements suggest possibilities beyond simple device control to cognitive enhancement.
Telekinesis: A New Paradigm of Controlling Objects with Thoughts
‘Telekinesis’ is defined as “neural signal-based physical object control technology” and is currently being implemented through the R1 robot system. Equipped with an 8 degrees of freedom (DOF) drive mechanism and force feedback sensors, this system began testing in November 2024, with participants successfully manipulating objects with 0.5mm precision.
A notable feature is that it’s designed to enable three-dimensional spatial control using only motor imagery signals, representing an innovative technology that overcomes the two-dimensional limitations of existing BCI technology. In manufacturing site simulations, the telekinesis interface recorded assembly speeds 40% faster compared to traditional joystick controls.
Medical Innovation and Ethical Challenges Coexist
In virtual simulation studies with spinal cord injury patients, the application of the telekinesis system significantly improved the Activities of Daily Living (ADL) index from 45 to 78 points (out of 100). Additionally, in stroke rehabilitation, the addition of targeted electrical stimulation for neural plasticity induction proved to reduce motor function recovery time by 40%.
However, technical challenges and ethical dilemmas persist. 30% of first-phase implant patients showed electrode sensitivity decreased to 65% of initial levels after six months, primarily attributed to neural tissue scarring. In response, Neuralink is developing third-generation electrode threads with anti-inflammatory coating materials.
Furthermore, a recent report from Harvard’s Ethics Institute pointed out that 43 out of 127 types of neural data collectable by BCI devices qualify as ‘ultra-sensitive information’ under the EU’s General Data Protection Regulation (GDPR). Particularly, concerns have been raised about the potential commercial use of emotional state tracking data, and Neuralink plans to implement data anonymization encryption protocols.
Global Expansion and Regulatory Environment Response
According to trademark application documents, the Telepathy trademark was filed simultaneously under international classes 9 (electronic devices) and 42 (scientific and technological services), while the Telekinesis trademark was also filed with the European Union Intellectual Property Office (EUIPO), clearly indicating a global market entry strategy.
The regulatory environment is also rapidly evolving. The US FDA approved Neuralink’s Blindsight implant as an innovative device designation in September 2024, and Canadian health authorities approved the CAN-PRIME clinical trial in November 2024. In Europe, the amendment to Medical Device Regulation Article 5, effective January 2025, mandated the establishment of independent ethics review committees for BCI devices.
Expert Outlook: “Beyond Medical Use to Daily Innovation”
Brain-computer interface technology experts predict that Neuralink’s trademark applications will be more than just a commercial strategy, marking the beginning of a technological revolution that expands human biological limitations.
“While initially focusing on medical applications, particularly for neurological disorders and injury patients, there is high potential for expansion into the general consumer market in the long term,” analyzed Director Kim Min-seok of the Neural Engineering Institute.
However, according to a recent survey presented at the IEEE International Conference, public acceptance of non-medical BCI technology applications remains skeptical at 44%. Experts unanimously agree that for telepathy and telekinesis technologies to establish themselves as tools for human advancement, simultaneous pursuit of technical completeness and social consensus is essential.
The US Department of Labor projects the creation of 1.2 million BCI-related jobs by 2030, and the commercialization of telepathy and telekinesis technologies is expected to play a major role in realizing this projection.
With commercialization announced for 2026, Neuralink’s recent trademark applications are expected to serve as an important milestone bringing us one step closer to a future where humans and technology converge.
The Future of Deep Tech Investment: How Innovation Technology Opens the Door to Wealth
1.1 Five Core Principles of Technical Depth
Deep Tech is a driving force of modern technological innovation, representing a field that goes beyond simple technology application. It particularly requires a balance between scientific fundamentality and industrial applicability, and this balance has become an essential element for sustainable technological development and tangible value creation. This chapter will examine in detail the five core principles for successful development and implementation of Deep Tech.
1. Scientific Fundamentality
The core of Deep Tech lies in innovation derived from basic scientific research. This is based on deep scientific insights that go beyond simple technological applications. A prime example is Ginkgo Bioworks, which started in MIT laboratories, developing innovative DNA design technology in synthetic biology. Their technology is used across various industrial sectors from biofuel production to advanced pharmaceutical development, demonstrating how basic scientific research can lead to tangible commercial value.
Looking at the global Deep Tech industry landscape, as of 2024, over 70% of all Deep Tech companies possess their own patent portfolios. A characteristic feature of these companies is that they invest an average of more than five years in in-depth research and development to enhance technological maturity. This serves as a clear indicator of the importance of long-term research investment and scientific validation in the Deep Tech field.
Examining Korea’s Deep Tech ecosystem, AI-bio convergence technology development is actively progressing, centered around the Daedeok Special Research Complex. However, with only 0.05 Deep Tech companies per million population, there is an urgent need to strengthen both the quality and quantity of the basic research ecosystem to secure global competitiveness. This suggests the necessity of not just increasing the number of companies, but also improving research quality and building a sustainable innovation ecosystem.
2. Industrial Applicability
The true value of scientific discovery lies in solving real industrial problems. Recent cases clearly demonstrate the importance of such applicability. Google DeepMind’s AlphaFold3 has achieved 92% accuracy in protein structure prediction using artificial intelligence technology. This has dramatically shortened the most time-consuming phase in drug development, reducing the overall development period by 50%.
Another notable example is global pharmaceutical company Merck’s implementation of IBM’s blockchain technology in pharmaceutical distribution. This achieved remarkable results by reducing counterfeit drug distribution rates by 99.8%, significantly contributing to patient safety and improving pharmaceutical industry reliability. However, in contrast to these global success stories, Korea’s reality shows some limitations. Particularly, the difficulty in finding successful commercialization cases among technology-specialized listed companies demonstrates the challenges in translating Korea’s R&D investments into actual business outcomes.
3. Patent Governance
Patents are crucial strategic assets that determine the survival and growth of Deep Tech companies. In this context, the Deep Tech IP finance activation policy pursued by the Korea Intellectual Property Service Association in 2025 shows notable progress. This is because it achieved tangible results with 13 billion won in investment attraction through the introduction of a patent evaluation cost support program. Meanwhile, different approaches to patent management are observed at the global level. The U.S. DARPA (Defense Advanced Research Projects Agency) has adopted a model where the government proactively promotes patent standardization to facilitate technology transfer to the private sector. In contrast, China is strengthening its domestic companies’ competitiveness by forming technology blocks and intensively managing patent pools.
4. Ecosystem Dependency
4. Ecosystem Dependency: The Hidden Key to Deep Tech Success
Deep Tech’s success depends not only on technological advancement but also on strong support from industry-academia-research cooperation networks. Israel produces over 150 innovative startups annually through its spin-off model that converts military technology for civilian use, establishing itself as an important benchmark in the global Deep Tech ecosystem. For example, HiFive AI successfully transformed military image analysis technology into a medical diagnostic platform, demonstrating the potential for technology commercialization.
In contrast, while Korea attracted 124.4 billion won in investment through the Ministry of SMEs and Startups’ Deep Tech TIPS Program in 2024, the technology transfer rate between universities and companies remains at just 12%. This is only about one-third of the U.S. rate of 35%, indicating that Korea’s Deep Tech ecosystem is still in its maturation phase.
Israel’s Spin-off Model: Success Cases in Military-Civilian Technology Transfer
Israel’s military-civilian technology transfer model converts military technology for civilian industry, facilitating the birth of innovative startups. Many Israeli Deep Tech companies expand into civilian sectors based on military technology, bringing innovation to various industries including medical, security, and energy. For example, military drone technology has been converted into an agricultural monitoring platform, generating annual sales of 30 billion won.
Deep Tech TIPS Program: Challenges and Opportunities
The Deep Tech TIPS Program plays an important role in supporting innovative startups through public-private cooperation. However, the low technology transfer rate suggests the need for strengthening industry-academia-research cooperation. This requires close collaboration between universities and companies and regulatory improvements. In particular, strengthening the industry-academia-research cooperation network is a key element that can elevate Korea’s Deep Tech ecosystem to a globally competitive level.
The Importance of Ecosystem Dependency
Deep Tech’s success depends not only on technological advancement but also on strong support from industry-academia-research cooperation networks. This plays a crucial role in all aspects, including technology commercialization, market expansion, and investment attraction. Therefore, Korea should use Israel’s spin-off model as a benchmark to strengthen industry-academia-research cooperation and further mature the Deep Tech ecosystem through regulatory improvements.
This ecosystem dependency is essential for Deep Tech companies to secure global competitiveness
In a recent episode of “The Ezra Klein Show” published on March 4, 2025, in The New York Times, former White House special adviser for artificial intelligence Ben Buchanan made a startling claim: artificial general intelligence (AGI) is likely to arrive during Donald Trump’s second term, perhaps within the next two to three years1. This assertion challenges previous assumptions that AGI was five to fifteen years away and signals a potentially transformative moment in human history that governments, corporations, and individuals may be unprepared to navigate1. This comprehensive analysis examines the claims, evidence, potential implications, and policy considerations surrounding the imminent arrival of AGI as presented in this influential conversation.
The Accelerating Timeline Toward Artificial General Intelligence
According to Buchanan, what has changed is not just the theoretical possibility of AGI but the timeline for its development. While experts previously estimated AGI might take five to fifteen years to develop, many now believe it could arrive within just two to three years1. This dramatic acceleration is based on insider observations of current AI capabilities and development trajectories within leading AI labs. As Buchanan puts it, “The trend line is even clearer now than it was then,” referencing his time in the White House where he witnessed indicators pointing toward this acceleration1.
Buchanan defines these “extraordinarily capable AI systems” as approaching the canonical definition of AGI—a system capable of performing almost any cognitive task a human can do1. While he dislikes the term AGI itself (repeatedly caveating his use of it), he acknowledges that systems matching this general description are approaching rapidly. This is not merely theoretical; concrete examples already demonstrate the trajectory. Klein mentions using Deep Research, an OpenAI product that can produce high-quality analytical research reports in minutes that would take human researchers days to compile1.
The implications extend beyond specialized applications into fundamental economic transformation. As Klein observes, numerous firms report expectations that by the end of 2025 or early 2026, most code will not be written by human beings but by AI systems1. The rate of this transformation is particularly significant because, unlike previous technological revolutions such as electricity or railroads which took decades to implement, AI capabilities are expanding at unprecedented speed1.
National Security Dimensions: The Race With China
A central theme in the conversation is the perceived necessity for the United States to reach AGI before China does. Buchanan argues there are “profound economic, military and intelligence capabilities that would be downstream of getting to AGI or transformative AI,” making AI leadership a fundamental national security imperative1. He invokes John F. Kennedy’s 1962 Rice University speech about space exploration to illustrate the stakes: “Whether it will become a force for good or ill depends on man. And only if the United States occupies a position of pre-eminence can we help decide whether this new ocean will be a sea of peace or a new terrifying theater of war”1.
The Biden administration implemented export controls on advanced semiconductor technology to China specifically to maintain America’s AI advantage. These controls have been controversial—semiconductor companies like Nvidia have argued they limit their market opportunities—but Buchanan defends them as essential for national security, even as he acknowledges they’ve driven China to develop its own computing supply chain110.
The emergence of DeepSeek, a Chinese AI company that has produced competitive AI models reportedly with less computing power than American counterparts, raised concerns about the efficacy of these export controls18. Buchanan downplays this development, arguing that DeepSeek still represents algorithmic efficiency improvements rather than a fundamental breakthrough and that chip export restrictions remain effective and necessary1.
The Biden Administration’s AI Policy Approach
Under President Biden, the administration developed a multifaceted approach to AI governance that sought to balance innovation with safety. As Buchanan explains, the administration established new institutions like the U.S. Artificial Intelligence Safety Institute to focus on safety concerns including cyber risks, biorisks, and accident risks1. The administration issued an executive order on AI and a national security memorandum addressing AI in defense applications1.
Buchanan emphasizes that beyond a requirement for leading AI labs to share safety test results, most of the Biden administration’s approach was voluntary rather than regulatory1. The goal was to create a foundation for future governance while not impeding development. This foundation included export controls on advanced chips to China, creation of the AI Safety Institute, the executive order on AI, and efforts to accelerate domestic power development for AI infrastructure111.
One crucial insight Buchanan offers is that AI represents a departure from previous revolutionary technologies because it is not funded by the Department of Defense. He notes, “This is the first revolutionary technology that is not funded by the Department of Defense, basically,” contrasting it with nuclear science, space technology, early internet, microprocessors, and other historically significant innovations where government leadership shaped development1.
The Trump Administration’s Shift in AI Policy
The transition to the Trump administration has brought significant changes in AI policy direction. In January 2025, President Trump signed an executive order revoking Biden’s AI executive order, characterizing it as imposing “onerous and unnecessary government control over the development of AI”5. The Trump order directs departments and agencies to “revise or rescind all policies, directives, regulations, orders, and other actions taken under the Biden AI order that are inconsistent with enhancing America’s leadership in AI”5.
The philosophical shift was clearly articulated by Vice President J.D. Vance at an AI summit in Paris, where he stated: “When conferences like this convene to discuss a cutting-edge technology, oftentimes I think our response is to be too self-conscious, too risk averse. But never have I encountered a breakthrough in tech that so clearly calls us to do precisely the opposite”1. This signals a more accelerationist approach to AI development.
The new administration brings influential tech figures into government, including Elon Musk and Marc Andreessen, who hold strong views about AI development. Andreessen has publicly criticized the Biden administration’s approach, claiming they wanted to limit AI to “two or three large companies” and eliminate startups in the space—a characterization Buchanan disputes1.
The Safety Versus Acceleration Debate
A fundamental tension emerges in the conversation between approaches prioritizing AI safety versus those advocating acceleration. Buchanan argues that these aren’t necessarily in conflict, citing historical examples where safety standards facilitated rather than hindered technological adoption. He points to railroad development in the late 1800s, where safety standards like block signaling, air brakes, and standardized tracks made the technology more widely adopted1.
“If you look at the history of technology and technology adaptation, the evidence is pretty clear that the right amount of safety action unleashes opportunity and, in fact, unleashes speed,” Buchanan argues1. However, he acknowledges the risk of overregulation, noting the example of nuclear power, where safety concerns may have “strangled in the crib” a promising technology1.
The accelerationist view, represented by figures in the Trump administration, emphasizes moving quickly and addressing problems as they arise rather than being overly cautious. Harry Glorikian, summarizing Klein and Buchanan’s conversation, notes the gravity of the situation: “Artificial General Intelligence (AGI)—the phrase might spark visions of science fiction, but… it’s fast becoming reality, and if that is the case the implications could be enormous”2.
International Relations and AI Governance
The conversation reveals complex international dynamics around AI governance. While the U.S. competes fiercely with China on AI development, it has also engaged in dialogue on AI safety with Chinese counterparts. Buchanan mentions flying to Geneva to meet with Chinese representatives as part of an “AI dialogue”1.
Relations with European allies also feature prominently. According to Buchanan, the Biden administration took a different approach than the European Union, which has developed the comprehensive EU AI Act. Vance’s speech in Paris signaled that the Trump administration would resist complex multilateral regulations that could slow American AI companies and suggested potential retaliation if European regulations penalized U.S. firms1.
Before leaving office, the Biden administration organized gatherings of allied nations to discuss AI safety protocols. Officials from Canada, Kenya, Singapore, the United Kingdom, and the 27-member European Union were set to meet in San Francisco to address issues like detecting and preventing AI-generated deepfakes11. The future of such international cooperation under the Trump administration remains uncertain.
Labor Market Implications and Social Preparedness
One of the most pressing concerns about AGI is its potential impact on labor markets. Klein expresses frustration at the lack of concrete policy proposals to address potential job displacement: “Are we about to enter a world where we are much more digitally vulnerable as normal people? And I’m not just talking about people whom the states might want to spy on. But you will get versions of these systems that all kinds of bad actors will have”1.
Buchanan acknowledges the legitimacy of these concerns but admits the Biden administration had no comprehensive plan to address them: “We were thinking about this question. We knew it was not going to be a question we were going to confront in the president’s term. We knew it was a question that you would need Congress to do anything about”1. He also notes that any solution would need to preserve the “dignity that work brings”1.
The conversation reveals a significant gap between the expected speed of AI transformation and society’s preparedness for its consequences. As Klein points out, there are no solid policy proposals on the shelf for addressing severe labor market disruptions, despite years of warning about the possibility1. This preparation gap extends to other domains, including the security of AI labs themselves, which may be vulnerable to hacking or industrial espionage1.
Surveillance, Security, and Democratic Values
The potential for AI to enhance surveillance capabilities raises profound concerns for democratic societies. Buchanan acknowledges that while AI might enable more efficient analysis of already-collected data (like satellite imagery), there are legitimate concerns about surveillance states becoming more effective1. He notes that in autocracies like China, AI could make government control more pervasive, eliminating the traditional breathing room captured in the saying “Heaven is high, and the emperor is far away”1.
For democratic societies, AI in law enforcement presents both opportunities and risks. Buchanan mentions the Department of Justice developing principles for AI use in criminal justice, acknowledging potential benefits of consistency but also “tremendous risk of bias and discrimination” and “a risk of a fundamental encroachment on rights from the widespread unchecked use of AI in the law enforcement system”1.
Security dimensions extend to potential vulnerabilities in AI systems themselves. Buchanan discusses how more powerful AI could benefit both offensive and defensive cybersecurity operations1. While offensive actors might find vulnerabilities more easily, defensive systems could write more secure code and better detect intrusions. During a transitional period, however, legacy systems without AI-enhanced protections could be particularly vulnerable1.
Critical Decisions Ahead for AGI Governance
As AGI approaches, several critical policy decisions loom. Buchanan identifies the open-source/open-weights question as particularly significant. This concerns whether the “weights” of AI models—roughly analogous to the strength of connections between neurons in the brain—should be openly published1. Open-weight systems facilitate innovation but also make it easier to remove safety protocols like refusals to assist with weapons development1.
Another key decision involves the relationship between the public and private sectors. As AI becomes more capable, governments will need to determine whether voluntary safety arrangements should become mandatory1. This raises questions about the appropriate level of government oversight and the balance between innovation and regulation.
The use of AI in national defense presents another crucial decision point. Buchanan notes that the Biden administration established guidelines for military AI applications consistent with American values, but the Trump administration will need to decide whether to maintain these safeguards or prioritize speed of development1.
Conclusion: Preparing for an Uncertain Future
The conversation between Klein and Buchanan reveals both the extraordinary potential and profound uncertainty surrounding AGI development. As Buchanan puts it, “I think there should be an intellectual humility here. Before you take a policy action, you have to have some understanding of what it is you’re doing and why”1. This humility extends to recognizing the limits of current understanding while still preparing for transformative change.
Klein expresses frustration with this tension, noting the disconnect between the massive implications described and the measured policy responses proposed1. This disconnect underscores a broader societal challenge: how to prepare for a technology that could fundamentally transform human civilization when we cannot fully anticipate what that transformation will look like.
