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May 14, 2026

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Based on โ€œClaude Code Can Be Your Second Brainโ€ from Every Watch the original video

The AI Amplifier: Inside the Ultimate Second Brain for Deep Work

In an age where digital tools promise productivity but often deliver distraction, Noah Brier has engineered a system that transcends the typical. Co-founder of successful startups like Percolate and Variance, and now leading AI strategy consultancy Alfik, Brier has cultivated a unique approach to harnessing artificial intelligence. His setup, which he affectionately refers to as a โ€œheavy duty Claude Code setupโ€ rather than just for coding, transforms an Obsidian note-taking vault into a true second brain โ€“ a relentless thinking partner, researcher, and even a logkeeper of his evolving ideas, all accessible from anywhere.

This isnโ€™t just about using AI for quick answers or content generation; itโ€™s about deep, sustained intellectual work, reimagined. Brierโ€™s innovation lies in his ability to leverage AI not as a replacement for human thought, but as a profound amplifier, enabling him to think, research, write, and even ship code from the most unexpected of places: his phone.

The Second Brain Unleashed: Noahโ€™s Obsidian-Claude Code Nexus

At the heart of Brierโ€™s system is Obsidian, a popular note-taking application that stores notes as plain markdown files in a userโ€™s local file system. This choice is deliberate, offering flexibility and ownership that traditional cloud-based note apps often lack. โ€œOne of the big advantages with Obsidian as a note-taking platform is that itโ€™s a bunch of markdown files and a bunch of folders,โ€ Brier explains, โ€œand they can then be synced with Git and you can do lots of other fun kinds of things.โ€

On top of this Obsidian vault, Brier runs Claude Code, Anthropicโ€™s AI assistant designed for coding and text processing. But Brierโ€™s primary use isnโ€™t for writing code; itโ€™s for interacting with his vast archive of notes. His most recent โ€œobsession,โ€ he shares, has been standing up a home server in his basement to host this entire setup, making his Claude Code-powered Obsidian vault accessible and fully functional on his phone. This seemingly simple step has been transformative, turning his phone from a device primarily for consumption into a powerful tool for deep intellectual engagement.

โ€œI found whether itโ€™s like Claude Code and Obsidian orโ€ฆ even Claude Code and code right,โ€ Brier notes, โ€œbeing able to sign in on your phone and have Claude Code push a small update to something because you just realize it while youโ€™re out is amazing.โ€ This capability extends the reach of his second brain, allowing him to seamlessly transition between desktop and mobile environments for complex tasks.

Beyond Generative: The Power of AIโ€™s โ€œReadingโ€

A core philosophy underpinning Brierโ€™s workflow is the distinction between โ€œthinking modeโ€ and โ€œwriting mode.โ€ He observes that most AI models, often labeled โ€œgenerative,โ€ are overly eager to produce artifacts โ€“ outlines, drafts, or completed pieces. This, he argues, misses the AIโ€™s most powerful, yet often overlooked, capability: its ability to โ€œread.โ€

โ€œI think partially because we call it generative, thereโ€™s entirely too much focus on its ability to write and not enough focus on its ability to read,โ€ Brier states. โ€œIts ability to read is incredible, right? And I think, arguably, sort of like much more useful on a day-to-day basis. Like we produce artifacts far less frequently than we just like think about things.โ€

To enforce this distinction, Brier employs a specific โ€œthinking partnerโ€ sub-agent within Claude Code. This agent is meticulously prompted with instructions like: โ€œYour role is to facilitate thinkingโ€ฆ donโ€™t try to write the thing.โ€ He even includes explicit directives: โ€œI do not under any circumstances want you to try to write it. Take this literally. Do not create outlines, drafts, or any versions of talks/writing. Only gather and organize the requested materials.โ€ This ensures the AI acts as a Socratic guide, asking sharp questions and helping him explore complex problems, rather than prematurely drafting solutions.

When embarking on a new project, such as preparing for a conference talk, Brierโ€™s process is meticulous:

  1. Project Initialization: He creates a new folder (following the PARA method for organization) and starts Claude Code in his root Obsidian directory, giving it access to his entire vault.
  2. Contextualization: He feeds the AI past talks and general ideas to establish style and scope.
  3. Vault-Wide Research: Crucially, he instructs Claude Code to search his entire 1500+ note archive for existing research relevant to the new project and pull it into a dedicated โ€œresearchโ€ folder. This jumpstarts the process with his own prior knowledge.
  4. External Chats: Transcripts from conversations with other AI models (ChatGPT, Grok, Claude) are also clipped and stored in a โ€œchatsโ€ folder, becoming part of the research corpus.
  5. Daily Progress Log: At the end of each day, Brier has Claude Code review all new notes and chats, then summarize what heโ€™s learned and the best ideas that emerged, helping to push the project forward.

Perhaps one of the most powerful features for maintaining deep work is the โ€œcatch me upโ€ command. After interruptions, Brier can simply ask Claude Code, โ€œCan you catch me up on the last three days of research?โ€ The AI then sifts through all new material in the project folder, providing a concise summary of progress and insights. โ€œItโ€™s pretty amazing also to just be able to kind of revisit deep work like this,โ€ Brier marvels, acknowledging that picking up work after a break is often the hardest part.

The Voice of Genius: Grok in the Car and Beyond

While Claude Code powers his Obsidian vault, Brier also champions Grokโ€™s voice mode as a superior tool for on-the-go deep thinking. He singles out Grok 2, 3, or 4 for its intelligence and โ€œtool callingโ€ capabilities โ€“ its ability to integrate with other functions or search the web effectively โ€“ which he finds significantly better than competitors like ChatGPT or Gemini.

โ€œI will fight anybody who says anything different,โ€ he declares, adding, โ€œI just found Grokโ€™s voice mode to be significantly smarter than anybody elseโ€™s.โ€ He describes it as โ€œa podcast made specifically for you about whatever youโ€™re curious about.โ€

Brier shares several anecdotes illustrating Grokโ€™s utility:

  • A 5-hour drive to New Hampshire for summer camp drop-off turned into a 2-hour research session, working through a complex piece just by connecting his phone to Bluetooth.
  • A โ€œmind-blowing sessionโ€ on self-attention mechanisms, where Grok delivered the best explanation heโ€™d ever heard.
  • Using Grok in his Tesla (where itโ€™s now integrated) to research Walter Benjaminโ€™s โ€œThe Work of Art in the Age of Mechanical Reproduction,โ€ exploring themes of elitist critiques against new technologies.

This ability to engage in profound intellectual exploration while commuting or driving represents a paradigm shift. โ€œItโ€™s just Iโ€ฆ and you know obviously all the sort of other ChatGPT and Claude and all these things of just being able to sort of like go and do research and really think and and explore things in this device thatโ€™s always been useful but like not useful for deep work,โ€ he explains. โ€œI feel like it it itโ€™s really changed my ability to do that.โ€

AI as Bureaucracyโ€™s Bane: The โ€œThomasโ€™s English Muffinโ€ Theory

Brierโ€™s current talk preparation, a detailed example he walks us through, ties together historical insights with his vision for AIโ€™s impact on organizations. The talk explores the OSSโ€™s (Office of Strategic Services, precursor to the CIA) โ€œSimple Sabotage Field Manualโ€ โ€“ a guide for citizen saboteurs during WWII. He highlights the manualโ€™s recommendations for white-collar workers: โ€œalways refer things to committee,โ€ โ€œalways revisit previously made decisions,โ€ โ€œdonโ€™t act with too much haste.โ€

Brier connects this historical bureaucracy to modern organizational challenges, proposing that AI can โ€œsidestep a lot of the bureaucracy that exists inside large organizations because it sort of has thisโ€ฆ goo-like effect where it can kind of fit into any crevice or crack.โ€ He calls this his โ€œThomasโ€™s English muffin theory of AI,โ€ where AI gets into โ€œthe nooks and crannies.โ€

This theory posits that unlike past technologies, which often forced companies to adopt new structures or centralize tools (e.g., everyone must use Jira, not Asana), AI can act as a โ€œfuzzy interface.โ€ It doesnโ€™t care what tools or data structures teams use because โ€œitโ€™s all just data structures to them.โ€ This allows companies to maintain diverse, decentralized workflows while AI models in the middle translate and integrate information.

He draws a parallel to Wild Bill Donovan, who started the OSS, and his emphasis on โ€œempowering individualsโ€ and โ€œautonomy at the edgesโ€ โ€“ a philosophy he sees echoed in AIโ€™s potential to enable distributed, yet coordinated, work. Brier even floats a nascent idea: โ€œbureaucracy as positional encoding,โ€ suggesting that bureaucracy, while often negative, was an innovation for large-scale operations. AI, through its ability to parallelize work (like transformers displacing sequential models), might offer a new way to achieve structure and hierarchy without the traditional rigidities.

This isnโ€™t just theoretical. The host, Dan, offers a real-world example from Every, the company behind the video. With 15 people running six different products, each with its own tech stack, AI is enabling โ€œtacit code sharing.โ€ Instead of abstracting common functionalities (like fast file search) into modular libraries โ€“ a โ€œheavy liftโ€ โ€“ developers can simply use Claude Code to understand and adapt code from other product repos. โ€œEveryone gets more productive because AI can kind of translate,โ€ Dan explains.

Noah Brierโ€™s journey into building an AI-powered second brain reveals a profound shift in how we can engage with information and deepen our thinking. By treating AI as a collaborative partner rather than just a generative tool, and by leveraging its unique capabilities to read, organize, and stimulate thought across all devices, he demonstrates a future where deep work is not only more accessible but also more profound. This isnโ€™t just about personal productivity; itโ€™s a blueprint for how AI can fundamentally reshape our intellectual processes and organizational structures, one thought, one research query, one โ€œnook and crannyโ€ at a time.


Based on โ€œTwo Superpowers Across the Tableโ€ from New York Times Podcasts Watch the original video

The Uneasy Summit: Trumpโ€™s Beijing Trip Under the Shadow of Iran

For the first time in nearly a decade, President Donald Trump was set to meet with Chinese President Xi Jinping in Beijing. But this wasnโ€™t the triumphant return of a newly elected leader, basking in the glow of global pageantry. As Rachel Abrams from The Daily noted, the meeting on Wednesday, May 13th, of Trumpโ€™s hypothetical second term, came at a fraught moment. Trump was struggling to extricate the United States from a war with Iran, forcing him to face off against China, arguably the biggest long-term threat to American dominance across technology, trade, and military power.

My colleague, David Sanger, reporting live from his Beijing hotel, painted a vivid picture of the high stakes and low expectations surrounding this critical summit. What would come of it, and more pressingly, what wouldnโ€™t?

A Weakened Hand in the Dragonโ€™s Lair

The contrast with President Trumpโ€™s first visit to China in 2017 couldnโ€™t have been starker. Then, he was a freshly minted president, treated to the full spectacle of Chinese hospitality. โ€œPresident Xi, I want to thank you for that incredible welcoming ceremony,โ€ Trump had declared, addressing the โ€œchronic imbalanceโ€ in trade and pledging to protect American intellectual property. He was just beginning to shape his China policy, focusing on the nationโ€™s rise and envisioning a stronger bilateral relationship.

This time, however, Trump arrived under a significant cloud: the ongoing conflict with Iran. The summit, originally planned for April, had been postponed with the expectation that by mid-May, Iran would have capitulated. Instead, Iran was resisting, with other world leaders like Chancellor Mertz of Germany suggesting the United States had been humiliated. The Chinese themselves were reportedly โ€œa bit mystifiedโ€ by the USโ€™s struggles to secure the Strait of Hormuz or defeat what they perceived as a โ€œsecond or third rate powerโ€ like Iran.

โ€œAll summits are about optics,โ€ Sanger observed, โ€œand while Iโ€™m sure there will be all the pomp and ceremony that goes with these, the fact of the matter is he comes into this summit looking a bit weakened.โ€ This shift in perceived strength was a critical backdrop to any negotiations.

The Low-Hanging Fruit: Beef, Beans, and Boeing

With Trumpโ€™s arrival, discussions inevitably began with trade and economic relationships. While the fundamental divides between the two superpowers loomed large, the immediate focus would likely be on what David Sanger termed โ€œthe low-hanging fruit.โ€

โ€œThis is Donald Trump and his idea of a summit is to emerge with a bunch of business deals, even if they donโ€™t fundamentally change the nature of the relationship,โ€ Sanger explained. The predictable announcements would revolve around โ€œthe three Bs: beef, beans, and Boeing.โ€ These distinctly American exportsโ€”soybeans, aircraft, and specialty beefโ€”were items China often purchased anyway. They offered President Trump tangible โ€œdeliverablesโ€ to present to the American people, allowing him to declare โ€œthe biggest purchases ever,โ€ even if they were essentially commodities.

The true test, however, lay in the more contentious โ€œTโ€: tariffs. China had been a primary target of Trumpโ€™s tariff regime, making it a dominant discussion point. Yet, Xi Jinping likely felt he held a strong hand. China had previously demonstrated leverage by cutting off rare earths and magnets to the US in retaliation. Moreover, recent US Supreme Court and trade court decisions had forced the repayment of some collected tariffs and challenged the presidentโ€™s ability to impose sweeping duties.

One specific tariff issue of significant concern to China was the 100% tariff on Chinese cars entering the US, notably imposed by Joe Biden during his tenure. While China had globally exported 7 million cars last year, a million of which were destined for the US in Trumpโ€™s first term, the American market was now largely closed. Despite Chinaโ€™s push, a deal on this front was unlikely. The threat Chinese car production posed to American automakers mirrored the challenge Japan presented decades ago, making a significant concession politically unfeasible for the US.

These immediate trade tensions, while important, often overshadow the โ€œmuch more fundamental dividesโ€ that truly define the US-China relationship.

The Core Divides: A Battle for Global Dominance

Beneath the surface of trade deals and tariff disputes lies a profound โ€œdeath struggleโ€ for global dominance. President Xi Jinping has openly declared his ambition for China to be the worldโ€™s number one military, economic, political, and even cultural power by 2049. The central question for the United States, as Sanger articulated, is โ€œhow do you deal with a country thatโ€™s trying to displace you as the worldโ€™s number one power?โ€

The Nuclear Arms Race

One of the most concerning areas of this competition is nuclear weapons. For decades, China maintained a โ€œminimum nuclear deterrentโ€ of 100-200 weapons. However, under Xi, a massive buildup began, largely unnoticed by the US until years later. Today, China possesses approximately 600 nuclear weapons, with Pentagon estimates projecting 1,000 by 2030 and parity with the US and Russia by 2035.

This rapid expansion takes on critical significance following the expiration of the last remaining arms control treaty between Russia and the United States. President Trump, rightly, insisted that any new treaty must include China. Yet, the Chinese have firmly stated their disinterest in arms control discussions until they achieve an arsenal comparable in size to the US and Russia, refusing to negotiate from a perceived disadvantage. Trumpโ€™s stated intention to raise nuclear arms control with Xi was therefore unlikely to yield much progress.

The Taiwan Question

Taiwan remains a perennial flashpoint. President Xiโ€™s objective is to subtly shift US policy, making Taiwan more doubtful of American aid in the event of a Chinese takeover. This often manifests in seemingly minor โ€œwording changesโ€ in diplomatic language. For instance, American officials typically state they โ€œwould not support Taiwan declaring its own independence.โ€ The Chinese, however, desire a shift to โ€œoppose,โ€ a word carrying immense diplomatic weight, implying US recognition of the Peopleโ€™s Republic as the sole legitimate China and opposition to any challenge to that claim.

Despite the critical importance of Taiwanโ€”a major producer of advanced semiconductors through Taiwan Semiconductor Corporation (TSMC), essential for the AI revolutionโ€”President Trump has historically shown reluctance to fully engage on the issue. This creates a potential opening for Xi, who might offer guarantees on chip supply in exchange for a less robust US stance on the islandโ€™s broader autonomy.

The AI Arms Race: Uncharted Territory

Perhaps the most urgent and least understood challenge is the race for artificial intelligence dominance. The current discussions between world leaders on AI are โ€œpretty limited and pretty superficial,โ€ Sanger noted. Even basic agreements, like ensuring humans, not AI, control nuclear weapons, took months to negotiate during the Biden administration. The goal is to establish new forms of arms control for AI, recognizing that traditional methods of counting and inspecting physical weapons donโ€™t apply to algorithms and code. These would largely be โ€œcodes of conduct,โ€ inherently difficult to enforce.

Both the US and China are locked in a fierce competition to โ€œwin the AI battle,โ€ making them hesitant to implement restrictions that might hinder their own growth. Yet, the need for guardrails is undeniable. This urgency was underscored by the recent emergence of โ€œMythos,โ€ Anthropicโ€™s advanced AI product, which was deemed so effective at conducting offensive cyberattacksโ€”instantly finding vulnerabilities in utility grids and infrastructureโ€”that it was withheld from public release. While Mythos could also be used defensively, China is undoubtedly developing similar large language models, likely just months away from their own version.

This prospect deeply worries the administration, but a significant concern among American China experts is that top officials, distracted by the Middle East conflict, are โ€œill-preparedโ€ to tackle these complex AI issues.

The Shadow of Iran

The ongoing war in Iran fundamentally altered the conditions for this summit. President Trump had envisioned a swift resolution, with Iran capitulating and the Strait of Hormuz reopening. None of these outcomes materialized.

The Chinese have a profound economic interest in resolving the conflict, with over 30% of their oil and gas transiting the Strait of Hormuz. The soaring energy prices exacerbated by the war were devastating many Chinese enterprises, already struggling from a domestic economic slowdown. Trump would undoubtedly press Xi to stop supplying targeting data and technology to Iran for their missiles and interceptors. He would also urge China, as a major purchaser of Iranian goods, to use its influence to persuade Iran to reopen the strait. It remained to be seen whether the cautious President Xi, despite his strong interest in ending the war, would quietly intervene on the USโ€™s behalf.

Defining a โ€œWinโ€ in a High-Stakes Game

Given the complexity and urgency of these issues, what would constitute a โ€œwinโ€ for each leader at the end of the day?

For President Trump, a win would likely be measured in tangible business deals, allowing him to return home and declare success as the โ€œdealmaker-in-chief.โ€ This narrative, however, would sidestep the deeper, more fundamental questions of power and influence. It would also fail to address the perception, particularly after the Iran conflict, that the United States might not be as invincible as some leaders once believed.

For President Xi, the game is a longer one. He has little interest in individual deals beyond their utility in โ€œgreasing the wheels of diplomacy.โ€ Xiโ€™s primary objective is to demonstrate that China is the more stable, reliable power on the global stage. As he recently said in a veiled swipe at Trump, China is โ€œnot invading other countries or following the law of the jungle.โ€ His long-term plan is to show that the world will increasingly depend on Chinese power and capital to rebuild and establish new trading relationships. In this context, Xi might also seek to highlight any perceived lack of a coherent, long-term strategy from the United States.

Ultimately, this summit was less about immediate breakthroughs on the thorniest issues and more about a demonstration of strength, or perceived weakness, on a global stage where two superpowers are engaged in a relentless struggle for the future. The real outcomes would likely unfold not in the press conferences, but in the quiet shifts of diplomatic language and the strategic maneuvering that continues long after the leaders have departed Beijing.


ํ•œ๊ตญ์–ด

โ€œClaude Code Can Be Your Second Brainโ€ โ€” Every ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

ํด๋กœ๋“œ ์ฝ”๋“œ๋กœ ๊ตฌ์ถ•ํ•œ โ€˜๋ชจ๋ฐ”์ผ ์ œ2์˜ ๋‡Œโ€™: AI ๊ธฐ๋ฐ˜ ์‚ฌ๊ณ  ํ™•์žฅ๋ฒ•

๋…ธ์•„ ๋ธŒ๋ผ์ด์–ด(Noah Brier)๋Š” AI ์ „๋žต ์ปจ์„คํŒ… ๊ธฐ์—… ์•Œํ”ฝ(Alfik)์„ ์šด์˜ํ•˜๋ฉฐ, ํด๋กœ๋“œ ์ฝ”๋“œ(Claude Code)๋ฅผ ํ™œ์šฉํ•ด ์ž์‹ ๋งŒ์˜ ๋…ํŠนํ•œ โ€˜์ œ2์˜ ๋‡Œ(Second Brain)โ€™ ์‹œ์Šคํ…œ์„ ๊ตฌ์ถ•ํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ์˜ ์‹œ์Šคํ…œ์€ ๋‹จ์ˆœํžˆ ๋ฉ”๋ชจ๋ฅผ ์ •๋ฆฌํ•˜๋Š” ๊ฒƒ์„ ๋„˜์–ด, ๊นŠ์ด ์žˆ๋Š” ์‚ฌ๊ณ ์™€ ์—ฐ๊ตฌ, ๊ธ€์“ฐ๊ธฐ, ์‹ฌ์ง€์–ด ์ฝ”๋”ฉ๊นŒ์ง€ ์Šค๋งˆํŠธํฐ ํ•˜๋‚˜๋กœ ๊ฐ€๋Šฅํ•˜๊ฒŒ ๋งŒ๋“œ๋Š” ํ˜์‹ ์ ์ธ ์ ‘๊ทผ ๋ฐฉ์‹์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ์ด ๊ธฐ์‚ฌ๋Š” ๋…ธ์•„ ๋ธŒ๋ผ์ด์–ด๊ฐ€ ์–ด๋–ป๊ฒŒ ํด๋กœ๋“œ ์ฝ”๋“œ๋ฅผ ์ง„์ •ํ•œ โ€˜์‚ฌ๊ณ  ํŒŒํŠธ๋„ˆ(Thinking Partner)โ€˜๋กœ ํ™œ์šฉํ•˜๋ฉฐ, ๊ฐœ์ธ๊ณผ ์กฐ์ง์˜ ์ƒ์‚ฐ์„ฑ์„ ๊ทน๋Œ€ํ™”ํ•˜๋Š”์ง€ ๊ทธ์˜ ํ†ต์ฐฐ์„ ๊นŠ์ด ์žˆ๊ฒŒ ํƒ๊ตฌํ•ฉ๋‹ˆ๋‹ค.

์—๋ฒ„๋…ธํŠธ์—์„œ ์˜ต์‹œ๋””์–ธ, ๊ทธ๋ฆฌ๊ณ  ํด๋กœ๋“œ ์ฝ”๋“œ๋กœ: ์‚ฌ๊ณ  ๋„๊ตฌ์˜ ์ง„ํ™”

๋…ธ์•„ ๋ธŒ๋ผ์ด์–ด๋Š” ๊ณผ๊ฑฐ ์—๋ฒ„๋…ธํŠธ(Evernote)๋ฅผ ๋…์ฐฝ์ ์œผ๋กœ ํ™œ์šฉํ•˜๋ฉฐ โ€˜์‚ฌ๊ณ  ๋„๊ตฌ(Tools for Thought)โ€™ ๋ถ„์•ผ์—์„œ ์„ ๊ตฌ์ ์ธ ์•ˆ๋ชฉ์„ ๋ณด์—ฌ์คฌ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ทธ๋Š” ์ˆ˜๋งŽ์€ ์‚ฌ๋žŒ๋“ค๊ณผ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ ์—๋ฒ„๋…ธํŠธ๋ฅผ ๋– ๋‚˜ ์˜ต์‹œ๋””์–ธ(Obsidian)์œผ๋กœ ์ „ํ™˜ํ–ˆ์Šต๋‹ˆ๋‹ค. ์˜ต์‹œ๋””์–ธ์€ ๋ชจ๋“  ๋…ธํŠธ๊ฐ€ ๋งˆํฌ๋‹ค์šด(Markdown) ํŒŒ์ผ ํ˜•ํƒœ๋กœ ๋กœ์ปฌ์— ์ €์žฅ๋˜๋ฉฐ, ๊นƒ(Git)๊ณผ ๊ฐ™์€ ๋ฒ„์ „ ๊ด€๋ฆฌ ์‹œ์Šคํ…œ๊ณผ ์‰ฝ๊ฒŒ ์—ฐ๋™๋˜๋Š” ์žฅ์ ์ด ์žˆ์Šต๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ์˜ต์‹œ๋””์–ธ์˜ ์œ ์—ฐ์„ฑ์€ ๋…ธ์•„์˜ ํด๋กœ๋“œ ์ฝ”๋“œ ํ™œ์šฉ์— ํ•ต์‹ฌ์ ์ธ ๊ธฐ๋ฐ˜์ด ๋ฉ๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ง‘ ์ง€ํ•˜์‹ค์— ํ™ˆ ์„œ๋ฒ„(Home Server)๋ฅผ ๊ตฌ์ถ•ํ•˜๊ณ , ๊ทธ ์•ˆ์— ์˜ต์‹œ๋””์–ธ ๋ณผํŠธ(Obsidian Vault, ๋…ธํŠธ ์ €์žฅ์†Œ)๋ฅผ ๋„ฃ์–ด๋‘์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด ์˜ต์‹œ๋””์–ธ ์œ„์— ํด๋กœ๋“œ ์ฝ”๋“œ๋ฅผ ์‹คํ–‰์‹œ์ผœ, ์–ธ์ œ ์–ด๋””์„œ๋“  ์ž์‹ ์˜ ๋ชจ๋“  ๋…ธํŠธ์— ์ ‘๊ทผํ•˜๊ณ  AI์™€ ์ƒํ˜ธ์ž‘์šฉํ•  ์ˆ˜ ์žˆ๋Š” ํ™˜๊ฒฝ์„ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค. ํด๋กœ๋“œ ์ฝ”๋“œ์˜ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ์šฉ๋„๋Š” ๋ฐ”๋กœ ์ด ๋…ธํŠธ๋“ค๊ณผ์˜ ์ƒํ˜ธ์ž‘์šฉ์— ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ๋…ธ์•„๋Š” ์Šค๋งˆํŠธํฐ๋งŒ์œผ๋กœ๋„ ์ƒ๊ฐํ•˜๊ณ , ์—ฐ๊ตฌํ•˜๊ณ , ๊ธ€์„ ์“ฐ๊ณ , ์ฝ”๋“œ๋ฅผ ๋ฐฐํฌํ•˜๋Š” ๋“ฑ ์‹ฌ์ธต์ ์ธ ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•ฉ๋‹ˆ๋‹ค.

์†์•ˆ์˜ โ€˜์ƒ๊ฐํ•˜๋Š” ํŒŒํŠธ๋„ˆโ€™: AI ๊ธฐ๋ฐ˜ ๋ชจ๋ฐ”์ผ ์ƒ์‚ฐ์„ฑ์˜ ์žฌ์ •์˜

๋…ธ์•„๋Š” AI๊ฐ€ ๋ชจ๋ฐ”์ผ ํ™˜๊ฒฝ์—์„œ์˜ ์ƒ์‚ฐ์„ฑ์„ ํ˜์‹ ์ ์œผ๋กœ ๋ณ€ํ™”์‹œํ‚ค๊ณ  ์žˆ๋‹ค๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ๊ณผ๊ฑฐ ์Šค๋งˆํŠธํฐ์€ ๊ธ€์“ฐ๊ธฐ๋‚˜ ์ฝ”๋”ฉ ๊ฐ™์€ โ€˜์‹ฌ์ธต ์ž‘์—…(Deep Work)โ€˜์—๋Š” ์ ํ•ฉํ•˜์ง€ ์•Š์€ ๊ธฐ๊ธฐ๋กœ ์—ฌ๊ฒจ์กŒ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ AI๋Š” ์ด๋Ÿฌํ•œ ํ•œ๊ณ„๋ฅผ ๊ทน๋ณตํ•˜๊ณ  ํœด๋Œ€ํฐ์„ ์ง„์ •ํ•œ โ€˜์ƒ์ธต ์ž‘์—… ๋„๊ตฌโ€™๋กœ ํƒˆ๋ฐ”๊ฟˆ์‹œ์ผฐ์Šต๋‹ˆ๋‹ค.

ํŠนํžˆ ๊ทธ๋Š” ๊ทธ๋ก ์Œ์„ฑ ๋ชจ๋“œ(Grock Voice Mode)์˜ ํƒ์›”ํ•จ์— ๊นŠ์€ ์ธ์ƒ์„ ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ๊ทธ๋ก์˜ ์Œ์„ฑ ๋ชจ๋“œ๊ฐ€ ๋‹ค๋ฅธ AI ๋ชจ๋ธ(์ฑ—GPT, ์ œ๋ฏธ๋‚˜์ด ๋“ฑ)์˜ ์Œ์„ฑ ๋ชจ๋“œ๋ณด๋‹ค โ€œํ›จ์”ฌ ๋›ฐ์–ด๋‚˜๊ณ , ํ›จ์”ฌ ์Šค๋งˆํŠธํ•˜๋ฉฐ, ๋„๊ตฌ ํ˜ธ์ถœ(Tool Calling)๊ณผ ์—ฐ๊ตฌ ์ˆ˜ํ–‰ ๋Šฅ๋ ฅ์ด ์›”๋“ฑํ•˜๋‹คโ€๊ณ  ๋‹จ์–ธํ•ฉ๋‹ˆ๋‹ค. ํ…Œ์Šฌ๋ผ(Tesla) ์ฐจ๋Ÿ‰์— ๊ทธ๋ก์ด ๋‚ด์žฅ๋œ ์ดํ›„ ๋”์šฑ ํŽธ๋ฆฌํ•˜๊ฒŒ ์‚ฌ์šฉํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์‹ฌ์ง€์–ด ํ…Œ์Šฌ๋ผ์— ํƒ‘์žฌ๋˜๊ธฐ ์ „์—๋„ 5์‹œ๊ฐ„ ์šด์ „ ์ค‘ 2์‹œ๊ฐ„ ๋™์•ˆ ๊ทธ๋ก ์Œ์„ฑ ๋ชจ๋“œ๋ฅผ ํ†ตํ•ด ๊ธ€์˜ ์ฃผ์ œ๋ฅผ ์—ฐ๊ตฌํ•˜๊ณ  ์•„์ด๋””์–ด๋ฅผ ๋ฐœ์ „์‹œ์ผฐ๋˜ ๊ฒฝํ—˜์„ ๊ณต์œ ํ•ฉ๋‹ˆ๋‹ค.

โ€œ๋งˆ์น˜ ๋‚˜๋งŒ์„ ์œ„ํ•œ ํŒŸ์บ์ŠคํŠธ๋ฅผ ๋“ฃ๋Š” ๊ฒƒ ๊ฐ™์•„์š”. ๊ถ๊ธˆํ•œ ๋ชจ๋“  ๊ฒƒ์— ๋Œ€ํ•ด ๋งž์ถคํ˜• ์„ค๋ช…์„ ์ œ๊ณตํ•ด์ฃผ์ฃ .โ€ ๋…ธ์•„๋Š” ๊ทธ๋ก ์Œ์„ฑ ๋ชจ๋“œ๊ฐ€ ๋ณต์žกํ•œ ๊ฐœ๋…(์˜ˆ: ์…€ํ”„ ์–ดํ…์…˜(Self-Attention))์„ ์ดํ•ดํ•˜๋Š” ๋ฐ ์ตœ๊ณ ์˜ ์„ค๋ช…์„ ์ œ๊ณตํ–ˆ๋‹ค๊ณ  ๊ทน์ฐฌํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Š” ์šด์ „ ์ค‘์—๋„ ๋ฐœํ„ฐ ๋ฒค์•ผ๋ฏผ(Walter Benjamin)์˜ โ€˜์ด๋ฏธ์ง€์˜ ๋Œ€๋Ÿ‰ ์ƒ์‚ฐ(Mass Production of Images)โ€˜์— ๋Œ€ํ•œ ์•„์ด๋””์–ด๋ฅผ ํƒ์ƒ‰ํ•˜๊ณ , ๊ทธ์˜ ๋™์‹œ๋Œ€ ์‚ฌ์ƒ๊ฐ€๋“ค์„ ์—ฐ๊ตฌํ•˜๋Š” ๋“ฑ ๊นŠ์ด ์žˆ๋Š” ์‚ฌ๊ณ ์™€ ์—ฐ๊ตฌ๋ฅผ ๋Š์ž„์—†์ด ์ด์–ด๊ฐˆ ์ˆ˜ ์žˆ๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.

โ€˜์ƒ๊ฐ ๋ชจ๋“œโ€™์™€ โ€˜์ž‘์„ฑ ๋ชจ๋“œโ€™์˜ ๋ถ„๋ฆฌ: AI๋ฅผ ํ™œ์šฉํ•œ ์‹ฌ์ธต ์‚ฌ๊ณ ๋ฒ•

๋…ธ์•„๋Š” AI ๋ชจ๋ธ์„ ํ™œ์šฉํ•  ๋•Œ ๊ฐ€์žฅ ์ค‘์š”ํ•œ ํ†ต์ฐฐ ์ค‘ ํ•˜๋‚˜๋กœ โ€˜์ƒ๊ฐ ๋ชจ๋“œโ€™์™€ โ€˜์ž‘์„ฑ ๋ชจ๋“œโ€™๋ฅผ ๋ช…ํ™•ํžˆ ๋ถ„๋ฆฌํ•ด์•ผ ํ•œ๋‹ค๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ๋งŽ์€ ์‚ฌ๋žŒ๋“ค์ด AI๋ฅผ โ€˜์ƒ์„ฑํ˜•(Generative)โ€˜์ด๋ผ๊ณ  ๋ถ€๋ฅด๊ธฐ ๋•Œ๋ฌธ์—, AI๊ฐ€ ์ฆ‰์‹œ โ€˜๊ฒฐ๊ณผ๋ฌผ(Artifact)โ€˜์„ ๋งŒ๋“ค์–ด๋‚ด๋Š” ๋Šฅ๋ ฅ์—๋งŒ ์ดˆ์ ์„ ๋งž์ถฅ๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๋…ธ์•„๋Š” AI์˜ ์ง„์ •ํ•œ ๊ฐ€์น˜๊ฐ€ โ€˜์ฝ๋Š”(Reading)โ€™ ๋Šฅ๋ ฅ์— ์žˆ๋‹ค๊ณ  ์ฃผ์žฅํ•ฉ๋‹ˆ๋‹ค.

โ€œAI์˜ ์ฝ๋Š” ๋Šฅ๋ ฅ์€ ๋†€๋ž๊ณ , ์ผ์ƒ์ ์ธ ์ธก๋ฉด์—์„œ ํ›จ์”ฌ ๋” ์œ ์šฉํ•ฉ๋‹ˆ๋‹ค. ์šฐ๋ฆฌ๋Š” ๊ฒฐ๊ณผ๋ฌผ์„ ๋งŒ๋“ค์–ด๋‚ด๋Š” ๊ฒƒ๋ณด๋‹ค ์ƒ๊ฐํ•˜๋Š” ์‹œ๊ฐ„์ด ํ›จ์”ฌ ๋งŽ๊ธฐ ๋•Œ๋ฌธ์ด์ฃ .โ€

๊ทธ๋Š” AI๊ฐ€ ๋„ˆ๋ฌด ๋นจ๋ฆฌ ๊ธ€์“ฐ๊ธฐ๋‚˜ ์š”์•ฝ ๊ฐ™์€ ๊ฒฐ๊ณผ๋ฌผ ์ƒ์„ฑ์— ๋›ฐ์–ด๋“ค๋ ค๋Š” ๊ฒฝํ–ฅ์ด ์žˆ๋‹ค๊ณ  ์ง€์ ํ•˜๋ฉฐ, ์ด๋ฅผ ์ œ์–ดํ•˜๊ธฐ ์œ„ํ•ด ๋งค์šฐ ๊ตฌ์ฒด์ ์ธ ์ง€์‹œ๋ฅผ ๋‚ด๋ฆฝ๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ํด๋กœ๋“œ ์ฝ”๋“œ์—๊ฒŒ โ€œ์ง€๊ธˆ์€ ๊ธ€์“ฐ๊ธฐ๋ฅผ ๋„์™€์ฃผ์ง€ ๋งˆ๋ผ. ์˜ค์ง ์ƒ๊ฐํ•˜๊ณ  ์งˆ๋ฌธ์„ ๋˜์ ธ๋ผ. ๊ฐœ์š”๋‚˜ ์ดˆ์•ˆ์„ ๋งŒ๋“ค์ง€ ๋งˆ๋ผ. ์š”์ฒญ๋œ ์ž๋ฃŒ๋ฅผ ์ˆ˜์ง‘ํ•˜๊ณ  ์ •๋ฆฌํ•˜๋Š” ๋ฐ๋งŒ ์ง‘์ค‘ํ•˜๋ผโ€๊ณ  ๋ช…์‹œ์ ์œผ๋กœ ๋ช…๋ นํ•ฉ๋‹ˆ๋‹ค.

๊ทธ์˜ ์ž‘์—… ํ๋ฆ„์€ ๋‹ค์Œ๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค:

  1. ํ”„๋กœ์ ํŠธ ํด๋” ์ƒ์„ฑ: ์ƒˆ๋กœ์šด ๊ฐ•์—ฐ์ด๋‚˜ ๊ธ€์“ฐ๊ธฐ ํ”„๋กœ์ ํŠธ๊ฐ€ ์‹œ์ž‘๋˜๋ฉด, ์˜ต์‹œ๋””์–ธ์— ์ „์šฉ ํด๋”๋ฅผ ๋งŒ๋“ญ๋‹ˆ๋‹ค.
  2. ์ดˆ๊ธฐ ํ”„๋กฌํ”„ํŠธ: ํด๋กœ๋“œ ์ฝ”๋“œ์—๊ฒŒ ์ž์‹ ์ด โ€˜์ƒ๊ฐ ๋ชจ๋“œโ€™์— ์žˆ์œผ๋ฉฐ, ๊ณผ๊ฑฐ ๊ฐ•์—ฐ ์ž๋ฃŒ๋ฅผ ์ œ๊ณตํ•˜์—ฌ ์ž์‹ ์˜ ์Šคํƒ€์ผ์„ ์ดํ•ด์‹œํ‚ค๊ณ , ๊ฐ•์—ฐ์˜ ํ•ต์‹ฌ ์•„์ด๋””์–ด๋ฅผ ๊ณต์œ ํ•ฉ๋‹ˆ๋‹ค.
  3. ๊ธฐ์กด ์ง€์‹ ํ™œ์šฉ: ํด๋กœ๋“œ ์ฝ”๋“œ์—๊ฒŒ ์˜ต์‹œ๋””์–ธ ๋ณผํŠธ ์ „์ฒด(์•ฝ 1,500๊ฐœ์˜ ๋…ธํŠธ)๋ฅผ ๊ฒ€์ƒ‰ํ•˜์—ฌ ํ”„๋กœ์ ํŠธ์™€ ๊ด€๋ จ๋œ ๊ธฐ์กด ์—ฐ๊ตฌ ์ž๋ฃŒ๋‚˜ ๋…ธํŠธ๋ฅผ โ€˜์—ฐ๊ตฌ(Research)โ€™ ํด๋”๋กœ ๊ฐ€์ ธ์˜ค๋„๋ก ์ง€์‹œํ•ฉ๋‹ˆ๋‹ค. ์ด๋•Œ AI๋Š” ๋‹จ์ˆœํ•œ ํ‚ค์›Œ๋“œ ๊ฒ€์ƒ‰์„ ๋„˜์–ด, ๋…ธ์•„์˜ ๊ธฐ์กด ์‚ฌ๊ณ  ํ๋ฆ„๊ณผ ๊ด€๋ จ๋œ ์ž๋ฃŒ๋ฅผ ์ฐพ์•„๋‚ด๋Š” ๋ฐ ๋„์›€์„ ์ค๋‹ˆ๋‹ค.
  4. ์‚ฌ๊ณ  ํŒŒํŠธ๋„ˆ ์—์ด์ „ํŠธ ํ™œ์šฉ: ํด๋กœ๋“œ ์ฝ”๋“œ ๋‚ด์— โ€œ๋ณต์žกํ•œ ๋ฌธ์ œ๋ฅผ ํƒ์ƒ‰ํ•˜๋Š” ๋ฐ ํŠนํ™”๋œ ํ˜‘๋ ฅ์  ์‚ฌ๊ณ  ํŒŒํŠธ๋„ˆโ€ ์—ญํ• ์„ ํ•˜๋Š” ์„œ๋ธŒ ์—์ด์ „ํŠธ(Sub-agent)๋ฅผ ์ƒ์„ฑํ•ฉ๋‹ˆ๋‹ค. ์ด ์—์ด์ „ํŠธ๋Š” ๋…ธ์•„์—๊ฒŒ ๋‚ ์นด๋กœ์šด ์งˆ๋ฌธ์„ ๋˜์ง€๊ณ , ๊ทธ์˜ ์ƒ๊ฐ์„ ์ •๋ฆฌํ•˜๋ฉฐ, ํƒ์ƒ‰ ๊ณผ์ •์—์„œ ์–ป์€ ํ†ต์ฐฐ์„ ์ง€์†์ ์œผ๋กœ ๊ธฐ๋กํ•ฉ๋‹ˆ๋‹ค.
  5. ์™ธ๋ถ€ ๋Œ€ํ™” ํ†ตํ•ฉ: ์ฑ—GPT, ํด๋กœ๋“œ, ๊ทธ๋ก ๋“ฑ ๋‹ค๋ฅธ AI์™€ ๋‚˜๋ˆด๋˜ ๋Œ€ํ™” ๋‚ด์šฉ(์ „์ฒด ์Šคํฌ๋ฆฝํŠธ)์„ ์˜ต์‹œ๋””์–ธ ๋‚ด โ€˜๋Œ€ํ™”(Chats)โ€™ ํด๋”์— ํด๋ฆฌํ•‘ํ•˜์—ฌ ํด๋กœ๋“œ ์ฝ”๋“œ๊ฐ€ ์ฐธ๊ณ ํ•˜๋„๋ก ํ•ฉ๋‹ˆ๋‹ค. ์ด๋ฅผ ํ†ตํ•ด AI๋Š” ๋…ธ์•„์˜ ๋‹ค์–‘ํ•œ ์‚ฌ๊ณ  ๊ณผ์ •์„ ์ข…ํ•ฉ์ ์œผ๋กœ ์ดํ•ดํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
  6. ๋ฐ์ผ๋ฆฌ ์ง„ํ–‰ ์ƒํ™ฉ ๊ธฐ๋ก: ๋งค์ผ AI๊ฐ€ ๊ทธ๋‚  ์ƒ์„ฑ๋œ ๋ชจ๋“  ๋…ธํŠธ๋ฅผ ๊ฒ€ํ† ํ•˜๊ณ , ๊ฐ•์—ฐ ์ง„ํ–‰์— ๋„์›€์ด ๋˜๋Š” ํ•™์Šต ๋‚ด์šฉ๊ณผ ์•„์ด๋””์–ด๋ฅผ ์ •๋ฆฌํ•˜์—ฌ ๊ธฐ๋กํ•˜๋„๋ก ํ•ฉ๋‹ˆ๋‹ค.
  7. ํ๋ฆ„ ๋Š๊น€ ๋ฐฉ์ง€: ์—…๋ฌด ๋“ฑ์œผ๋กœ ์ธํ•ด ์ž‘์—… ํ๋ฆ„์ด ๋Š๊ฒผ์„ ๋•Œ, โ€œ์ง€๋‚œ ๋ฉฐ์น ๊ฐ„์˜ ์—ฐ๊ตฌ ๋‚ด์šฉ์„ ์š”์•ฝํ•ด๋‹ฌ๋ผโ€๊ณ  ์š”์ฒญํ•˜๋ฉด, AI๋Š” ํ•ด๋‹น ๊ธฐ๊ฐ„ ๋™์•ˆ์˜ ๋ชจ๋“  ๋…ธํŠธ๋ฅผ ์ฝ๊ณ  ์ฃผ์š” ํ†ต์ฐฐ๊ณผ ์ง„ํ–‰ ์ƒํ™ฉ์„ ์ •๋ฆฌํ•ด์ค๋‹ˆ๋‹ค. ์ด๋Š” ๋‹ค์‹œ ์ž‘์—…์— ๋ชฐ์ž…ํ•˜๋Š” ๋ฐ ํฐ ๋„์›€์„ ์ค๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ๊ณผ์ •์„ ํ†ตํ•ด ๋…ธ์•„๋Š” โ€˜ํŠธ๋žœ์Šคํฌ๋จธ๊ฐ€ ์„ธ์ƒ์„ ์ง‘์–ด์‚ผํ‚ค๊ณ  ์žˆ๋‹ค(Transformers are eating the world)โ€˜๋Š” ๊ทธ์˜ ํ•ต์‹ฌ ์•„์ด๋””์–ด(ํŠน์ˆ˜ ๋ชฉ์  ์ฝ”๋“œ๋ฅผ ๋Œ€์ฒดํ•˜๋Š” ํŠธ๋žœ์Šคํฌ๋จธ ๋ชจ๋ธ, ํ…Œ์Šฌ๋ผ๊ฐ€ ์‹ ๊ฒฝ๋ง์œผ๋กœ 30๋งŒ ์ค„์˜ ์ฝ”๋“œ๋ฅผ ์ œ๊ฑฐํ•œ ์‚ฌ๋ก€ ๋“ฑ)์™€ โ€˜๊ด€๋ฃŒ์ฃผ์˜(Bureaucracy)โ€˜์˜ ๋ณธ์งˆ, ๊ทธ๋ฆฌ๊ณ  OSS(์ „๋žต์‚ฌ๋ฌด๊ตญ) ์„ค๋ฆฝ์ž ์™€์ผ๋“œ ๋นŒ ๋„๋…ธ๋ฐ˜(Wild Bill Donovan)์˜ ๋ฆฌ๋”์‹ญ ์ฒ ํ•™์„ ์—ฎ๋Š” ๋ณต์žกํ•œ ๊ฐ•์—ฐ ์•„์ด๋””์–ด๋ฅผ ๊ตฌ์ฒดํ™”ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

AI, ์กฐ์ง ๊ด€๋ฃŒ์ฃผ์˜๋ฅผ ํ—ˆ๋ฌด๋Š” โ€˜ํ† ๋งˆ์Šค ์ž‰๊ธ€๋ฆฌ์‹œ ๋จธํ•€โ€™ ์ด๋ก 

๋…ธ์•„๋Š” AI๊ฐ€ ์กฐ์ง์˜ ๊ด€๋ฃŒ์ฃผ์˜๋ฅผ ํ•ด๊ฒฐํ•˜๋Š” ๋ฐ ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ•  ๊ฒƒ์ด๋ผ๋Š” ํฅ๋ฏธ๋กœ์šด ์ฒ ํ•™์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Š” ๊ด€๋ฃŒ์ฃผ์˜๊ฐ€ ํ•œ๋•Œ ๊ธฐ์—… ์šด์˜ ๋ฐฉ์‹์˜ ํ˜์‹ ์ด์—ˆ์œผ๋ฉฐ, ๋Œ€๊ทœ๋ชจ ์กฐ์ง ์šด์˜์— ํ•„์š”ํ•œ ๊ณ„์ธต๊ณผ ๊ตฌ์กฐ๋ฅผ ์ œ๊ณตํ–ˆ๋‹ค๊ณ  ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ˜„๋Œ€์— ์™€์„œ๋Š” ๋น„ํšจ์œจ๊ณผ ๊ฒฝ์ง์„ฑ์˜ ์ƒ์ง•์ด ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.

๊ณผ๊ฑฐ์˜ ๊ธฐ์ˆ ๋“ค์€ ์กฐ์ง์—๊ฒŒ ๊ธฐ์กด ๊ตฌ์กฐ๋ฅผ ์œ ์ง€ํ•˜๋ฉฐ ๊ธฐ์ˆ ์„ ํ†ตํ•ฉํ• ์ง€, ์•„๋‹ˆ๋ฉด ์ƒˆ๋กœ์šด ๊ตฌ์กฐ๋ฅผ ์ฑ„ํƒํ• ์ง€ ๊ฒฐ์ •ํ•˜๋„๋ก ๊ฐ•์š”ํ–ˆ์Šต๋‹ˆ๋‹ค. ๋Œ€๋ถ€๋ถ„์˜ ๊ฒฝ์šฐ ์ƒˆ๋กœ์šด ์†Œํ”„ํŠธ์›จ์–ด๋Š” ์ƒˆ๋กœ์šด ๊ตฌ์กฐ๋ฅผ ์š”๊ตฌํ–ˆ๊ณ , ์ด๋กœ ์ธํ•ด ๋งŽ์€ ์†Œํ”„ํŠธ์›จ์–ด ํ”„๋กœ์ ํŠธ๊ฐ€ ์‹คํŒจํ–ˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ AI๋Š” ๋‹ค๋ฆ…๋‹ˆ๋‹ค.

๋…ธ์•„๋Š” AI๋ฅผ โ€œํ† ๋งˆ์Šค ์ž‰๊ธ€๋ฆฌ์‹œ ๋จธํ•€(Thomasโ€™s English Muffin) ์ด๋ก โ€์— ๋น„์œ ํ•ฉ๋‹ˆ๋‹ค. ์ž‰๊ธ€๋ฆฌ์‹œ ๋จธํ•€์˜ โ€˜๋ˆ„ํฌ ์•ค ํฌ๋ž˜๋‹ˆ(nooks and crannies)โ€˜์ฒ˜๋Ÿผ, AI๋Š” ์กฐ์ง์˜ โ€˜ํ‹ˆ์ƒˆ์™€ ๊ท ์—ดโ€™ ์†์œผ๋กœ ํŒŒ๊ณ ๋“ค์–ด ๊ธฐ์กด์˜ ๋‹ค์–‘ํ•œ ์ž‘์—… ๋ฐฉ์‹์„ ๊ทธ๋Œ€๋กœ ์œ ์ง€ํ•˜๋ฉด์„œ๋„ ์ „์ฒด๋ฅผ ์—ฐ๊ฒฐํ•˜๋Š” โ€˜ํผ์ง€ ์ธํ„ฐํŽ˜์ด์Šค(Fuzzy Interface)โ€™ ์—ญํ• ์„ ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.

์˜ˆ๋ฅผ ๋“ค์–ด, ํ•œ ํŒ€์€ ์•„์‚ฌ๋‚˜(Asana)๋ฅผ, ๋‹ค๋ฅธ ํŒ€์€ ์ง€๋ผ(Jira)๋ฅผ, ๋˜ ๋‹ค๋ฅธ ํŒ€์€ ๋ฆฌ๋‹ˆ์–ด(Linear)๋ฅผ ์‚ฌ์šฉํ•˜๋Š” ํšŒ์‚ฌ์—์„œ ๊ธฐ์กด์—๋Š” ๋ชจ๋“  ํŒ€์ด ํ•˜๋‚˜์˜ ๋„๊ตฌ๋กœ ํ†ตํ•ฉ๋˜๋„๋ก ๊ฐ•์š”๋ฐ›์•˜์Šต๋‹ˆ๋‹ค. ์ด ๊ณผ์ •์—์„œ ๋งŽ์€ ํŒ€์ด ๋ถˆ๋งŒ์„ ๊ฐ€์กŒ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ AI๋Š” ๊ฐ ํŒ€์ด ์„ ํ˜ธํ•˜๋Š” ๋„๊ตฌ๋ฅผ ๊ณ„์† ์‚ฌ์šฉํ•˜๋„๋ก ํ—ˆ์šฉํ•˜๋ฉด์„œ๋„, ๋ชจ๋“  ๋ฐ์ดํ„ฐ๋ฅผ AI ๋ชจ๋ธ์ด ์ดํ•ดํ•  ์ˆ˜ ์žˆ๋Š” ๊ณตํ†ต ๊ตฌ์กฐ๋กœ ๋ณ€ํ™˜ํ•˜์—ฌ ์ค‘์•™์—์„œ ๊ด€๋ฆฌํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค. AI๋Š” ์–ด๋–ค ๋„๊ตฌ๋ฅผ ์‚ฌ์šฉํ•˜๋“  ์ƒ๊ด€ํ•˜์ง€ ์•Š๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ๊ธฐ์—…์šฉ ์†Œํ”„ํŠธ์›จ์–ด ๋„์ž…์˜ ๊ทผ๋ณธ์ ์ธ ๋ฌธ์ œ์˜€๋˜ โ€˜๋„์ž… ๋ฐ ๋ณ€ํ™” ๊ด€๋ฆฌ(Adoption and Change Management)โ€˜์˜ ๋ถ€๋‹ด์„ ํฌ๊ฒŒ ์ค„์—ฌ์ค„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

์—๋ธŒ๋ฆฌ(Every)์‚ฌ ๋‚ด๋ถ€์˜ ์‚ฌ๋ก€๋Š” ์ด๋Ÿฌํ•œ ๋…ธ์•„์˜ ์ด๋ก ์„ ๋’ท๋ฐ›์นจํ•ฉ๋‹ˆ๋‹ค. ์—๋ธŒ๋ฆฌ๋Š” 6๊ฐœ์˜ ์ œํ’ˆ์„ 15๋ช…์˜ ์ธ์›์œผ๋กœ ์šด์˜ํ•˜๋ฉฐ, ๊ฐ ์ œํ’ˆ๋งˆ๋‹ค ์„œ๋กœ ๋‹ค๋ฅธ ๊ธฐ์ˆ  ์Šคํƒ(๋ ˆ์ผ์ฆˆ, ํƒ€์ž…์Šคํฌ๋ฆฝํŠธ ๋“ฑ)์„ ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค. ์ตœ๊ทผ โ€˜์ŠคํŒŒํด(Sparkle)โ€˜์ด๋ผ๋Š” ํŒŒ์ผ ๊ฒ€์ƒ‰ ๋„๊ตฌ์™€ โ€˜ํŒŒ๋ผ(Parah)โ€˜๋ผ๋Š” ๋ฒ•๋ฅ  ๋ณด์กฐ AI ์ œํ’ˆ์„ ๊ฐœ๋ฐœํ•˜๋ฉด์„œ, ๋‘ ์ œํ’ˆ ๋ชจ๋‘ โ€˜๋น ๋ฅธ ํŒŒ์ผ ๊ฒ€์ƒ‰โ€™ ๊ธฐ๋Šฅ์ด ํ•„์š”ํ–ˆ์Šต๋‹ˆ๋‹ค.

๊ณผ๊ฑฐ๋ผ๋ฉด ์ŠคํŒŒํด์˜ ํŒŒ์ผ ๊ฒ€์ƒ‰ ๊ธฐ๋Šฅ์„ ์ถ”์ƒํ™”ํ•˜๊ณ  ๋ชจ๋“ˆํ™”ํ•˜์—ฌ ์žฌ์‚ฌ์šฉ ๊ฐ€๋Šฅํ•œ ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ๋กœ ๋งŒ๋“ค์–ด์•ผ ํ–ˆ์„ ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ์ƒ๋‹นํ•œ ์‹œ๊ฐ„๊ณผ ๋…ธ๋ ฅ์ด ๋“œ๋Š” ์ž‘์—…์ž…๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์—๋ธŒ๋ฆฌ๋Š” ๋Œ€์‹  ํŒŒ๋ผ ๊ฐœ๋ฐœ์ž๋ฅผ ์ŠคํŒŒํด ๋ ˆํฌ(Repo, ์ €์žฅ์†Œ)์— ์ถ”๊ฐ€ํ•˜๊ณ , ํด๋กœ๋“œ ์ฝ”๋“œ์—๊ฒŒ ์ŠคํŒŒํด์˜ ์ž‘๋™ ๋ฐฉ์‹์„ ํŒŒ์•…ํ•œ ํ›„ ํŒŒ๋ผ์— ๋งž๋Š” ์ž์ฒด ๋ฒ„์ „์„ ๋งŒ๋“ค๋„๋ก ์ง€์‹œํ–ˆ์Šต๋‹ˆ๋‹ค.

์ด์ฒ˜๋Ÿผ AI๋Š” ์„œ๋กœ ๋‹ค๋ฅธ ํ™˜๊ฒฝ๊ณผ ๋ฐฉ์‹์œผ๋กœ ์œ ์‚ฌํ•œ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋Š” ์—ฌ๋Ÿฌ ๋ ˆํฌ ์‚ฌ์ด์—์„œ โ€˜์•”๋ฌต์  ์ฝ”๋“œ ๊ณต์œ (Tacit Code Sharing)โ€˜๋ฅผ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค. AI๊ฐ€ ์ฝ”๋“œ๋ฅผ ๋ฒˆ์—ญํ•˜๊ณ  ์ดํ•ดํ•จ์œผ๋กœ์จ, ๊ฐœ๋ฐœ์ž๋“ค์€ ๋ณต์žกํ•œ ์ถ”์ƒํ™”๋‚˜ ๋ชจ๋“ˆํ™” ์ž‘์—… ์—†์ด๋„ ๋‹ค๋ฅธ ํŒ€์˜ ์ง€์‹๊ณผ ๊ฒฝํ—˜์„ ํ™œ์šฉํ•˜์—ฌ ์ƒ์‚ฐ์„ฑ์„ ๋†’์ผ ์ˆ˜ ์žˆ๊ฒŒ ๋œ ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๊ฒฐ๋ก : AI๋ฅผ ํ†ตํ•œ ์ง€์‹ ๊ด€๋ฆฌ ๋ฐ ์ƒ์‚ฐ์„ฑ์˜ ๋ฏธ๋ž˜

๋…ธ์•„ ๋ธŒ๋ผ์ด์–ด์˜ ์‚ฌ๋ก€๋Š” AI๊ฐ€ ๋‹จ์ˆœํ•œ ๋„๊ตฌ๋ฅผ ๋„˜์–ด ๊ฐœ์ธ์˜ ์‚ฌ๊ณ ์™€ ํ•™์Šต, ๊ทธ๋ฆฌ๊ณ  ์กฐ์ง์˜ ์ž‘๋™ ๋ฐฉ์‹๊นŒ์ง€ ํ˜์‹ ํ•  ์ˆ˜ ์žˆ๋Š” ์ž ์žฌ๋ ฅ์„ ๋ช…ํ™•ํžˆ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ํด๋กœ๋“œ ์ฝ”๋“œ๋ฅผ โ€˜์ œ2์˜ ๋‡Œโ€™์ด์ž โ€˜์‚ฌ๊ณ  ํŒŒํŠธ๋„ˆโ€™๋กœ ํ™œ์šฉํ•˜๋Š” ๊ทธ์˜ ๋ฐฉ์‹์€ ์šฐ๋ฆฌ๊ฐ€ AI๋ฅผ ์–ด๋–ป๊ฒŒ ํ™œ์šฉํ•ด์•ผ ํ•˜๋Š”์ง€์— ๋Œ€ํ•œ ์ค‘์š”ํ•œ ์ฒญ์‚ฌ์ง„์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค.

ํ•ต์‹ฌ์€ AI์˜ โ€˜์ƒ์„ฑโ€™ ๋Šฅ๋ ฅ๋ณด๋‹ค โ€˜์ดํ•ดโ€™ ๋Šฅ๋ ฅ์— ์ง‘์ค‘ํ•˜๊ณ , AI์—๊ฒŒ ๋ช…ํ™•ํ•œ ์—ญํ• ์„ ๋ถ€์—ฌํ•˜์—ฌ ์šฐ๋ฆฌ์˜ ์‚ฌ๊ณ  ๊ณผ์ •์„ ๋ณด์™„ํ•˜๋„๋ก ๋งŒ๋“œ๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๋˜ํ•œ, AI๋Š” ์กฐ์ง ๋‚ด ๋‹ค์–‘ํ•œ ์‹œ์Šคํ…œ๊ณผ ์ธ๊ฐ„์˜ ์ž‘์—… ๋ฐฉ์‹์„ ์—ฐ๊ฒฐํ•˜๋Š” ์œ ์—ฐํ•œ ์ธํ„ฐํŽ˜์ด์Šค๊ฐ€ ๋˜์–ด, ๋น„ํšจ์œจ์ ์ธ ๊ด€๋ฃŒ์ฃผ์˜๋ฅผ ์™„ํ™”ํ•˜๊ณ  โ€˜๋ณ€ํ™” ๊ด€๋ฆฌโ€™์˜ ๋ถ€๋‹ด ์—†์ด ์ƒ์‚ฐ์„ฑ์„ ํ–ฅ์ƒ์‹œํ‚ฌ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

AI๋Š” ๋” ์ด์ƒ ๋ฏธ๋ž˜์˜ ๊ธฐ์ˆ ์ด ์•„๋‹ˆ๋ผ, ์ง€๊ธˆ ๋ฐ”๋กœ ์šฐ๋ฆฌ์˜ ์ง€์‹ ๊ด€๋ฆฌ์™€ ์ƒ์‚ฐ์„ฑ์„ ์žฌ์ •์˜ํ•˜๋Š” ๊ฐ•๋ ฅํ•œ ๋™๋ฐ˜์ž์ž…๋‹ˆ๋‹ค. ๋…ธ์•„ ๋ธŒ๋ผ์ด์–ด์˜ ๊ฒฝํ—˜์€ ์ด๋Ÿฌํ•œ AI ์‹œ๋Œ€๋ฅผ ์‚ด์•„๊ฐ€๋Š” ์šฐ๋ฆฌ์—๊ฒŒ ๊นŠ์€ ์˜๊ฐ๊ณผ ์‹ค์šฉ์ ์ธ ์ง€์นจ์„ ์ œ๊ณตํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.


โ€œTwo Superpowers Across the Tableโ€ โ€” New York Times Podcasts ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

๊ฒฉ๋ž‘์˜ ์‹œ๋Œ€, ๋ฏธ์ค‘ ์ •์ƒํšŒ๋‹ด: ์ด๋ž€ ๊ฐˆ๋“ฑ๊ณผ ํŒจ๊ถŒ ๊ฒฝ์Ÿ ์† ํŠธ๋Ÿผํ”„์™€ ์‹œ์ง„ํ•‘์˜ ๋Œ€์ขŒ

๋‰ด์š•ํƒ€์ž„์ฆˆ ํŒŸ์บ์ŠคํŠธ โ€˜๋” ๋ฐ์ผ๋ฆฌ(The Daily)โ€˜๋Š” ์ตœ๊ทผ ๊ทผ 10๋…„ ๋งŒ์— ๋ฒ ์ด์ง•์—์„œ ์—ด๋ฆฐ ๋„๋„๋“œ ํŠธ๋Ÿผํ”„ ๋ฏธ๊ตญ ๋Œ€ํ†ต๋ น๊ณผ ์‹œ์ง„ํ•‘ ์ค‘๊ตญ ๊ตญ๊ฐ€์ฃผ์„์˜ ์ •์ƒํšŒ๋‹ด์„ ์‹ฌ์ธต ๋ถ„์„ํ•˜๋ฉฐ, ์ด ํšŒ๋‹ด์ด ๋‹จ์ˆœํ•œ ์™ธ๊ต์  ๋งŒ๋‚จ์„ ๋„˜์–ด์„  ๋ณต์žกํ•œ ์—ญํ•™ ๊ด€๊ณ„์™€ ๋ฏธ๋ž˜ ํŒจ๊ถŒ ๊ฒฝ์Ÿ์˜ ์ „์ดˆ์ „์ž„์„ ์กฐ๋ช…ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋ž€๊ณผ์˜ ๊ฐˆ๋“ฑ์— ๋ฐœ๋ชฉ ์žกํžŒ ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์ด ๊ณผ๊ฑฐ์™€๋Š” ํ™•์—ฐํžˆ ๋‹ฌ๋ผ์ง„ ์œ„์ƒ์œผ๋กœ ์ค‘๊ตญ์„ ์ฐพ์œผ๋ฉด์„œ, ๊ธฐ์ˆ ๋ถ€ํ„ฐ ๋ฌด์—ญ์— ์ด๋ฅด๊ธฐ๊นŒ์ง€ ๋ชจ๋“  ๋ถ„์•ผ์—์„œ ๋ฏธ๊ตญ์˜ ์ง€๋ฐฐ๋ ฅ์— ๊ฐ€์žฅ ํฐ ์œ„ํ˜‘์ด ๋˜๋Š” ์ค‘๊ตญ๊ณผ์˜ ๋Œ€๊ฒฐ์— ์ง๋ฉดํ–ˆ์Šต๋‹ˆ๋‹ค. ๋‰ด์š•ํƒ€์ž„์ฆˆ์˜ ๋ฐ์ด๋น„๋“œ ์ƒ์–ด(David Sanger) ๊ธฐ์ž๋Š” ์ด๋ฒˆ ํšŒ๋‹ด์—์„œ ๋ฌด์—‡์ด ๋…ผ์˜๋  ๊ฐ€๋Šฅ์„ฑ์ด ๋†’๊ณ , ๋” ์ค‘์š”ํ•˜๊ฒŒ๋Š” ๋ฌด์—‡์ด ๋…ผ์˜๋˜์ง€ ์•Š์„ ๊ฒƒ์ธ์ง€์— ๋Œ€ํ•œ ํ†ต์ฐฐ์„ ์ œ๊ณตํ–ˆ์Šต๋‹ˆ๋‹ค.

์ด๋ž€ ๊ฐˆ๋“ฑ์˜ ๊ทธ๋ฆผ์ž ์•„๋ž˜, ์•ฝํ™”๋œ ํŠธ๋Ÿผํ”„์˜ ์ž…์žฅ

2017๋…„๊ณผ ๋‹ฌ๋ผ์ง„ ์œ„์ƒ

2017๋…„, ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ์ค‘๊ตญ๊ณผ ์ „ ์„ธ๊ณ„๋ฅผ ๋†€๋ผ๊ฒŒ ํ•˜๋ฉฐ ๋Œ€ํ†ต๋ น์— ๋‹น์„ ๋œ ์งํ›„ ๋ฒ ์ด์ง•์„ ๋ฐฉ๋ฌธํ–ˆ์Šต๋‹ˆ๋‹ค. ๋‹น์‹œ ๊ทธ๋Š” ์ค‘๊ตญ์ด ๋งค์šฐ ๋Šฅ์ˆ™ํ•˜๊ฒŒ ํŽผ์น˜๋Š” ๋ชจ๋“  ํ™”๋ คํ•œ ์˜์ „๊ณผ ํ™˜์˜์„ ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค. ์‹œ ์ฃผ์„์€ โ€œํ™˜์ƒ์ ์ธ ํ™˜์˜์‹์— ๊ฐ์‚ฌ๋“œ๋ฆฐ๋‹คโ€๋Š” ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์˜ ๋ง์—์„œ ์•Œ ์ˆ˜ ์žˆ๋“ฏ, ์ตœ๊ณ ์˜ ์˜ˆ์šฐ๋ฅผ ๋ฒ ํ’€์—ˆ์Šต๋‹ˆ๋‹ค. ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ๋‹น์‹œ ์ค‘๊ตญ์ด ์ž์‹ ์˜ ๊ฒฝ์ œ ๋ฐ ๊ตญ๋ฐฉ ์ •์ฑ…๊ณผ ์–ด๋–ป๊ฒŒ ์—ฐ๊ด€๋ ์ง€ ๊ณ ๋ฏผํ•˜๊ธฐ ์‹œ์ž‘ํ–ˆ์œผ๋ฉฐ, ์ง€์  ์žฌ์‚ฐ๊ถŒ ๋ณดํ˜ธ์™€ ๊ณต์ •ํ•œ ๊ฒฝ์Ÿ ํ™˜๊ฒฝ ์กฐ์„ฑ์— ๋Œ€ํ•œ ๋ฏธ๊ตญ์˜ ์˜์ง€๋ฅผ ๊ฐ•์กฐํ•˜๋ฉด์„œ ์ค‘๊ตญ์˜ ๋ถ€์ƒ์„ ์ฃผ์š” ๊ฐ•๋Œ€๊ตญ์œผ๋กœ ์ธ์ •ํ•˜๋Š” ๋ถ„์œ„๊ธฐ์˜€์Šต๋‹ˆ๋‹ค.

๊ทธ๋Ÿฌ๋‚˜ ์ด๋ฒˆ ๋ฐฉ๋ฌธ์€ ์ƒํ™ฉ์ด ์™„์ „ํžˆ ๋‹ฌ๋ž์Šต๋‹ˆ๋‹ค. ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ๋ณธ๋ž˜ 4์›”์— ์ค‘๊ตญ์„ ๋ฐฉ๋ฌธํ•  ์˜ˆ์ •์ด์—ˆ์œผ๋‚˜, ์ด๋ž€๊ณผ์˜ ๊ฐˆ๋“ฑ์ด ์ค‘์ˆœ๊นŒ์ง€๋Š” ์ด๋ž€์˜ ํ•ญ๋ณต์œผ๋กœ ๋๋‚  ๊ฒƒ์ด๋ผ๋Š” ํ™•์‹  ์•„๋ž˜ 6์ฃผ ์—ฐ๊ธฐํ–ˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ทธ์˜ ์˜ˆ์ƒ์€ ๋น—๋‚˜๊ฐ”๊ณ , ์ด๋ž€์€ ์—ฌ์ „ํžˆ ์ €ํ•ญํ•˜๊ณ  ์žˆ์œผ๋ฉฐ ๋…์ผ์˜ ๋ฉ”๋ฅด์ธ  ์ด๋ฆฌ๋ฅผ ๋น„๋กฏํ•œ ๋‹ค๋ฅธ ์„ธ๊ณ„ ์ง€๋„์ž๋“ค์€ ์ด๋ž€์ด ๋ฏธ๊ตญ์„ ๊ตด์š•์‹œ์ผฐ๋‹ค๊ณ  ํ‰๊ฐ€ํ•˜๋Š” ์ƒํ™ฉ์ž…๋‹ˆ๋‹ค. ์ค‘๊ตญ ๋‚ด๋ถ€์—์„œ๋„ ๋ฏธ๊ตญ์ด ํ˜ธ๋ฅด๋ฌด์ฆˆ ํ•ดํ˜‘๊ณผ ๊ฐ™์€ ์ˆ˜์—ญ์„ ๊ฐœ๋ฐฉํ•˜๊ฑฐ๋‚˜ ์ด๋ž€๊ณผ ๊ฐ™์€ 2, 3๋ฅ˜ ๊ตญ๊ฐ€๋ฅผ ์ œ์••ํ•˜๋Š” ๋ฐ ์™œ ๊ทธ๋ ‡๊ฒŒ ์–ด๋ ค์›€์„ ๊ฒช๋Š”์ง€ ์˜์•„ํ•ดํ•˜๋Š” ๋ถ„์œ„๊ธฐ์ž…๋‹ˆ๋‹ค. ๋ชจ๋“  ์ •์ƒํšŒ๋‹ด์ด ๊ทธ๋ ‡๋“ฏ โ€˜์™ธ๊ด€(optics)โ€˜์ด ์ค‘์š”ํ•˜์ง€๋งŒ, ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ์ด๋ฒˆ ํšŒ๋‹ด์— ๋‹ค์†Œ ์•ฝํ™”๋œ ๋ชจ์Šต์œผ๋กœ ์ž„ํ•˜๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.

ํ˜ธ๋ฅด๋ฌด์ฆˆ ํ•ดํ˜‘๊ณผ ์ค‘๊ตญ์˜ ์˜๋ฌธ

ํ˜ธ๋ฅด๋ฌด์ฆˆ ํ•ดํ˜‘ ๋ฌธ์ œ๋Š” ํŠนํžˆ ์ค‘๊ตญ์—๊ฒŒ ํฐ ์˜๋ฌธ์œผ๋กœ ๋‹ค๊ฐ€์™”์Šต๋‹ˆ๋‹ค. ์ค‘๊ตญ์€ ์ด๋ž€์ด ๋ฏธ๊ตญ์˜ ์ œ์žฌ์™€ ๊ตฐ์‚ฌ์  ์••๋ ฅ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์—ฌ์ „ํžˆ ํ˜ธ๋ฅด๋ฌด์ฆˆ ํ•ดํ˜‘์„ ๋ด‰์‡„ํ•˜๋ฉฐ ์ €ํ•ญํ•˜๊ณ  ์žˆ๋Š” ์ƒํ™ฉ์„ ์ดํ•ดํ•˜๊ธฐ ์–ด๋ ต๊ฒŒ ์—ฌ๊น๋‹ˆ๋‹ค. ์„œ๋ฐฉ์˜ ์‹œ๊ฐ์—์„œ๋Š” ์ด๋ž€์ด โ€œ2๋ฅ˜ ๋˜๋Š” 3๋ฅ˜โ€ ๊ตญ๊ฐ€๋กœ ๋ถ„๋ฅ˜๋  ์ˆ˜ ์žˆ์Œ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ๋ฏธ๊ตญ์ด ์ด๋ž€์„ ์ƒ๋Œ€๋กœ ๋ช…ํ™•ํ•œ ์šฐ์œ„๋ฅผ ์ ํ•˜์ง€ ๋ชปํ•˜๋Š” ๋ชจ์Šต์€ ๋ฏธ๊ตญ์˜ ๊ตญ์ œ์  ์œ„์ƒ๊ณผ ๊ตฐ์‚ฌ๋ ฅ์— ๋Œ€ํ•œ ์˜๊ตฌ์‹ฌ์„ ์ž์•„๋ƒˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์˜ ์™ธ๊ต์  ์ž…์ง€๋ฅผ ๋”์šฑ ์•ฝํ™”์‹œํ‚ค๋Š” ์š”์ธ์œผ๋กœ ์ž‘์šฉํ–ˆ์Šต๋‹ˆ๋‹ค.

์ •์ƒํšŒ๋‹ด์˜ โ€˜์‰ฌ์šด ๊ณผ์ œโ€™: 3B ๋ฌด์—ญ ํ˜‘์ƒ

์†Œ๊ณ ๊ธฐ, ์ฝฉ, ๋ณด์ž‰ โ€“ ๋ฏธ๊ตญ์‚ฐ ์ˆ˜์ถœํ’ˆ

ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์ด ์ฐธ์—ฌํ•˜๋Š” ์ •์ƒํšŒ๋‹ด์˜ ๊ฐ€์žฅ ํ™•์‹คํ•œ ์˜์ œ๋Š” ํ•ญ์ƒ ๋ฌด์—ญ๊ณผ ๊ฒฝ์ œ ๊ด€๊ณ„์ž…๋‹ˆ๋‹ค. ์ด๋ฒˆ ํšŒ๋‹ด์—์„œ๋„ ์ค‘๊ตญ์˜ ๋Œ€๊ทœ๋ชจ ๊ตฌ๋งค ๋ฐœํ‘œ์™€ ์ž ์žฌ์ ์ธ ์‚ฌ์—… ๊ฑฐ๋ž˜ ๋ฐ ์–‘ํ•ด๊ฐ์„œ(MOU)๊ฐ€ ๊ธฐ๋Œ€๋ฉ๋‹ˆ๋‹ค. ๋ฐ์ด๋น„๋“œ ์ƒ์–ด ๊ธฐ์ž๋Š” ์ด๋ฅผ โ€œ๋‚ฎ๊ฒŒ ๋งค๋‹ฌ๋ฆฐ ๊ณผ์ผ(low-hanging fruit)โ€œ์ด๋ผ๊ณ  ํ‘œํ˜„ํ•˜๋ฉฐ, ์ด๋Ÿฌํ•œ ์•ˆ๊ฑด๋“ค์ด ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์ด ์–ด๋–ค ์ •์ƒํšŒ๋‹ด์—์„œ๋“  ์ถ”๊ตฌํ•˜๋Š” ์†์‰ฌ์šด ์„ฑ๊ณผ์ž„์„ ๊ฐ•์กฐํ–ˆ์Šต๋‹ˆ๋‹ค.

ํŠนํžˆ ์ฃผ๋ชฉ๋ฐ›๋Š” ๊ฒƒ์€ ์ด๋ฅธ๋ฐ” โ€˜3Bโ€™์ž…๋‹ˆ๋‹ค: ์†Œ๊ณ ๊ธฐ(Beef), ์ฝฉ(Beans), ๋ณด์ž‰(Boeing). ์ด๋“ค์€ ์ค‘๊ตญ์ด ์–ด์ฐจํ”ผ ๊ตฌ๋งคํ•ด์•ผ ํ•˜๊ฑฐ๋‚˜, ๋ฏธ๊ตญ์ด ์ฆ‰๊ฐ์ ์ธ ์„ฑ๊ณผ๋กœ ์ œ์‹œํ•˜๊ธฐ ์ข‹์€ ๋Œ€ํ‘œ์ ์ธ ๋ฏธ๊ตญ์‚ฐ ์ˆ˜์ถœํ’ˆ์ž…๋‹ˆ๋‹ค.

  • ์ฝฉ(Soybeans): ์ค‘๊ตญ์€ ์˜ค๋žซ๋™์•ˆ ๋ฏธ๊ตญ์‚ฐ ์ฝฉ์„ ๊ตฌ๋งคํ•ด์™”์ง€๋งŒ, ๊ฐ€๊ฒฉ์ด ๋น„์‹ธ๋‹ค๊ณ  ์—ฌ๊น๋‹ˆ๋‹ค.
  • ๋ณด์ž‰(Boeing): ์ค‘๊ตญ์€ ๋ณด์ž‰ ํ•ญ๊ณต๊ธฐ์— ์˜์กดํ•ด์™”์ง€๋งŒ, ์ด์ œ๋Š” ์ž์ฒด์ ์œผ๋กœ ํ›Œ๋ฅญํ•œ ํ•ญ๊ณต๊ธฐ๋ฅผ ์ƒ์‚ฐํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.
  • ์†Œ๊ณ ๊ธฐ(Beef): ์ค‘๊ตญ๋„ ์ž์ฒด ์†Œ๊ณ ๊ธฐ ์‚ฐ์—…์„ ์œก์„ฑํ•˜๊ณ  ์žˆ์ง€๋งŒ, ์—ฌ์ „ํžˆ ํŠน์ • ๋ฏธ๊ตญ์‚ฐ ๊ณ ๊ธ‰ ์†Œ๊ณ ๊ธฐ๋ฅผ ๊ตฌ๋งคํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ํ’ˆ๋ชฉ๋“ค์€ ์ค‘๊ตญ์ด ์–ด๋А ์ •๋„ ํ•„์š”๋กœ ํ•˜๋Š” ๊ฒƒ๋“ค์ด๊ธฐ์—, ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ์ด๋ฅผ ํ†ตํ•ด ๋ฏธ๊ตญ ๊ตญ๋ฏผ์—๊ฒŒ ์ฆ‰๊ฐ์ ์ธ ์„ฑ๊ณผ๋ฅผ ๋ณด์—ฌ์ค„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” โ€œ์—ญ๋Œ€ ์ตœ๋Œ€ ๊ตฌ๋งค๋Ÿ‰โ€์ด๋ผ๊ณ  ์„ ์–ธํ•  ํ…Œ์ง€๋งŒ, ๋ณธ์งˆ์ ์œผ๋กœ ์ด๋“ค์€ ์–‘๊ตญ์ด ๊ฐ€์žฅ ์‰ฝ๊ฒŒ ๊ฑฐ๋ž˜ํ•  ์ˆ˜ ์žˆ๋Š” ์ƒํ’ˆ๋“ค์ž…๋‹ˆ๋‹ค.

๊ด€์„ธ ๋ฌธ์ œ์™€ ์ค‘๊ตญ ์ž๋™์ฐจ

๋ฐ์ด๋น„๋“œ ์ƒ์–ด ๊ธฐ์ž๋Š” โ€˜3Bโ€™ ๋…ผ์˜์—์„œ ๊ด€์„ธ(Tariffs)๊ฐ€ ์–ธ๊ธ‰๋˜์ง€ ์•Š์€ ์ ์„ ์ง€์ ํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ด€์„ธ๋Š” ์ค‘๊ตญ์—๊ฒŒ ๋งค์šฐ ์ค‘์š”ํ•œ ๋ฌธ์ œ์ž…๋‹ˆ๋‹ค. ์ค‘๊ตญ์€ ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์˜ ๊ด€์„ธ ์ •์ฑ…์˜ ์ฃผ์š” ํ‘œ์ ์ด์—ˆ์œผ๋ฉฐ, ์ด๋Š” ์ด๋ฒˆ ํšŒ๋‹ด ๋…ผ์˜์˜ ์ƒ๋‹น ๋ถ€๋ถ„์„ ์ฐจ์ง€ํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ค‘๊ตญ์€ ์ด๋ฏธ ์ž‘๋…„์— ํฌํ† ๋ฅ˜์™€ ์ž์„ ์ˆ˜์ถœ์„ ์ค‘๋‹จํ•˜๋Š” ๋ณด๋ณต ์กฐ์น˜๋ฅผ ํ†ตํ•ด ๋ฏธ๊ตญ์— ์ƒ๋‹นํ•œ ์••๋ ฅ์„ ๊ฐ€ํ•˜์—ฌ ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์˜ ์ผ๋ถ€ ์ •์ฑ…์„ ํ›„ํ‡ด์‹œํ‚จ ๊ฒฝํ—˜์ด ์žˆ์Šต๋‹ˆ๋‹ค.

๋˜ํ•œ, ๋ฏธ๊ตญ ๋Œ€๋ฒ•์›์˜ ํŒ๊ฒฐ๋กœ ์ด๋ฏธ ์ง•์ˆ˜๋œ ์ผ๋ถ€ ๊ด€์„ธ๋ฅผ ํ™˜๊ธ‰ํ•ด์•ผ ํ–ˆ๊ณ , ์ตœ๊ทผ ๋ฌด์—ญ ๋ฒ•์›์˜ ํŒ๊ฒฐ์€ ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์ด ๋ชจ๋“  ๊ตญ๊ฐ€์— 10%์˜ ๊ด€์„ธ๋ฅผ ๋ถ€๊ณผํ•  ์ˆ˜ ์žˆ๋Š” ๋Šฅ๋ ฅ์— ์ œ๋™์„ ๊ฑธ์—ˆ์Šต๋‹ˆ๋‹ค. ์‹œ์ง„ํ•‘ ์ฃผ์„์€ ์ด๋ฏธ ์‹ธ์›€์˜ ์ ˆ๋ฐ˜์€ ์ด๊ธฐ๊ณ  ์‹œ์ž‘ํ•œ๋‹ค๊ณ  ๋А๋‚„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

ํŠนํžˆ ์ค‘๊ตญ์€ ํŠน์ • ํ’ˆ๋ชฉ์— ๋Œ€ํ•œ ๊ด€์„ธ, ๊ทธ์ค‘์—์„œ๋„ ์ค‘๊ตญ์‚ฐ ์ž๋™์ฐจ์— ๋Œ€ํ•œ ๊ด€์„ธ๋ฅผ ํฌ๊ฒŒ ์šฐ๋ คํ•ฉ๋‹ˆ๋‹ค. ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์˜ ์ฒซ ์ž„๊ธฐ ๋™์•ˆ ์ค‘๊ตญ์€ ์—ฐ๊ฐ„ ์•ฝ 100๋งŒ ๋Œ€์˜ ์ž๋™์ฐจ๋ฅผ ์ˆ˜์ถœํ–ˆ์ง€๋งŒ, ์ž‘๋…„์—๋Š” ์ „ ์„ธ๊ณ„์ ์œผ๋กœ 700๋งŒ ๋Œ€๋ฅผ ์ˆ˜์ถœํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ฏธ๊ตญ ์‹œ์žฅ์—์„œ๋Š” ์กฐ ๋ฐ”์ด๋“  ๋Œ€ํ†ต๋ น์ด 100%์˜ ๊ด€์„ธ๋ฅผ ๋ถ€๊ณผํ•˜์—ฌ ์‚ฌ์‹ค์ƒ ์ˆ˜์ถœ์ด ์ฐจ๋‹จ๋œ ์ƒํƒœ์ž…๋‹ˆ๋‹ค. ์ค‘๊ตญ์€ ์ด๋Ÿฌํ•œ ์ƒํ™ฉ์— ๋Œ€ํ•ด ๊ฐ•๋ ฅํžˆ ๋ถˆ๋งŒ์„ ์ œ๊ธฐํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ๋ฏธ๊ตญ ์‹œ์žฅ์œผ๋กœ์˜ ์ž๋™์ฐจ ์ˆ˜์ถœ ์žฌ๊ฐœ๋ฅผ ๊ฐ•๋ ฅํžˆ ์›ํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค.

ํ•˜์ง€๋งŒ ๋ฏธ๊ตญ์€ ์ด ๋ฌธ์ œ์—์„œ ์–‘๋ณดํ•˜์ง€ ์•Š์„ ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋ฉ๋‹ˆ๋‹ค. ์ˆ˜์‹ญ ๋…„ ์ „ ์ผ๋ณธ ์ž๋™์ฐจ๊ฐ€ ๊ทธ๋žฌ๋“ฏ์ด, ์ค‘๊ตญ์˜ ์ž๋™์ฐจ ์ƒ์‚ฐ ๋Šฅ๋ ฅ์€ ๋ฏธ๊ตญ ์ž๋™์ฐจ ์ œ์กฐ์—…์ฒด์— ์ƒ๋‹นํ•œ ์œ„ํ˜‘์ด ๋˜๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ด€์„ธ ๊ด€๋ จ ๋…ผ์˜๋Š” ๊ตญ๊ฐ€ ๊ฐ„์˜ ์ผ์ƒ์ ์ธ ๋ฌด์—ญ ๊ฐˆ๋“ฑ์˜ ์ผ๋ถ€์ด๋ฉฐ, ์ด๋ฒˆ ํšŒ๋‹ด์—์„œ ํ•ด๊ฒฐ๋  ์ˆ˜ ์žˆ๋Š” โ€œ์‰ฌ์šด ๊ณผ์ œโ€๋กœ ๋ถ„๋ฅ˜๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

ํ…Œ์ด๋ธ” ์•„๋ž˜ ๋†“์ธ ์ง„์งœ ์˜์ œ: ํŒจ๊ถŒ ๊ฒฝ์Ÿ์˜ ์‹ฌ์žฅ๋ถ€

์ •์ƒํšŒ๋‹ด์—์„œ ๋‹ค๋ค„์ง€๋Š” ์ฆ‰๊ฐ์ ์ธ ๋ฌด์—ญ ๋ฌธ์ œ ์™ธ์—๋„, ์–‘๊ตญ ๊ฐ„์—๋Š” ํ–ฅํ›„ ์ˆ˜์‹ญ ๋…„๊ฐ„ ๋ˆ„๊ฐ€ ์ง€๋ฐฐ์ ์ธ ๊ฒฝ์ œ, ๊ตฐ์‚ฌ, ๊ธฐ์ˆ  ๊ฐ•๊ตญ์ด ๋  ๊ฒƒ์ธ๊ฐ€ ํ•˜๋Š” ๊ทผ๋ณธ์ ์ธ ์งˆ๋ฌธ๊ณผ ๊ด€๋ จ๋œ ํ›จ์”ฌ ๋” ๊นŠ์€ ๋ถ„์—ด์ด ์กด์žฌํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ํ•ต์‹ฌ ์˜์ œ๋“ค์€ ์ง์ ‘์ ์ธ ํ˜•ํƒœ๋กœ ๋…ผ์˜๋˜์ง€ ์•Š์„ ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์Šต๋‹ˆ๋‹ค.

ํ•ต๋ฌด๊ธฐ ๊ฒฝ์Ÿ๊ณผ ๊ตฐ๋น„ ํ†ต์ œ

์ง€๋‚œ 10๋…„๊ฐ„ ๋ฏธ๊ตญ๊ณผ ์ค‘๊ตญ์€ โ€˜์น˜์—ดํ•œ ์‚ฌํˆฌโ€™๋ฅผ ๋ฒŒ์—ฌ์™”์Šต๋‹ˆ๋‹ค. ์‹œ์ง„ํ•‘ ์ฃผ์„์€ 2049๋…„๊นŒ์ง€ ์ค‘๊ตญ์„ ์„ธ๊ณ„ ์ตœ๊ณ ์˜ ๊ตฐ์‚ฌ, ๊ฒฝ์ œ, ์ •์น˜, ์‹ฌ์ง€์–ด ๋ฌธํ™” ๊ฐ•๊ตญ์œผ๋กœ ๋งŒ๋“ค๊ฒ ๋‹ค๋Š” ๋ชฉํ‘œ๋ฅผ ์ˆจ๊ธฐ์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋งฅ๋ฝ์—์„œ ์ค‘๊ตญ์˜ ํ•ต๋ฌด๊ธฐ ์ฆ๊ฐ•์€ ๋ฏธ๊ตญ์˜ ๊ทผ๋ณธ์ ์ธ ์šฐ๋ ค ์‚ฌํ•ญ์ž…๋‹ˆ๋‹ค.

๋งˆ์˜ค์ฉŒ๋‘ฅ ์‹œ๋Œ€ ์ดํ›„ ์ˆ˜์‹ญ ๋…„ ๋™์•ˆ ์ค‘๊ตญ์€ ์ตœ์†Œํ•œ์˜ ํ•ต ์–ต์ง€๋ ฅ์„ ์œ ์ง€ํ•˜๋ฉฐ 100~200๊ธฐ์˜ ํ•ต๋ฌด๊ธฐ๋ฅผ ๋ณด์œ ํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹œ์ง„ํ•‘ ์ฃผ์„ ์ง‘๊ถŒ ์ดํ›„ ์ค‘๊ตญ์€ ๋Œ€๊ทœ๋ชจ ํ•ต๋ฌด๊ธฐ ์ฆ๊ฐ•์„ ์‹œ์ž‘ํ–ˆ์œผ๋ฉฐ, ๋ฏธ๊ตญ์€ ์ˆ˜๋…„์ด ์ง€๋‚˜์„œ์•ผ ์ด๋ฅผ ์™„์ „ํžˆ ์ธ์ง€ํ–ˆ์Šต๋‹ˆ๋‹ค. ํ˜„์žฌ ์ค‘๊ตญ์€ ์•ฝ 600๊ธฐ์˜ ํ•ต๋ฌด๊ธฐ๋ฅผ ๋ณด์œ ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ๋ฏธ๊ตญ ๊ตญ๋ฐฉ๋ถ€(Pentagon)๋Š” 2030๋…„๊นŒ์ง€ ์•ฝ 1,000๊ธฐ, 2035๋…„๊นŒ์ง€๋Š” ๋ฏธ๊ตญ๊ณผ ๋Ÿฌ์‹œ์•„ ์ˆ˜์ค€์˜ ํ•ต๋ฌด๊ธฐ๋ฅผ ๋ณด์œ ํ•  ๊ฒƒ์œผ๋กœ ์ถ”์ •ํ•ฉ๋‹ˆ๋‹ค.

์ด๊ฒƒ์ด ์ค‘์š”ํ•œ ์ด์œ ๋Š” ๋ช‡ ๋‹ฌ ์ „ ๋Ÿฌ์‹œ์•„์™€ ๋ฏธ๊ตญ ๊ฐ„์˜ ๋งˆ์ง€๋ง‰ ๊ตฐ๋น„ ํ†ต์ œ ์กฐ์•ฝ์ด ๋งŒ๋ฃŒ๋˜์—ˆ๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ์ค‘๊ตญ์ด ํ•ฉ์˜์— ์ฐธ์—ฌํ•˜์ง€ ์•Š๋Š” ํ•œ ์ƒˆ๋กœ์šด ์กฐ์•ฝ์„ ํ˜‘์ƒํ•˜๋Š” ๊ฒƒ์€ ๋ฌด์˜๋ฏธํ•˜๋‹ค๊ณ  ์ฃผ์žฅํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ค‘๊ตญ์€ ์ž์‹ ๋“ค์ด ๋ฏธ๊ตญ๊ณผ ๋Œ€๋“ฑํ•œ ์ˆ˜์ค€์˜ ํ•ต๋ฌด๊ธฐ๋ฅผ ๋ณด์œ ํ•˜๊ธฐ ์ „๊นŒ์ง€๋Š” ๊ตฐ๋น„ ํ†ต์ œ์— ๊ด€์‹ฌ์„ ๋‘์ง€ ์•Š๊ฒ ๋‹ค๋Š” ์ž…์žฅ์„ ๊ณ ์ˆ˜ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ์‹œ ์ฃผ์„์—๊ฒŒ ํ•ต ๊ตฐ๋น„ ํ†ต์ œ ๋ฌธ์ œ๋ฅผ ์ œ๊ธฐํ•  ๊ณ„ํš์ด์ง€๋งŒ, ์ค‘๊ตญ์ด ๋…ผ์˜ํ•  ์ค€๋น„๊ฐ€ ๋˜์–ด ์žˆ์ง€ ์•Š์•„ ํฐ ์ง„์ „์„ ์ด๋ฃจ๊ธฐ๋Š” ์–ด๋ ค์šธ ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๋Œ€๋งŒ์˜ ๋ฏธ๋ž˜์™€ ๋ฏธ๊ตญ์˜ โ€˜๋ง ๋ฐ”๊พธ๊ธฐโ€™

์ค‘๊ตญ์ด ๋…ผ์˜ํ•  ์ค€๋น„๊ฐ€ ๋˜์–ด ์žˆ๋Š” ์ฃผ์ œ๋Š” ๋ฐ”๋กœ ๋Œ€๋งŒ(Taiwan)๊ณผ ๋Œ€๋งŒ์˜ ์กด์žฌ๊ถŒ์ž…๋‹ˆ๋‹ค. ์‹œ์ง„ํ•‘ ์ฃผ์„์€ ๋ฏธ๊ตญ์ด ์‹œ๊ฐ„์ด ์ง€๋‚จ์— ๋”ฐ๋ผ ์ค‘๊ตญ์ด ๋Œ€๋งŒ์„ ์žฅ์•…ํ•˜๋Š” ๊ฒƒ์— ๋Œ€ํ•ด ๋” ๊ฐœ๋ฐฉ์ ์ธ ์ž…์žฅ์„ ์ทจํ•˜๊ณ  ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ฃผ๊ธฐ ์œ„ํ•ด ๋ชจ๋“  ๋…ธ๋ ฅ์„ ๋‹คํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ฆ‰๊ฐ์ ์ธ ๋Œ€๋งŒ ์นจ๊ณต์„ ์œ„ํ•œ ์ดˆ๋Œ€๋ฅผ ๊ธฐ๋Œ€ํ•˜์ง€ ์•Š์ง€๋งŒ, ๋Œ€๋งŒ์ธ๋“ค์ด ๋ฏธ๊ตญ์˜ ์ง€์›์— ๋Œ€ํ•ด ๋” ์˜๊ตฌ์‹ฌ์„ ๊ฐ–๊ฒŒ ํ•  ์ˆ˜ ์žˆ๋Š” โ€œ๋ฏธ๋ฌ˜ํ•œ ๋ฌธ๊ตฌ ๋ณ€๊ฒฝโ€์„ ์ถ”๊ตฌํ•ฉ๋‹ˆ๋‹ค.

๊ฐ€์žฅ ํ”ํžˆ ์–ธ๊ธ‰๋˜๋Š” ์˜ˆ์‹œ๋Š” ๋ฏธ๊ตญ ๊ด€๋ฆฌ๋“ค์ด ๋Œ€๋งŒ์˜ ๋…๋ฆฝ ์„ ์–ธ์„ โ€œ์ง€์ง€ํ•˜์ง€ ์•Š๋Š”๋‹ค(not support)โ€œ๊ณ  ๋งํ•˜๋Š” ๊ฒƒ์„ ์ค‘๊ตญ์ด โ€œ๋ฐ˜๋Œ€ํ•œ๋‹ค(oppose)โ€œ๋กœ ๋ฐ”๊พธ๊ธฐ๋ฅผ ์›ํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ์ž‘์€ ๋ณ€ํ™”์ฒ˜๋Ÿผ ๋“ค๋ฆฌ์ง€๋งŒ, ์™ธ๊ต์ ์œผ๋กœ๋Š” ์—„์ฒญ๋‚œ ์˜๋ฏธ๋ฅผ ๊ฐ€์ง‘๋‹ˆ๋‹ค. โ€œ๋ฐ˜๋Œ€ํ•œ๋‹คโ€๋Š” ๊ฒƒ์€ ๋ฏธ๊ตญ์ด ์œ ์ผํ•œ ์ง„์ •ํ•œ ์ค‘๊ตญ์€ ์ค‘ํ™”์ธ๋ฏผ๊ณตํ™”๊ตญ์ด๋ฉฐ, ์ด์— ๋„์ „ํ•˜๋ ค๋Š” ์–ด๋–ค ๋…ธ๋ ฅ๋„ ๋ฐ˜๋Œ€ํ•œ๋‹ค๋Š” ํŠน์ • ๊ฒฌํ•ด๋ฅผ ์ทจํ•  ๊ฒƒ์ž„์„ ์˜๋ฏธํ•˜๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ โ€œ๋ง ๋ฐ”๊พธ๊ธฐโ€๋Š” ์‹ค์ œ์ ์ธ ํ–‰๋™์ด ์•„๋‹ˆ๋”๋ผ๋„ ๋Œ€๋งŒ์—๊ฒŒ๋Š” ํฐ ์œ„ํ˜‘์œผ๋กœ ๋‹ค๊ฐ€์˜ฌ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์˜ ์ฆ‰ํฅ์ ์ธ(freelance) ์„ฑํ–ฅ์„ ๊ณ ๋ คํ•  ๋•Œ, ์ค‘๊ตญ์€ ๊ทธ๊ฐ€ ์ด ๋ฌธ์ œ์—์„œ ์˜ˆ์ƒ์น˜ ๋ชปํ•œ ๋ฐœ์–ธ์„ ํ•˜๊ธฐ๋ฅผ ๋ฐ”๋ž„ ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๋Œ€๋งŒ์€ ๋˜ํ•œ ์ธ๊ณต์ง€๋Šฅ(AI) ๊ด€๋ จ ํ•ต์‹ฌ ๊ธฐ์ˆ ์ธ ๋ฐ˜๋„์ฒด ์นฉ์˜ ์ฃผ์š” ์ƒ์‚ฐ๊ตญ์ž…๋‹ˆ๋‹ค. ์„ธ๊ณ„์—์„œ ๊ฐ€์žฅ ๋ฐœ์ „๋œ ๋ฐ˜๋„์ฒด ์ œ์กฐ์—…์ฒด์ธ ๋Œ€๋งŒ ๋ฐ˜๋„์ฒด ํšŒ์‚ฌ(Taiwan Semiconductor Corporation, TSMC)์˜ ์‹œ์„ค์€ ๋Œ€๋งŒ์— ์ง‘์ค‘๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค. AI ํ˜๋ช…์˜ ํ•ต์‹ฌ์ธ AI ์นฉ ์ƒ์‚ฐ์„ ์œ„ํ•ด ๋ฏธ๊ตญ์€ TSMC์˜ ์ƒ์‚ฐ์— ์˜์กดํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์‹œ์ง„ํ•‘ ์ฃผ์„์€ ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์—๊ฒŒ ์นฉ ๊ณต๊ธ‰์„ ๋ณด์žฅํ•˜๋ฉฐ ๋Œ€๋งŒ ์„ฌ์˜ ๋‚˜๋จธ์ง€ ๋ถ€๋ถ„์— ๋Œ€ํ•ด์„œ๋Š” ์‹ ๊ฒฝ ์“ฐ์ง€ ์•Š๋„๋ก ์œ ๋„ํ•  ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค.

AI ํŒจ๊ถŒ ์ „์Ÿ๊ณผ โ€˜๋ฏธํ† ์Šคโ€™์˜ ๊ฒฝ๊ณ 

AI๋Š” ํ•ต๋ฌด๊ธฐ๋‚˜ ๋Œ€๋งŒ ๋ฌธ์ œ๋ณด๋‹ค ํ›จ์”ฌ ๋” ์‹œ๊ธ‰ํ•˜๊ฒŒ ๋А๊ปด์ง€๋Š” ์ „ ์„ธ๊ณ„์ ์ธ ๊ด€์‹ฌ์‚ฌ์ž…๋‹ˆ๋‹ค. ์ด ๊ธฐ์ˆ ์€ ์šฐ๋ฆฌ์˜ ์•ˆ๋ณด, ์‹ฌ์ง€์–ด ์ดํ•ด๋ฅผ ๋„˜์–ด์„œ ๋น ๋ฅด๊ฒŒ ๋ฐœ์ „ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์–‘๊ตญ ์ •์ƒ ๊ฐ„์˜ AI ๊ด€๋ จ ๋…ผ์˜๋Š” ๋งค์šฐ ์ œํ•œ์ ์ด๊ณ  ํ”ผ์ƒ์ ์ผ ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์Šต๋‹ˆ๋‹ค. ๋ฐ”์ด๋“  ํ–‰์ •๋ถ€ ์‹œ์ ˆ์—๋„ ๋ฏธ๊ตญ๊ณผ ์ค‘๊ตญ์ด ํ•ต๋ฌด๊ธฐ๊ฐ€ ์ธ๊ณต์ง€๋Šฅ ํ”„๋กœ๊ทธ๋žจ์— ์˜ํ•ด ์ง€์‹œ๋˜์ง€ ์•Š๋„๋ก ํ•ฉ์˜ํ•˜๋Š” ๋ฐ ์ˆ˜๊ฐœ์›”์ด ๊ฑธ๋ ธ์Šต๋‹ˆ๋‹ค.

AI ์‹œ๋Œ€์—๋Š” ํ•ต ์‹œ๋Œ€์˜ ๊ตฐ๋น„ ํ†ต์ œ ๋ฐฉ์‹์ด ์ž˜ ์ ์šฉ๋˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค. AI๋Š” ์‰ฝ๊ฒŒ ๊ฒ€์‚ฌํ•˜๊ฑฐ๋‚˜ ์ˆ˜๋ฅผ ์„ธ๊ฑฐ๋‚˜ ํ†ต์ œํ•  ์ˆ˜ ์žˆ๋Š” ํŠน์ • ๋ฌด๊ธฐ๊ฐ€ ์•„๋‹ˆ๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ๋”ฐ๋ผ์„œ AI์— ๋Œ€ํ•œ ํ†ต์ œ๋Š” ์ฃผ๋กœ ๊ฐ•์ œํ•˜๊ธฐ ์–ด๋ ค์šด ํ–‰๋™ ๊ฐ•๋ น(codes of conduct)์˜ ํ˜•ํƒœ๊ฐ€ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์–‘๊ตญ ์ง€๋„์ž๋“ค์ด ์ด ์ฃผ์ œ๋ฅผ ์–ธ๊ธ‰ํ•˜๊ฑฐ๋‚˜ ์‹ค๋ฌด์ง„์—๊ฒŒ ๋…ผ์˜๋ฅผ ์ง€์‹œํ• ์ง€์กฐ์ฐจ ๋ถˆํ™•์‹คํ•ฉ๋‹ˆ๋‹ค.

๋ฏธ๊ตญ๊ณผ ์ค‘๊ตญ ๋ชจ๋‘ AI ํŒจ๊ถŒ ๊ฒฝ์Ÿ์—์„œ ์Šน๋ฆฌํ•˜๊ธฐ ์œ„ํ•ด ์ „๋ ฅํˆฌ๊ตฌํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฒฝ์Ÿ ๋•Œ๋ฌธ์— ์–‘๊ตญ ๋ชจ๋‘ ์„ฑ์žฅ์„ ์ œํ•œํ•  ์–ด๋–ค ์กฐ์น˜๋„ ์ทจํ•˜๊ณ  ์‹ถ์–ด ํ•˜์ง€ ์•Š์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์–‘๊ตญ ๋ชจ๋‘ ์ƒ๋Œ€๋ฐฉ์— ๋Œ€ํ•œ ์ผ์ข…์˜ ์•ˆ์ „์žฅ์น˜(guardrails)๋ฅผ ๋งˆ๋ จํ•˜๋Š” ๋ฐ ์ดํ•ด๊ด€๊ณ„๊ฐ€ ์žˆ๋‹ค๋Š” ๊ฒƒ์€ ๋ถ„๋ช…ํ•ด ๋ณด์ž…๋‹ˆ๋‹ค.

ํŠธ๋Ÿผํ”„ ํ–‰์ •๋ถ€๋Š” ์ฒ˜์Œ์—๋Š” โ€œํ•œ ๊ตญ๊ฐ€๊ฐ€ ์ด ๊ฒฝ์Ÿ์—์„œ ์Šน๋ฆฌํ•  ๊ฒƒ์ด๋ฉฐ, ์ด๋Š” ์‚ฐ์—…์ด ๊ทœ์ œ ์—†์ด ์ž์œ ๋กญ๊ฒŒ ํ™œ๋™ํ•˜๋„๋ก ํ—ˆ์šฉํ•˜๋Š” ๊ตญ๊ฐ€๊ฐ€ ๋  ๊ฒƒโ€์ด๋ผ๋Š” ์ž…์žฅ์ด์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ตœ๊ทผ ๋ช‡ ์ฃผ ๋™์•ˆ ์ด๋Ÿฌํ•œ ํƒœ๋„๋Š” ๋ณ€ํ™”ํ–ˆ์Šต๋‹ˆ๋‹ค. ๋ณ€ํ™”์˜ ๊ณ„๊ธฐ๋Š” ์ธ๊ณต์ง€๋Šฅ ๊ธฐ์—… ์•คํŠธ๋กœํ”ฝ(Anthropic)์ด ๊ฐœ๋ฐœํ•œ โ€˜๋ฏธํ† ์Šค(Mythos)โ€˜๋ผ๋Š” ๊ฐ€์ƒ์˜ ์ œํ’ˆ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ์ด ์ œํ’ˆ์€ ๊ณต๊ฒฉ์ ์ธ ์‚ฌ์ด๋ฒ„ ๊ณต๊ฒฉ์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐ ๋งค์šฐ ํšจ๊ณผ์ ์ด์–ด์„œ ๋Œ€์ค‘์—๊ฒŒ ๊ณต๊ฐœ๋˜์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค. ๋ฏธํ† ์Šค๋Š” ์œ ํ‹ธ๋ฆฌํ‹ฐ ๊ทธ๋ฆฌ๋“œ๋‚˜ ๋‹ค๋ฅธ ์ธํ”„๋ผ ์ฝ”๋“œ์˜ ์ทจ์•ฝ์ ์„ ๊ฑฐ์˜ ์ฆ‰์‹œ ์ฐพ์•„๋‚ด ๊ณต๊ฒฉ์„ ๋ช…๋ นํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ฌผ๋ก  ์ด๋Š” ๋ฐฉ์–ด์—๋„ ์œ ์šฉํ•  ์ˆ˜ ์žˆ์ง€๋งŒ, ์ค‘๊ตญ ์—ญ์‹œ ๋ฏธํ† ์Šค์™€ ์œ ์‚ฌํ•œ ๋Œ€๊ทœ๋ชจ ์–ธ์–ด ๋ชจ๋ธ์„ ๊ฐœ๋ฐœ ์ค‘์ด๋ฉฐ, 6๊ฐœ์›”์—์„œ 1๋…„ ์•ˆ์— ์ž์ฒด์ ์ธ ๋ฏธํ† ์Šค๋ฅผ ๊ฐ–๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ๋ฏธ๊ตญ ํ–‰์ •๋ถ€๋ฅผ ์‹ฌ๊ฐํ•˜๊ฒŒ ์šฐ๋ คํ•˜๊ฒŒ ๋งŒ๋“ค ์‚ฌ์•ˆ์ž…๋‹ˆ๋‹ค. ๋งŽ์€ ๋ฏธ๊ตญ ๋‚ด ์ค‘๊ตญ ์ „๋ฌธ๊ฐ€๋“ค์€ ํŠธ๋Ÿผํ”„ ํ–‰์ •๋ถ€ ๊ณ ์œ„ ๊ด€๋ฆฌ๋“ค์ด ์ค‘๋™ ์‚ฌํƒœ์— ๋„ˆ๋ฌด ๋ชฐ๋‘ํ•˜์—ฌ ์ด๋ฒˆ ํšŒ๋‹ด์— ์ œ๋Œ€๋กœ ์ค€๋น„๋˜์ง€ ์•Š์€ ์ƒํƒœ๋กœ ์ž„ํ•˜๊ณ  ์žˆ๋‹ค๋Š” ์ ์„ ์šฐ๋ คํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

์ด๋ž€ ์‚ฌํƒœ, ์ •์ƒํšŒ๋‹ด์˜ ์˜ˆ์ƒ์น˜ ๋ชปํ•œ ๋ณ€์ˆ˜

ํ˜ธ๋ฅด๋ฌด์ฆˆ ํ•ดํ˜‘ ๊ฐœ๋ฐฉ์˜ ์ ˆ๋ฐ•ํ•จ

ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ํšŒ๋‹ด์„ 6์ฃผ ์—ฐ๊ธฐํ•  ๋•Œ, ์ „์Ÿ์ด ๋๋‚˜๊ณ  ์ด๋ž€์ด ํ•ญ๋ณตํ•˜๋ฉฐ ํ˜ธ๋ฅด๋ฌด์ฆˆ ํ•ดํ˜‘์ด ๊ฐœ๋ฐฉ๋  ๊ฒƒ์ด๋ผ๊ณ  ์˜ˆ์ƒํ–ˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ด ์„ธ ๊ฐ€์ง€ ๋ชจ๋‘ ํ˜„์‹ค์ด ๋˜์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค. ์ด๋ž€ ์ „์Ÿ์€ ์ด๋ฒˆ ํšŒ๋‹ด์—์„œ ํ•ต๋ฌด๊ธฐ๋‚˜ AI ๊ฐ™์€ ๋‹ค๋ฅธ ์‹œ๊ธ‰ํ•œ ์ฃผ์ œ๋ณด๋‹ค ๋” ๋งŽ์€ ๋…ผ์˜ ์‹œ๊ฐ„์„ ์ฐจ์ง€ํ•  ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์Šต๋‹ˆ๋‹ค.

์ค‘๊ตญ์€ ํ˜ธ๋ฅด๋ฌด์ฆˆ ํ•ดํ˜‘์ด ๊ฐœ๋ฐฉ๋˜๊ธฐ๋ฅผ ๊ฐ•๋ ฅํžˆ ์›ํ•ฉ๋‹ˆ๋‹ค. ์ค‘๊ตญ์€ ์„์œ  ๋ฐ ๊ฐ€์Šค์˜ 30% ์ด์ƒ์„ ์ด ํ•ดํ˜‘์„ ํ†ตํ•ด ์šด์†กํ•˜๋ฉฐ, ์ด๋ž€ ์ „์Ÿ ์ด์ „์—๋„ ์ž๊ตญ ๊ฒฝ์ œ ์ƒํ™ฉ์ด ์ข‹์ง€ ์•Š์•˜๋˜ ํ„ฐ๋ผ ์—๋„ˆ์ง€ ๊ฐ€๊ฒฉ ์ƒ์Šน์ด ๋งŽ์€ ์ค‘๊ตญ ๊ธฐ์—…๋“ค์„ ๊ณ ์‚ฌ์‹œํ‚ค๊ณ  ์žˆ๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ค‘๊ตญ์€ ์ง์ ‘ ๊ฐœ์ž…ํ•  ๋งŒํ•œ ์—ญ๋Ÿ‰์ด ํฌ์ง€ ์•Š์Šต๋‹ˆ๋‹ค.

์ค‘๊ตญ์˜ ์—ญํ• ๊ณผ ๋”œ๋ ˆ๋งˆ

ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ์ค‘๊ตญ์—๊ฒŒ ์ด๋ž€ ๋ฏธ์‚ฌ์ผ, ์š”๊ฒฉ๊ธฐ ๋ฐ ์ „๋ฐ˜์ ์ธ ์ „์Ÿ ์ˆ˜ํ–‰์— ํ•„์š”ํ•œ ํ‘œ์  ๋ฐ์ดํ„ฐ์™€ ๊ธฐ์ˆ  ๊ณต๊ธ‰์„ ์ค‘๋‹จํ•ด ์ค„ ๊ฒƒ์„ ์š”์ฒญํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๋˜ํ•œ, ๋ฏธ๊ตญ์€ ์ค‘๊ตญ์ด ์ด๋ž€ ์ƒํ’ˆ์˜ ์ฃผ์š” ๊ตฌ๋งค์ž๋กœ์„œ ์ด๋ž€์— ๋Œ€ํ•œ ์˜ํ–ฅ๋ ฅ์„ ํ–‰์‚ฌํ•˜์—ฌ ์ด๋ž€์ด ํ•ดํ˜‘์„ ๊ฐœ๋ฐฉํ•˜๋„๋ก ์„ค๋“ํ•ด ์ค„ ๊ฒƒ์„ ์š”๊ตฌํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค.

์‹œ์ง„ํ•‘ ์ฃผ์„์€ ๋งค์šฐ ์‹ ์ค‘ํ•œ ์ธ๋ฌผ์ด์ง€๋งŒ, ์ „์Ÿ ์ข…์‹์— ๋Œ€ํ•œ ๊ฐ•๋ ฅํ•œ ์ดํ•ด๊ด€๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋”ฐ๋ผ์„œ ๊ทธ๊ฐ€ ๋ฏธ๊ตญ์˜ ํŽธ์—์„œ ์กฐ์šฉํžˆ ์ด๋ž€์— ๊ฐœ์ž…ํ• ์ง€ ์—ฌ๋ถ€๊ฐ€ ์ฃผ๋ชฉ๋ฉ๋‹ˆ๋‹ค. ์ด๋Š” ์ค‘๊ตญ์—๊ฒŒ ๋ณต์žกํ•œ ๋”œ๋ ˆ๋งˆ๊ฐ€ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๊ฐ์ž์˜ โ€˜์Šน๋ฆฌโ€™ ๋ฐฉ์ •์‹: ํŠธ๋Ÿผํ”„์˜ ๋‹จ๊ธฐ ์„ฑ๊ณผ, ์‹œ์ง„ํ•‘์˜ ์žฅ๊ธฐ ์ „๋žต

์ด๋ฒˆ ์ •์ƒํšŒ๋‹ด์—์„œ ๋‘ ์ง€๋„์ž๊ฐ€ ๊ฐ๊ฐ โ€˜์Šน๋ฆฌโ€™๋ผ๊ณ  ๋А๋‚„ ๋งŒํ•œ ๊ฒƒ์€ ๋ฌด์—‡์ผ๊นŒ์š”? ๊ทธ๋ฆฌ๊ณ  ๊ทธ๋“ค์ด ๋Œ€์ค‘์—๊ฒŒ โ€˜์Šน๋ฆฌโ€™๋กœ ํฌ์žฅํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒƒ์€ ๋ฌด์—‡์ผ๊นŒ์š”?

ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์—๊ฒŒ๋Š” ๋ถ„๋ช…ํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Š” ํ•ญ์ƒ ๋Œ€๊ทœ๋ชจ ์‚ฌ์—… ๊ฑฐ๋ž˜๋ฅผ ํ†ตํ•ด ํšŒ๋‹ด์—์„œ ๋ฒ—์–ด๋‚˜๋ฉฐ, ์ž์‹ ์„ โ€˜์ตœ๊ณ ์˜ ํ˜‘์ƒ๊ฐ€(dealmaker-in-chief)โ€˜๋กœ ์„ ์–ธํ•˜๊ณ  ์‹ถ์–ด ํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ฐ์ด๋น„๋“œ ์ƒ์–ด ๊ธฐ์ž๊ฐ€ ์ง€์ ํ–ˆ๋“ฏ์ด, ์ด๋Ÿฌํ•œ ๋‹จ๊ธฐ์ ์ธ ์„ฑ๊ณผ๋Š” ์ด๋ž€ ์‚ฌํƒœ ์ดํ›„ ์ค‘๊ตญ์ด ๋ฏธ๊ตญ์„ ๊ณผ๊ฑฐ์ฒ˜๋Ÿผ ๋ฌด์ ์˜ ์กด์žฌ๋กœ ๋ณด์ง€ ์•Š์„ ์ˆ˜๋„ ์žˆ๋‹ค๋Š” ๊ทผ๋ณธ์ ์ธ ์งˆ๋ฌธ์—๋Š” ๋‹ตํ•˜์ง€ ๋ชปํ•ฉ๋‹ˆ๋‹ค.

์‹œ์ง„ํ•‘ ์ฃผ์„์—๊ฒŒ๋Š” โ€˜์žฅ๊ธฐ์ ์ธ ๊ฒŒ์ž„โ€™์ž…๋‹ˆ๋‹ค. ๊ทธ๋Š” ๊ฐœ๋ณ„์ ์ธ ๊ฑฐ๋ž˜ ์ž์ฒด์—๋Š” ํฌ๊ฒŒ ๊ด€์‹ฌ์ด ์—†์Šต๋‹ˆ๋‹ค. ๋งŒ์•ฝ ๊ทธ๋Ÿฐ ๊ฑฐ๋ž˜๋“ค์ด ์™ธ๊ต์˜ ์œคํ™œ์œ  ์—ญํ• ์„ ํ•œ๋‹ค๋ฉด ๊ดœ์ฐฎ์Šต๋‹ˆ๋‹ค. ์‹œ ์ฃผ์„์€ ์ž์‹ ์ด ํ˜„์žฌ ๋” ์•ˆ์ •์ ์ธ ๊ฐ•๋Œ€๊ตญ์„ ์šด์˜ํ•˜๊ณ  ์žˆ์Œ์„ ๋ณด์—ฌ์ฃผ๊ณ  ์‹ถ์–ด ํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Š” ๋‹ค๋ฅธ ๋‚˜๋ผ๋ฅผ ์นจ๋žตํ•˜๊ฑฐ๋‚˜ โ€˜์ •๊ธ€์˜ ๋ฒ•์น™(law of the jungle)โ€˜์„ ๋”ฐ๋ฅด์ง€ ์•Š๋Š”๋‹ค๊ณ  ์ตœ๊ทผ ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์„ ๊ฒจ๋ƒฅํ•œ ๋“ฏํ•œ ๋ฐœ์–ธ์„ ํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์‹œ๊ฐ„์ด ์ง€๋‚จ์— ๋”ฐ๋ผ ์ „ ์„ธ๊ณ„๊ฐ€ ์ค‘๊ตญ์˜ ํž˜๊ณผ ์ž๋ณธ์— ์˜์กดํ•˜์—ฌ ์žฌ๊ฑดํ•˜๊ณ  ์ƒˆ๋กœ์šด ๋ฌด์—ญ ๊ด€๊ณ„๋ฅผ ๊ตฌ์ถ•ํ•˜๊ฒŒ ๋  ๊ฒƒ์ด๋ผ๊ณ  ๋ฏฟ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๊ฒƒ์ด ์‹œ ์ฃผ์„์˜ ์žฅ๊ธฐ์ ์ธ ๊ณ„ํš์ด๋ฉฐ, ๊ทธ๋Š” ๋ฏธ๊ตญ์ด ์ž์ฒด์ ์ธ ์žฅ๊ธฐ ๊ณ„ํš์„ ๊ฐ€์ง€๊ณ  ์žˆ๋Š”์ง€ ์˜์‹ฌํ•  ์ˆ˜๋„ ์žˆ์Šต๋‹ˆ๋‹ค.

์ด๋ฒˆ ๋ฏธ์ค‘ ์ •์ƒํšŒ๋‹ด์€ ๋‹จ์ˆœํžˆ ๋‘ ์ •์ƒ์˜ ๋งŒ๋‚จ์ด ์•„๋‹Œ, ๊ฒฉ๋ณ€ํ•˜๋Š” ๊ตญ์ œ ์งˆ์„œ ์†์—์„œ ๋‘ ์ดˆ๊ฐ•๋Œ€๊ตญ์ด ํŽผ์น˜๋Š” ์น˜์—ดํ•œ ํŒจ๊ถŒ ๊ฒฝ์Ÿ์˜ ํ•œ ์žฅ๋ฉด์ž…๋‹ˆ๋‹ค. ์ด๋ž€ ์‚ฌํƒœ๋ผ๋Š” ์˜ˆ์ƒ์น˜ ๋ชปํ•œ ๋ณ€์ˆ˜ ์†์—์„œ ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ์ž์‹ ์˜ ์ž…์ง€๋ฅผ ํšŒ๋ณตํ•˜๋ ค ์• ์“ฐ๊ณ , ์‹œ์ง„ํ•‘ ์ฃผ์„์€ ์žฅ๊ธฐ์ ์ธ ๋น„์ „์„ ๊ฐ€์ง€๊ณ  ์ค‘๊ตญ์˜ ์œ„์ƒ์„ ๊ฐ•ํ™”ํ•˜๋ ค ํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด๋ฒˆ ํšŒ๋‹ด์˜ ๊ฒฐ๊ณผ๋Š” ๋‹จ๊ธฐ์ ์ธ ์‚ฌ์—… ์„ฑ๊ณผ๋ฅผ ๋„˜์–ด, ํ–ฅํ›„ ์ˆ˜์‹ญ ๋…„๊ฐ„ ์„ธ๊ณ„์˜ ๊ถŒ๋ ฅ ์ง€ํ˜•์„ ๊ฒฐ์ •ํ•˜๋Š” ๋ฐ ์ค‘์š”ํ•œ ์ด์ •ํ‘œ๊ฐ€ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค.