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April 23, 2026

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Based on โ€œThe AI Sandwich: Where Humans Excel in an AI Worldโ€ from Every Watch the original video

The AI Sandwich: How Humans Master the Future of Work with AI

In a world increasingly shaped by artificial intelligence, a profound question looms: what remains the unique domain of human endeavor? As AI tools become more sophisticated, automating tasks once thought exclusive to human minds, many fear a future where human work is rendered obsolete. Yet, a compelling new framework, dubbed the โ€œAI Sandwich,โ€ offers a reassuring and empowering vision, positioning humans not as competitors to AI, but as its essential architects and refiners.

This insight, championed by Kieran, the General Manager of Kora and creator of the revolutionary Compound Engineering framework, suggests that while AI can handle the โ€œfillingโ€ of our work, humans provide the crucial โ€œbreadโ€ โ€“ the beginning and the end that give work its true flavor, meaning, and distinction.

Compound Engineering: A Blueprint for Human-AI Collaboration

Kieranโ€™s journey to this realization began with the development of Compound Engineering (CE), an innovative workflow designed to optimize how teams work with AI agents. Initially conceived for software development, the philosophy behind CE quickly proved applicable across a spectrum of knowledge work, from product design to general problem-solving.

The initial iteration of Compound Engineering comprised four core steps:

  1. Planning: Defining a clear, actionable plan for the AI to execute.
  2. Work: The AI agent performs the actual task, whether writing code, generating designs, or processing information.
  3. Review: Assessing the AIโ€™s output for quality and identifying areas for improvement.
  4. Compound: Crucially, any lessons learned or mistakes identified during planning or review are โ€œcompoundedโ€ โ€“ stored as knowledge within the system. This allows AI agents to learn from past errors, preventing repetition and continuously improving their performance. Kieran highlights this compounding step as โ€œby far the most powerful thingโ€ in the plugin, transforming AI from a mere tool into a learning collaborator.

However, as AI capabilities rapidly advanced, Kieran and his collaborator, Trevan, a key contributor to CE, noticed a striking trend: the โ€œworkโ€ phase was becoming increasingly automated and reliable. โ€œThe work phase is kind of done,โ€ Kieran remarks, explaining that with a well-defined plan, AI models are exceptionally good at โ€œjust following steps, doing deep work, working for hours, days even now.โ€ This raised a provocative question: if AI could handle the core execution, and even improve its own planning and review, where did humans fit in? โ€œDid I automate myself out of a job?โ€ Kieran mused.

The AI Sandwich: Where Humans Shine

The answer, they discovered, lies at the extremities of the work process, giving rise to the โ€œAI Sandwichโ€ metaphor. โ€œHumans are the bread in the sandwich and the AI is in the middle,โ€ explains Dan Shipper, the host of the Every podcast. โ€œThe AI is whatever you put on your sandwich.โ€

This means humans excel, and indeed are indispensable, in two critical phases:

The First Slice: Brainstorming, Ideation, and Setting the Frame

Before any plan can be executed, before any code can be written, or any design rendered, thereโ€™s a crucial stage of exploration and definition. Trevan introduced โ€œBrainstormโ€ and โ€œIdeateโ€ steps to Compound Engineering, pushing the human role to the very beginning.

  • Ideate: This phase involves โ€œgoing wide,โ€ generating a multitude of ideas from diverse perspectives.
  • Brainstorm: Here, humans engage deeply with a problem, even when its exact nature or solution isnโ€™t fully clear. Itโ€™s about asking probing questions and genuinely thinking hard, with AI serving as a support rather than the primary driver.

This initial human involvement is vital because, as Dan explains, humans are exceptionally good at โ€œflipping and changing frames.โ€ Take, for instance, a simple problem: โ€œMy knee hurts.โ€ An AI might suggest taking Advil (the immediate, obvious solution within a narrow frame). A human, however, can shift the frame: Is it an IT band issue? Am I running on hard surfaces too often? Each re-framing addresses the same problem at a deeper, more systemic level. โ€œOur job is to set the frame or set the bounds within which we solve the problem,โ€ Dan emphasizes, a task that remains incredibly challenging for AI to do autonomously.

The Second Slice: Polishing, Elevating, and Infusing Soul

Once the AI has done its work, and even after it has been reviewed and tested for functionality, thereโ€™s another critical human touchpoint: the final polish.

โ€œThe beauty comes in when a human looks at it, clicks around and has a feel like, โ€˜Oh, this doesnโ€™t feel good. We can polish it even more. We can make it even better,โ€™โ€ Kieran describes. This isnโ€™t about fixing errors, but about elevating the output beyond mere correctness to something truly exceptional. Itโ€™s about infusing โ€œtasteโ€ and โ€œfeelโ€ โ€“ qualities that AI, despite its increasing sophistication, struggles to emulate.

Kieran draws an analogy to the Pomodoro technique, where staying with a task beyond its initial completion can lead to unexpected breakthroughs. In that extra time, โ€œsomething beautiful happens because you will go deeper, you will go further than you would do.โ€ This final human touch ensures the output resonates, feels great, and stands out in a world where generic, AI-generated โ€œslopโ€ is becoming increasingly common. โ€œItโ€™s very important to make it feel great because the bar is high, the bar will always get higher,โ€ Kieran warns.

Why Humans Remain Indispensable

The โ€œAI Sandwichโ€ isnโ€™t just a workflow; itโ€™s a profound statement on the enduring value of human capabilities. Several deep reasons underscore why AI cannot fully replace the human โ€œbreadโ€:

  • The Art of Ownership: โ€œIf you ship something or do something or make a like a statement in the world, if you want it to be your ownโ€ฆ you cannot fully automate everything. Like it is maybe a little bit like art,โ€ Kieran states. True art, and truly impactful work, requires a personal connection, a โ€œfrom youโ€ quality that AI cannot replicate.
  • Beyond Genericity: AI models, trained on vast datasets, tend to produce outputs that are, by nature, generic. While they can mimic styles, they lack the unique perspective, worldview, and specific context needed to solve a problem with genuine flair or to create something truly resonant. They are โ€œsuper intelligences that have been kept in a box,โ€ as Dan puts it, needing human guidance to tune their output to exact, nuanced problems.
  • Rare Expertise and Feedback Loops: Many critical decisions in complex work rely on rare expertise and data that is hard to come by. Humans accumulate this through years of experience and intuition, often through limited, high-stakes feedback loops that are difficult for AI to learn from.
  • The Moving Target of Creativity: The boundary between โ€œroteโ€ and โ€œartโ€ is constantly shifting. As AI automates the rote, humans are freed to explore new frontiers of creativity, continuously pushing the envelope of what is considered โ€œartโ€ or โ€œbeautiful.โ€
  • The Music of the Soul: Kieran, with his background in classical composition, likens the human role to a musician or composer. While AI can generate melodies, it cannot capture the raw emotion of a live performance or the spark of creating something โ€œout of nothing.โ€ The โ€œmiddle partโ€ (practicing a piece 100 times) is rote, but the initial composition and the final performance are inherently human, infused with feeling and expression.

Riding the Wave: Adapting to the AI Era

For many, the rise of AI sparks anxiety about job security. However, the โ€œAI Sandwichโ€ offers an optimistic outlook. Software engineers, often seen as the โ€œcanary in the coal mine,โ€ are not losing their jobs but are evolving. They are becoming more like managers, orchestrating AI agents, and more like product people, focusing on the ultimate user experience and the โ€œfeelโ€ of the product.

The key, according to Kieran, is to lean into what brings you joy and energy: โ€œWhatever that means to you, that can mean beautiful code, beautiful abstractions, beautiful architecture, beautiful design, beautiful copy. I think itโ€™s very important to lean into what is beautiful to you because then you will find a way to utilize an LLM to make something that gives you energy instead of drains you all the way.โ€

This means embracing a future where we offload the mundane, repetitive tasks to AI, freeing ourselves to focus on the higher-order, more creative, and more uniquely human aspects of work โ€“ the parts that involve deep thought, personal touch, and the pursuit of true excellence. Itโ€™s about recognizing that the โ€œfinal thing thatโ€™s not automatable is art made by humans who feel something.โ€

The AI Sandwich isnโ€™t just a metaphor; itโ€™s a practical framework for navigating the evolving landscape of work. It empowers us to leverage AIโ€™s incredible capabilities while preserving and elevating the irreplaceable value of human creativity, intuition, and passion. By embracing our role as the โ€œbread,โ€ we donโ€™t just survive in an AI world โ€“ we thrive, creating work that is not only efficient and effective but also deeply personal, beautiful, and profoundly human.


Based on โ€œWhy Does Everyone Hate Rats? (Update) | Freakonomics Radioโ€ from Freakonomics Radio Network Watch the original video

The Unpopular Truth About Our Urban Co-Inhabitants: Why We Really Hate Rats

Itโ€™s springtime in New York City, and as the city greens and sidewalk cafes bustle, another, less welcome, sign of the season emerges: the rats. Their sudden visibility often sparks a familiar wave of revulsion and a renewed call to arms. But this visceral hatred, as a recent Freakonomics Radio episode explores, is more complicated than it seems, rooted in centuries of misinformation, cultural biases, and our own urban failures.

The cityโ€™s ongoing โ€œwar on ratsโ€ took a particularly dramatic turn in 2022 when then-Mayor Eric Adams posted a job listing for a โ€œcitywide director of rodent mitigation.โ€ The ideal candidate, it read, should be โ€œhighly motivated and somewhat bloodthirsty,โ€ possessing a โ€œswashbuckling attitude, crafty humor, and a general aura of badassery.โ€ This was no ordinary civil servant Adams sought; he was searching for a hero in his deeply personal crusade against an animal he openly detested. โ€œRats do something to traumatize you,โ€ Adams declared, recalling the unforgettable horror of a rat running across his foot.

That hero turned out to be Katy Corradi, a biologist and urban sustainability expert with a masterโ€™s degree in the field. As New York Cityโ€™s first โ€œrat czar,โ€ Corradi inherited a formidable challenge. While her title might evoke images of a ruthless exterminator, her approach is far more nuanced, focusing on the fundamental principles of pest management: sanitation.

New Yorkโ€™s Unending Battle: The Rat Czarโ€™s Perspective

Corradiโ€™s journey to becoming the rat czar began with a childhood petition against rats behind her Brooklyn home, a testament to her early understanding of their habitat needs. โ€œThey need a place to live and they need food to eat,โ€ she explains, highlighting how neglected spaces with overgrown brush provide ideal conditions for burrowing and nesting. Later, working in the cityโ€™s Department of Education, she tackled rat mitigation by improving waste management in public schools, recognizing the inseparable link between garbage and rodents.

For rats, New York City is a paradise. Its dense human population generates an endless buffet of food waste, particularly visible in the overflowing trash bags on sidewalks and the proliferation of outdoor dining sheds that emerged during the COVID-19 pandemic. Estimates of the cityโ€™s rat population vary wildly, from 3 million to 8 million, but Corradi wisely avoids specific numbers, deeming them โ€œfutileโ€ and easily distorted.

Rats, or Rattus norvegicus (the brown rat we commonly encounter), are โ€œcommensalโ€ animals, a term Corradi defines as literally meaning โ€œsitting at the table with us.โ€ They are adept at exploiting and thriving in human-dense environments, demonstrating a remarkable savviness. โ€œIn terms of adaptability to survive, thereโ€™s few species greater,โ€ Corradi notes. Research even suggests rats exhibit empathy, altruism, and a form of โ€œlaughing,โ€ challenging our simplistic view of them as mere vermin. They are survivors, and as Stephen Dubner puts it, โ€œno one except humans exploits an urban space better.โ€

The Ratโ€™s Tarnished Image: Re-examining the Plague

Our deep-seated aversion to rats is not new. Their ancestors arrived in the Americas in the 18th century on European ships, but the historical timeline of their bad reputation is even more complex. Bethany Brookshire, a science journalist and author of โ€œPests: How Humans Create Animal Villains,โ€ explains that while people disliked rats for spoiling food, they werenโ€™t considered โ€œdisgustingโ€ or major disease carriers until the 18th or 19th century.

The most famous association, of course, is with the Black Death, the devastating bubonic plague that ravaged Europe in the 14th century, killing half its population. Popular culture, from Netflix shows to classic horror films, continues to depict swarms of rats as harbingers of plague. But recent scientific inquiry challenges this long-held belief.

Nils Christian Stenseth, a professor of ecology and evolution at the University of Oslo and a leading plague researcher, argues that rats were likely not the primary culprits for the Black Death. His 2018 paper in the Proceedings of the National Academy of Sciences suggested that โ€œhuman ectoparasites, like body lice and human fleas, might be more likely than rats to have caused the rapidly developing epidemics.โ€ The reasoning, as Harvard economist Ed Glaeser explains, is that rat-led plagues would spread more slowly because fleas only leave a rat when it dies. The rapid spread of the Black Death across Europe points to human-to-human transmission via parasites.

However, rats were implicated in the third major bubonic plague pandemic, which began in the 19th century and persists today in small numbers, particularly in India, Vietnam, and parts of the US. This โ€œthird explosionโ€ did involve rats and their fleas transmitting the Yersinia pestis bacterium, which forms a biofilm in the fleaโ€™s esophagus, causing it to regurgitate bacteria into every bite.

So, while the ratโ€™s โ€œguiltโ€ in the Black Death might be exaggerated, its reputation has been permanently scarred. โ€œBlaming the rat is pretty much, you know, game over in terms of the ratโ€™s global reputation,โ€ Glaeser observes. However, he quickly adds, โ€œI think we should also just object to using the word guilt on rats. Itโ€™s not like they know whatโ€™s going on. Theyโ€™re dying, tooโ€ฆ Letโ€™s go to Yersinia pestis itself. Thatโ€™s where the evil lies.โ€

Today, the public health risk from rats, while real, is often overstated. Leptospirosis, a bacterial illness transmitted through rat urine, saw 24 reported cases in New York City in 2023 โ€“ a minor threat in a city of 8 million. However, Corradi points to โ€œunrealized potential public health risks,โ€ such as novel viruses found on rats by Columbia University researchers, which pose a constant threat of mutation and host-jumping due to ratsโ€™ close proximity to humans.

The Psychology of Disgust: Why We Hate Their Success

Beyond disease, our revulsion towards rats is deeply psychological and cultural. Bethany Brookshireโ€™s work on โ€œpestsโ€ highlights that our hatred for certain animals is โ€œso subjective.โ€ Animals are simply โ€œbeing animals,โ€ but we categorize them as โ€œpestsโ€ when they are โ€œnot where we want them to be.โ€

Consider the pigeon, once a revered messenger, food source, and fertilizer provider. Colin Jerolmackโ€™s research shows how the pigeon, over a century, devolved from โ€œnoble, innocent, beautifulโ€ to โ€œrats with wingsโ€ in the public eye. As we developed chemical fertilizers, email, and chicken, our utility for pigeons vanished, and their continued presence became an annoyance. โ€œWe used to have such a use for them and now we donโ€™t and we canโ€™t fathom why they wonโ€™t go away,โ€ Brookshire laments.

Rats, unlike pigeons, have never truly served a widespread human purpose in Western cultures. Yet, in other cultures, their perception is entirely different. The Karni Mata Temple in Deshnoke, India, houses around 25,000 black rats, considered sacred reincarnations of people. Devotees worship them, providing elaborate food and milk offerings, walking barefoot on marble floors shared with the holy rodents.

This stark contrast, Brookshire argues, stems from cultural narratives. Western cultures, often influenced by concepts like โ€œdominion over animalsโ€ from texts like Genesis, expect to control their environment. When animals like rats thrive in our โ€œpaved overโ€ spaces, it challenges our perceived control. โ€œWe really hate them. We hate their success because their success feels like our failure,โ€ she concludes.

Our Urban Partners: Towards Sympathy for the Rat

Economist Ed Glaeser, an expert on cities, views rats as โ€œagents of usually negative externalitiesโ€ โ€“ spreading disease, damaging property, and reducing the โ€œdensity level for peopleโ€ by making urban spaces less appealing. Rats are known to chew through wires, foundations, and food supplies, creating economic costs and, as Corradi emphasizes, significant mental well-being issues like stress, anxiety, and depression for those living in close quarters with them.

However, Glaeser also offers a more nuanced perspective. While acknowledging the need for โ€œsome control,โ€ he cautions against โ€œmaking a fetish out of complete eradication.โ€ He suggests a shift in perspective: โ€œItโ€™s hard not to think that rats have gotten something of a bad rapโ€ฆ they sort of co-live with humans, theyโ€™re in some sense our natural city partner.โ€

This idea of โ€œsympathy for the ratโ€ resonates with Dubner. He argues that rather than viewing them with horror, we should see them as โ€œour urban partner.โ€ This perspective acknowledges their role in our shared ecosystem, even as we manage their populations.

New York Cityโ€™s war on rats continues, with recent reports showing a 20% year-over-year decline in rat sightings. Current Mayor Zoran Momdani is pushing for citywide trash containerization by 2031, a policy Corradi would surely endorse as the fundamental solution to limiting ratsโ€™ food access.

Ultimately, the story of why everyone hates rats is less about the animals themselves and more about us โ€“ our history, our perceptions, and our choices in how we design and manage our urban environments. Perhaps itโ€™s time to move beyond the โ€œbloodthirstyโ€ rhetoric and cultivate a more informed, perhaps even empathetic, understanding of our most reviled urban co-inhabitants. After all, as Brookshire wisely notes, โ€œwe have choices in the way that we treat other animals and we have choices in the way we treat each other. And we donโ€™t need to live the way that we always have.โ€


Based on โ€œClaude Design is slow and I love it anyway (plus why I love ChatGPT Images 2.0)โ€ from How I AI Watch the original video

The AI Design Paradox: Embracing Claudeโ€™s Deliberate Pace and ChatGPTโ€™s Creative Leap

The world of AI-powered design is exploding, with new tools promising to revolutionize how we build and create. As a product leader and AI enthusiast, Claire Valle has been at the forefront, exploring these innovations to understand their true potential for businesses and creative workflows. This week, the spotlight falls on two major players: Anthropicโ€™s Claude Design, a web-based design tool taking a swing at prototyping and presentations, and OpenAIโ€™s new GPT Image 2 model, which claims a โ€œnew era of image generation.โ€

While both tools offer significant advancements, they also reveal a fascinating paradox in the current state of AI: the tension between groundbreaking capabilities and the sometimes-sluggish reality of their execution.

Claude Design: A New Approach to Prototyping

Anthropicโ€™s Claude Design has entered the arena with a bold vision, aiming to simplify the creation of prototypes, wireframes, high-fidelity designs, slides, and even videos. The critical question on everyoneโ€™s mind: Is this the Figma killer? Claireโ€™s take is nuanced: it might not replace Figma entirely, but it certainly has the potential to disrupt the ecosystem of prototyping tools used before handing off designs to engineering.

Design Systems as a First-Class Citizen

What truly sets Claude Design apart is its revolutionary approach to design systems. Unlike many prototyping tools where integrating brand guidelines can be an afterthought or a cumbersome process, Claude Design makes the design system a โ€œfirst-class citizen.โ€ This means the tool is designed from the ground up to understand and adhere to your brandโ€™s visual language.

Claireโ€™s initial test involved importing a design system for Lennyโ€™s Newsletter. The process is surprisingly straightforward: provide HTML, logos, images, and fonts. Claude then embarks on a โ€œreasoningโ€ journey, analyzing these materials to extract core colors, typography, components, and brand marks. This intelligent extraction aims to build a structured design system that AI can then use to render consistent, high-quality UI.

The tool even warns you that this process takes about five minutes, a detail that hints at the โ€œdeliberate paceโ€ characteristic of current large language models. The result, however, is impressive, producing a system that closely mirrors the original brand. This focus on structured design systems is gaining traction across the industry; Google Labs, for instance, recently introduced the design.md standard, an effort to standardize how design systems are described for AI tools. This trend underscores a broader shift towards AI-native design workflows where consistency is paramount.

Building with Brand: Marketing Pages and Presentation Power

Claude Design truly shines when tasked with creating marketing-specific landing pages and websites that require strict adherence to a brandโ€™s aesthetic. For marketers struggling to translate brand assets into beautiful, functional prototypes, Claude Design offers a compelling solution.

To demonstrate, Claire challenged Claude to create a landing page for a hypothetical โ€œLennyDoc PRD builder,โ€ a direct competitor to her own Chat PRD, using Lennyโ€™s Newsletter design system. The process involves a conversational Q&A, allowing users to guide the AI on audience, desired sections, interactivity, and even pricing. A standout feature is the ability to generate multiple variations (defaulting to three), offering diverse design directions without requiring iterative prompting. As Claire notes, โ€œThis is really smart from a design tool perspective because often those cycles of no, make it better or make it different can be very slow, and most people come into Claude design probably donโ€™t have the ability to articulate exactly the changes they make.โ€

However, this is where the โ€œdeliberate paceโ€ becomes a tangible challenge. The generation of a single landing page can take anywhere from 5 to 10 minutes. This slowness, coupled with Anthropicโ€™s credit limits (Claire quickly hit hers, requiring a $200 top-up), highlights a significant hurdle for rapid iteration. โ€œI think we underestimate how nice that is from a speed of iteration perspective when youโ€™re building and designing things,โ€ Claire observes, contrasting it with Figmaโ€™s instant drag-and-drop responsiveness. Despite the wait, the generated LennyDoc page impressively captures the brandโ€™s essence, though Claude does have a โ€œslop tellโ€: an affinity for italicized serif fonts on landing pages.

Beyond landing pages, Claude Design excels at generating presentation slides. By simply dropping a PDF article and selecting a design system, the tool can craft a visually appealing and brand-aligned deck. For product marketers, this capability is a game-changer for training materials, enablement content, and customer presentations. The delightful inclusion of interactive elements, like a โ€œcute fake terminalโ€ for code commands, hints at a future where slides are essentially code, offering dynamic and engaging experiences.

The Joy of โ€œUglyโ€ Design: Unleashing Creativity

Perhaps the most surprisingly fun use case for Claude Design emerges when you remove the constraints of a design system. Claire experimented with asking Claude to create a 90s GeoCities-style version of Lennyโ€™s Newsletter homepage. The result, dubbed โ€œLennyโ€™s Product Zone,โ€ is a hilariously accurate and intentionally โ€œuglyโ€ rendition, complete with brick backgrounds and Comic Sans fonts.

This exercise reveals a โ€œsecret powerโ€ of Claude Design: its exceptional copywriting. When given the freedom to generate content, it produces engaging and often humorous text, like โ€œYour OKRs are cringe and seven ways to fix them before Q3.โ€ This showcases the AIโ€™s ability to not just design visually but also to craft compelling narratives, an often-underappreciated aspect of great design.

ChatGPT Images 2.0: Thinking Beyond Pixels

Just as Claude Design pushes the boundaries of structured UI, OpenAIโ€™s new GPT Image 2 model is redefining image generation. Billed as the โ€œfirst model that can do thinking,โ€ its core advancements lie in accurately rendering text and objects within images, tackling long-standing challenges in AI art.

Text, Layout, and โ€œThinkingโ€: The New Frontier

The ability to accurately render text within an image has been a holy grail for AI image models, often resulting in garbled or nonsensical characters. GPT Image 2 appears to have largely overcome this, producing legible typography that doesnโ€™t carry the tell-tale โ€œAI image textโ€ look. Furthermore, its proficiency in layout and composition suggests a deeper understanding of visual hierarchy and design principles. This โ€œthinkingโ€ capability allows it to arrange elements thoughtfully, moving beyond mere pixel generation to more intelligent design.

Building a Brand Kit from Scratch (and Reference Images)

One compelling use case Claire explored was generating a multi-page brand kit for her company, Chat PRD. Starting with a general prompt, GPT Image 2 produced a nine-grid layout of brand elements with clean typography. While good, it didnโ€™t quite capture Chat PRDโ€™s specific aesthetic.

This is where the iterative power of the new model comes into play. Claire uploaded reference images from Midjourney โ€“ brighter, pinker, pixelated landscapes that defined her brand. The instruction was simple: โ€œThatโ€™s not really us. Here are some reference images. Update the brand kit.โ€ The model responded by generating a new brand kit that perfectly integrated the pixelated style and vibrant pinks, offering a fresh perspective on the brandโ€™s visual identity. This workflow, combining initial generation with image-based iteration, addresses a common dissatisfaction among marketers who find existing image models struggle to align with specific brand assets and voice.

Personal Style Analysis: A Fun, Practical Use Case

Beyond corporate branding, GPT Image 2 also demonstrates its versatility with more personal applications. Claire uploaded a photo of herself and asked for a color analysis, a common practice to determine flattering shades. The AI provided an analysis identifying her as โ€œwarm neutralโ€ with best colors in earthy tones, even rendering her image in these colors. While the initial facial rendering was โ€œreal weirdโ€ and โ€œteeth looking kind of funk,โ€ it was an impressive attempt.

More importantly, when Claire corrected the AI โ€“ stating she was actually a โ€œdark winterโ€ and clarifying her natural hair color โ€“ the model course-corrected beautifully. It generated an accurate color palette for a dark winter, along with a sophisticated layout that combined text, color swatches, and images. The ability to perform such complex analysis, combine various visual and textual elements, and present them in a clean, professional layout suggests a significant leap in graphic generation. Claire even muses about switching her companyโ€™s infographics to GPT Image 2 due to its โ€œmore expensive and a little nicerโ€ aesthetic.

The Road Ahead: Patience, Progress, and Popping Tokens

The spring 2026 drop of AI design tools presents a thrilling glimpse into the future. Claude Design offers a robust framework for brand-consistent prototyping and presentations, while GPT Image 2 ushers in a new era of intelligent image generation, particularly in text and layout.

Yet, as Claire Valle aptly summarizes, โ€œAt the end of the day, I donโ€™t think any of these tools are dead yet. They all have their benefits. Theyโ€™re all slow, and theyโ€™re all making me top up my tokens.โ€ The journey to truly seamless AI-powered design is still unfolding, marked by the need for patience with processing times and the ongoing cost of advanced models. However, the progress is undeniable. From structured design systems to โ€œthinkingโ€ image models, these tools are not just automating tasks; theyโ€™re fundamentally changing how designers, marketers, and product builders approach creativity and execution. The future of design is here, and it promises to be both deliberate and delightfully disruptive.


Based on โ€œInside Kash Patelโ€™s F.B.I.โ€ from New York Times Podcasts Watch the original video

Inside the Storm: How Political Winds Rocked the FBI Under Kash Patel

For decades, the Federal Bureau of Investigation has strived to operate as an independent entity, dedicated to following facts โ€œwithout fear or favorโ€ โ€“ a commitment born from the scandals of Watergate. Yet, under the leadership of Kash Patel, appointed FBI Director during the Trump administration, this foundational principle appears to have been severely tested. A comprehensive investigation by New York Times journalists Emily Basilon and Rachel Poser, based on interviews with 45 current and former FBI employees, reveals an agency straining under unprecedented political pressure, its mission transformed, and its seasoned professionals deeply concerned for the safety and security of the nation.

The reporting paints a stark picture of an FBI leadership prioritizing political optics over fundamental law enforcement duties, leading to a palpable culture of fear, demotions, and resignations among agents and analysts across the country.

A Controversial Appointment and a Shift in Mission

Kash Patelโ€™s selection as FBI Director was highly unusual. Lacking prior experience within the FBI or extensive federal law enforcement, Patelโ€™s background included stints as a public defender and an intelligence official during the first Trump term. Those who knew him described him as ambitious, cocky, and full of bluster, with a history of spinning conspiracy theories about the bureau itself. He famously asserted that he would โ€œshut down the FBI Hoover building on day one and reopening the next day as a museum of the deep state,โ€ a sentiment that immediately raised alarm bells both inside and outside the agency.

President Trump, who had openly called the FBI a โ€œvery corrupt institutionโ€ and claimed to be โ€œa victim of it,โ€ clearly signaled a desire for change. This directive was quickly echoed by the administration, which declared the โ€œDepartment of Justice into the Department of Injusticeโ€ days were โ€œover.โ€ For many within the bureau, this signaled a dramatic shift from their long-held tradition of political neutrality.

Tanya Ugoritz, then head of the Directorate of Intelligence at the FBI, earnestly tried to set Patel up for success. She prepared to deliver his morning intelligence briefings, even reading his book for insights. However, she quickly realized this was not business as usual.

Decisions Driven by Optics, Not Analysis

Patelโ€™s tenure began with an immediate and impactful order: to move hundreds of field agents from Washington D.C. to field offices across the country. While some insiders acknowledged that the bureau had become too D.C.-heavy, the execution of this directive was described as โ€œrandom and arbitrary,โ€ lacking the traditional โ€œvery sober and considered analysisโ€ the FBI was known for. Ugoritz saw this as the first instance of a pattern: โ€œdecisions first and then everybody scramble and figure out how to make it happen later.โ€ This signaled that Patel would make abrupt, sudden decisions affecting investigations without the usual meticulous planning.

The appointment of Dan Bongino as Patelโ€™s deputy director further solidified these concerns. Bongino, a former Secret Service agent turned pro-Trump podcaster and Fox News commentator, had a history of conspiratorial views, once describing FBI agents as โ€œthugs for the Democratic partyโ€ and advocating for the bureauโ€™s disbandment. For agents like John Sullivan, an intelligence section chief, Bonginoโ€™s selection was a critical turning point where he โ€œrealized in that moment that it was not going to be okay.โ€

Together, Patel and Bongino initiated a strong push for optics. Sources reported that President Trump, observing footage of raids without visible FBI โ€œflack jackets,โ€ expressed anger, leading to a directive to prioritize such visual elements. Meanwhile, Patel himself participated in videos at Quantico, โ€œcosplaying as Rambo,โ€ complete with explosions and helicopter rappelling. While intended to project an image of toughness, these actions were widely seen as โ€œchildishโ€ and a drain on critical resources, diverting time and money from serious investigative work.

This prioritization of image over mission was glaringly evident in the investigation following the shooting of Charlie Kirk. Patel, unusually, took over an executive call during an active manhunt, berating the special agent in charge and dictating social media strategy. This rushed approach led to โ€œmaking mistakesโ€ and โ€œputting wrong information out into the world,โ€ deeply frustrating agents who understood the dangers of misdirection in an ongoing investigation.

The focus on optics even strained international alliances. At a secret intelligence conference in the UK, Patel reportedly attempted to post a photo taken with the king at Windsor Castle, despite clear instructions that some participants were โ€œnon-disclosedโ€ intelligence operatives whose faces were not to appear in the press. This created a โ€œminor international incident,โ€ underscoring how Patelโ€™s priorities were at odds with the sensitive nature of intelligence work.

When confronted with these anecdotes, FBI spokesman Ben Williamson dismissed the reporting as โ€œa regurgitation of fake narratives, conjecture, and speculation from anonymous sources who are disconnected from reality.โ€ However, the reporting highlighted that many sources were named, and the consistent narrative from numerous individuals painted a different picture.

The Rank and File: Reassignments, Red Lines, and Resignations

The transformation under Patelโ€™s leadership profoundly impacted the day-to-day work of FBI employees. A significant trend was the Trump administrationโ€™s emphasis on immigration, a domain where the FBI traditionally played no enforcement role. Agents and analysts across the country found themselves reassigned from their core dutiesโ€”such as public corruption, cybercrime, white-collar crime, drug trafficking, and terrorismโ€”to assist with immigration enforcement.

Jill Fields, a dedicated intelligence analyst in Los Angeles who specialized in violent crime, experienced this shift firsthand. When a major immigration push occurred, she and her team were tasked with unfamiliar duties. She recalled being told to pull analysts off other critical teams because โ€œweโ€™ve got to do this for optics. Weโ€™ve got to make a show for the president.โ€

The situation escalated when Fields was asked to cross what she considered a โ€œred line.โ€ After a group of protesters filmed agents and used a megaphone to warn residents about ICE presence, Fieldsโ€™ team was instructed to run a โ€œpreassessment checkโ€โ€”the first step toward a criminal investigationโ€”on these individuals. Her team reviewed cellphone video and concluded that the protesters were merely exercising their First Amendment rights and had committed no wrongdoing. Yet, they were explicitly ordered to open an investigation anyway.

Fields described the order as โ€œludicrous,โ€ akin to a scenario in legal training where the correct answer would be to refuse. When she pushed back, she was told, โ€œyou can get fired today or you can get fired in 40 years when another administration comes in and starts looking and seeing who had violated the law and who had followed and acquiesced.โ€ This chilling admission suggested that the leadership was aware of the questionable legality of their demands.

In response to her defiance, Fieldsโ€™ squad was disbanded, she was reassigned, and informed she was โ€œa problemโ€ and that the โ€œseventh floorโ€โ€”where the director sitsโ€”was aware of her. Feeling monitored and knowing her career was effectively over, Jill Fields decided to leave the bureau, taking with her a careerโ€™s worth of dedication and expertise. โ€œIt hurt to know that things had changed so much that I was not going to be able to continue doing the job that I loved,โ€ she lamented.

This incident also highlighted the erosion of the FBIโ€™s โ€œpost-Hoover mindset,โ€ a commitment to balancing its mission with American civil rights, ingrained in agents after historical abuses.

The Purge: Loyalty Tests and Political Dismissals

The political reorientation of the bureau also manifested in a systematic push to remove employees whose past work was deemed unfavorable. Patel had openly spoken about โ€œpurging the agencyโ€ of anyone who had investigated the president.

Tanya Ugoritz found herself caught in this dragnet. In 2020, the FBI had issued an intelligence report about a second-hand tip alleging Chinese government involvement in creating fake IDs for the 2020 election. The report was later withdrawn due to questions about its credibility. Fast forward to 2025, Senator Chuck Grassley, chair of the Senate Judiciary Committee, began seeking internal FBI documents related to alleged โ€œsuspect bad thingsโ€ the FBI did during the Biden administration. An email wrongly identified Ugoritz as the official who ordered the reportโ€™s withdrawal.

Despite being the number two official, Dan Bongino told Ugoritz that the matter was โ€œout of his hands.โ€ The next day, she was placed on administrative leave. An internal investigation and even a polygraph found no misconduct on her part. Yet, when she asked to return to her position, she was told that as a senior executive, her role was โ€œat the discretion of the directorโ€โ€”Patel. She was denied her job back, demoted, and ultimately decided to leave. Ugoritz expressed profound sadness at how โ€œcasually discard[ing] such people as if they were like a used up tissueโ€ demonstrated a โ€œcarelessโ€ disregard for the organizationโ€™s integrity and the experience it was losing. She felt she was a โ€œscapegoatโ€ to avoid awkward explanations to Senator Grassley.

Blair Tolman, another supervisory special agent, experienced a similar fate. She had led an elite public corruption unit, CR15, which investigated government employees and conducted the โ€œArctic Frostโ€ investigation into President Trumpโ€™s alleged interference in the 2020 election. This investigation became a major target for Trump and his critics. Tolman watched as agents she had personally selected for their skill and impartiality were fired. Eventually, her own termination letter arrived, citing โ€œlack of judgment and lack of impartiality that led to the political weaponization of the government.โ€ For Tolman, it was clear: โ€œwhat that meant was you were on this investigation and weโ€™re firing you for it.โ€

A Culture of Fear and a Compromised Mission

The firings and reassignments have instilled a โ€œculture of fearโ€ and โ€œparanoiaโ€ throughout the bureau. Dozens of employees have been dismissed, and the ongoing nature of these actions has made agents wary of taking on assignments that might be perceived as political, fearing they could be targeted by a future administration. This chilling effect means that if a tip about corruption or even a terrorist threat involves someone perceived as an ally of the administration, agents might hesitate to act, leading to missed threats and a less safe America.

The internal checks and balances, the โ€œwatchdogs,โ€ and the channels for speaking to supervisors are widely perceived as either shut down or not functioning properly. This has driven many typically โ€œbuttoned up, secretive agencyโ€ employees to speak to the media, viewing the courts and the press as the โ€œlast open avenuesโ€ to convey their deep concern that the FBIโ€™s core mission is being โ€œseverely compromised.โ€

Blair Tolman is now a leading plaintiff in a lawsuit challenging these dismissals, describing it as a โ€œpolitical purge.โ€ The lawsuit seeks reinstatement and โ€œdue process,โ€ but also aims to โ€œmake sure that others are protected now and in the future.โ€

The journalists concluded that while many within the FBI acknowledge the need for reform, the methods employed under Patelโ€™s leadershipโ€”characterized by abrupt changes, political prioritization, and a disregard for established protocolsโ€”have been detrimental. As one source stated, โ€œthe ways in which you change an organization like the FBI are not by cutting off chunks of it and hoping that it grows back better.โ€ The fear is that โ€œcertain threats just arenโ€™t getting addressed because thereโ€™s no one there to work them,โ€ leaving the nation vulnerable. โ€œI donโ€™t know how we rebuild after this,โ€ one agent confided, โ€œI worry about what is being missed.โ€

While Patelโ€™s future remains uncertain, with mixed signals from the White House despite public statements of support, the profound impact of his tenure on the FBIโ€™s independence, morale, and effectiveness is undeniable. The struggle for the soul of Americaโ€™s premier law enforcement agency continues.


ํ•œ๊ตญ์–ด

โ€œThe AI Sandwich: Where Humans Excel in an AI Worldโ€ โ€” Every ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

AI ์‹œ๋Œ€, ์ธ๊ฐ„์˜ ์ง„์ •ํ•œ ๊ฐ€์น˜๋ฅผ ์ฐพ์•„๋ผ: โ€˜AI ์ƒŒ๋“œ์œ„์น˜โ€™ ๋ชจ๋ธ์˜ ํ†ต์ฐฐ

์ธ๊ณต์ง€๋Šฅ(AI) ๊ธฐ์ˆ ์ด ์ „๋ก€ ์—†๋Š” ์†๋„๋กœ ๋ฐœ์ „ํ•˜๋ฉด์„œ ๋งŽ์€ ์‚ฌ๋žŒ๋“ค์€ ๋ฏธ๋ž˜์˜ ์—…๋ฌด ํ™˜๊ฒฝ๊ณผ ์ธ๊ฐ„์˜ ์—ญํ• ์— ๋Œ€ํ•ด ๋ถˆ์•ˆ๊ฐ์„ ๋А๋ผ๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ณผ์—ฐ AI๋Š” ์šฐ๋ฆฌ์˜ ์ผ์ž๋ฆฌ๋ฅผ ๋นผ์•—๊ณ  ์ธ๊ฐ„์˜ ์—ญํ• ์„ ๋Œ€์ฒดํ• ๊นŒ์š”? ์—๋ธŒ๋ฆฌ(Every) ์ฑ„๋„์˜ ์œ ํŠœ๋ธŒ ๋น„๋””์˜ค์—์„œ ์ฝ”๋ผ(Kora)์˜ ์ œ๋„ˆ๋Ÿด ๋งค๋‹ˆ์ €์ด์ž ์ปดํŒŒ์šด๋“œ ์—”์ง€๋‹ˆ์–ด๋ง(Compound Engineering)์˜ ์ฐฝ์‹œ์ž์ธ ํ‚ค์–ด๋Ÿฐ(Kieran)๊ณผ ํ˜ธ์ŠคํŠธ ๋Œ„ ์‰ฌํผ(Dan Shipper)๋Š” ์ด๋Ÿฌํ•œ ์งˆ๋ฌธ์— ๋Œ€ํ•œ ํ˜์‹ ์ ์ธ ํ•ด๋‹ต์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. ๋ฐ”๋กœ โ€˜AI ์ƒŒ๋“œ์œ„์น˜โ€™ ๋ชจ๋ธ์ž…๋‹ˆ๋‹ค.

์ด ๋ชจ๋ธ์€ AI ์‹œ๋Œ€์— ์ธ๊ฐ„์ด ์–ด๋””์—์„œ ํƒ์›”ํ•œ ๋Šฅ๋ ฅ์„ ๋ฐœํœ˜ํ•˜๊ณ , AI์™€ ์–ด๋–ป๊ฒŒ ํ˜‘๋ ฅํ•ด์•ผ ํ•˜๋Š”์ง€์— ๋Œ€ํ•œ ๋ช…ํ™•ํ•œ ์ฒญ์‚ฌ์ง„์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ์ธ๊ฐ„์€ ์ƒŒ๋“œ์œ„์น˜์˜ โ€˜๋นตโ€™์ฒ˜๋Ÿผ ์‹œ์ž‘๊ณผ ๋์„ ๋‹ด๋‹นํ•˜๋ฉฐ, AI๋Š” ๊ทธ ์‚ฌ์ด์˜ โ€˜์†์žฌ๋ฃŒโ€™ ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•œ๋‹ค๋Š” ๊ฒƒ์ด ํ•ต์‹ฌ์ž…๋‹ˆ๋‹ค.

โ€˜AI ์ƒŒ๋“œ์œ„์น˜โ€™์˜ ํƒ„์ƒ ๋ฐฐ๊ฒฝ: ์ปดํŒŒ์šด๋“œ ์—”์ง€๋‹ˆ์–ด๋ง(Compound Engineering) ์—ฌ์ •

ํ‚ค์–ด๋Ÿฐ์€ ์—์ด์ „ํŠธ(agent) ๊ธฐ๋ฐ˜์˜ ์ฝ”๋“œ ์ž‘์—…์„ ํ˜์‹ ํ•˜๋Š” ์—”์ง€๋‹ˆ์–ด๋ง ํ”„๋ ˆ์ž„์›Œํฌ์ด์ž ํ”Œ๋Ÿฌ๊ทธ์ธ์ธ ์ปดํŒŒ์šด๋“œ ์—”์ง€๋‹ˆ์–ด๋ง์„ ๊ฐœ๋ฐœํ•˜๋ฉฐ โ€˜AI ์ƒŒ๋“œ์œ„์น˜โ€™ ๋ชจ๋ธ์— ๋Œ€ํ•œ ํ†ต์ฐฐ์„ ์–ป๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ฝ”๋ผ๋ฅผ ๊ตฌ์ถ•ํ•˜๋ฉด์„œ AI๋ฅผ ํ™œ์šฉํ•ด ๋” ๋น ๋ฅด๊ณ  ํšจ์œจ์ ์œผ๋กœ ์ž‘์—…ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ๊ณ ๋ฏผํ–ˆ๊ณ , ์ดˆ๊ธฐ ์ปดํŒŒ์šด๋“œ ์—”์ง€๋‹ˆ์–ด๋ง์€ ๋„ค ๊ฐ€์ง€ ํ•ต์‹ฌ ๋‹จ๊ณ„๋กœ ๊ตฌ์„ฑ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.

  1. ๊ณ„ํš(Planning): ๋ฌด์—‡์„ ๋งŒ๋“ค๊ณ  ์ˆ˜ํ–‰ํ• ์ง€ ๋ช…ํ™•ํ•œ ๊ณ„ํš์„ ์„ธ์›๋‹ˆ๋‹ค.
  2. ์ž‘์—…(Work): AI ์—์ด์ „ํŠธ๊ฐ€ ์‹ค์ œ ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•˜๊ณ  ์ฝ”๋“œ๋ฅผ ์ž‘์„ฑํ•˜๊ฑฐ๋‚˜ ๋””์ž์ธ ์ž‘์—…์„ ์ง„ํ–‰ํ•ฉ๋‹ˆ๋‹ค.
  3. ๊ฒ€ํ† (Review): ๊ฒฐ๊ณผ๋ฌผ์„ ๊ฒ€ํ† ํ•˜๊ณ  ๊ฐœ์„ ์ ์„ ์ฐพ์Šต๋‹ˆ๋‹ค. ์ „ํ†ต์ ์ธ ์ฝ”๋“œ ๋ฆฌ๋ทฐ์™€ ์œ ์‚ฌํ•ฉ๋‹ˆ๋‹ค.
  4. ๋ณตํ•ฉํ™”(Compound): ๊ฒ€ํ†  ๊ณผ์ •์ด๋‚˜ ๊ณ„ํš ๋‹จ๊ณ„์—์„œ ์–ป์€ ์ค‘์š”ํ•œ ํ•™์Šต ๋‚ด์šฉ์„ ์‹œ์Šคํ…œ์— ๋‹ค์‹œ ํ†ตํ•ฉ(compound)ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ์ง€์‹์œผ๋กœ ์ €์žฅ๋˜์–ด ์—์ด์ „ํŠธ๊ฐ€ ๋‹ค์Œ ์ž‘์—… ์‹œ ์ด์ „์— ์ €์ง€๋ฅธ ์‹ค์ˆ˜๋ฅผ ๋ฐ˜๋ณตํ•˜์ง€ ์•Š๋„๋ก ๋•๋Š” ๊ฐ€์žฅ ๊ฐ•๋ ฅํ•œ ๊ธฐ๋Šฅ์ž…๋‹ˆ๋‹ค.

์ด ๊ณผ์ •์—์„œ ํ‚ค์–ด๋Ÿฐ๊ณผ ๊ทธ์˜ ํŒ€์€ ํฅ๋ฏธ๋กœ์šด ์‚ฌ์‹ค์„ ๋ฐœ๊ฒฌํ–ˆ์Šต๋‹ˆ๋‹ค. ์ผ๋‹จ ์ข‹์€ ๊ณ„ํš์ด ์„ธ์›Œ์ง€๋ฉด โ€˜์ž‘์—…โ€™ ๋‹จ๊ณ„๋Š” AI๊ฐ€ ๋งค์šฐ ์ž˜ ์ˆ˜ํ–‰ํ•œ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๋Œ€๊ทœ๋ชจ ์–ธ์–ด ๋ชจ๋ธ(LLM, Large Language Model)์€ ์ง€์‹œ๋ฅผ ๋”ฐ๋ฅด๊ณ  ๊นŠ์ด ์žˆ๋Š” ์ž‘์—…์„ ๋ช‡ ์‹œ๊ฐ„, ์‹ฌ์ง€์–ด ๋ฉฐ์น  ๋™์•ˆ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐ ํƒ์›”ํ•œ ๋Šฅ๋ ฅ์„ ๋ณด์˜€์Šต๋‹ˆ๋‹ค. โ€˜์ž‘์—…โ€™ ๋‹จ๊ณ„๊ฐ€ ๊ฑฐ์˜ โ€˜ํ•ด๊ฒฐโ€™๋œ ์˜์—ญ์ด ๋˜์ž, ํŒ€์€ ์ธ๊ฐ„์˜ ์—ญํ• ์ด ์–ด๋””์— ๋‚จ์•„์žˆ๋Š”์ง€ ์งˆ๋ฌธํ•˜๊ธฐ ์‹œ์ž‘ํ–ˆ์Šต๋‹ˆ๋‹ค. โ€œ๋งŒ์•ฝ ๋ชจ๋“  ๊ฒƒ์ด ์ž‘๋™ํ•œ๋‹ค๋ฉด, ๋‚ด ์ผ์ž๋ฆฌ๋Š” ์ž๋™ํ™”๋˜๋Š” ๊ฒƒ์ธ๊ฐ€?โ€

์ธ๊ฐ„๊ณผ AI์˜ ์ตœ์  ํ˜‘์—… ๋ชจ๋ธ: ์ƒŒ๋“œ์œ„์น˜ ๋น„์œ ์˜ ์‹ฌ์ธต ๋ถ„์„

์ด๋Ÿฌํ•œ ์งˆ๋ฌธ์— ๋Œ€ํ•œ ๋‹ต์€ ์ปดํŒŒ์šด๋“œ ์—”์ง€๋‹ˆ์–ด๋ง ํ”Œ๋Ÿฌ๊ทธ์ธ์— ํฌ๊ฒŒ ๊ธฐ์—ฌํ•œ ์ œํ’ˆ ์ „๋ฌธ๊ฐ€ ํŠธ๋ ˆ๋ฐ˜ ์ฐจ์šฐ(Trevan Chow)์˜ ์ถ”๊ฐ€ ์ž‘์—…์—์„œ ์‹œ์ž‘๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” โ€˜๊ณ„ํšโ€™ ๋‹จ๊ณ„ ์ด์ „์— โ€˜๋ธŒ๋ ˆ์ธ์Šคํ† ๋ฐ(Brainstorm)โ€˜๊ณผ โ€˜์•„์ด๋””์–ด ๊ตฌ์ƒ(Ideate)โ€™ ๋‹จ๊ณ„๋ฅผ ์ถ”๊ฐ€ํ–ˆ์Šต๋‹ˆ๋‹ค.

AI์˜ ๊ฐ•์ : ํšจ์œจ์ ์ธ ์ค‘๊ฐ„ ๋‹จ๊ณ„ ์ž๋™ํ™”

AI๋Š” ์ž˜ ์ •์˜๋œ ์ž‘์—…์„ ์‹คํ–‰ํ•˜๋Š” ๋ฐ ํƒ์›”ํ•ฉ๋‹ˆ๋‹ค. โ€˜AI ์ƒŒ๋“œ์œ„์น˜โ€™ ๋ชจ๋ธ์—์„œ AI๋Š” ์ƒŒ๋“œ์œ„์น˜์˜ โ€˜์†์žฌ๋ฃŒโ€™ ์—ญํ• ์„ ๋‹ด๋‹นํ•ฉ๋‹ˆ๋‹ค. ์ฆ‰, ๊ณ„ํš, ์ž‘์—…, ๊ฒ€ํ† ์™€ ๊ฐ™์€ ์ค‘๊ฐ„ ๋‹จ๊ณ„์˜ ๋Œ€๋ถ€๋ถ„์„ ํšจ์œจ์ ์œผ๋กœ ์ž๋™ํ™”ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. LLM์€ ์ฃผ์–ด์ง„ ์ง€์‹œ๋ฅผ ์ •ํ™•ํžˆ ๋”ฐ๋ฅด๊ณ , ๋ณต์žกํ•œ ์ฝ”๋“œ ์ž‘์„ฑ์ด๋‚˜ ๋ฐ์ดํ„ฐ ๋ถ„์„ ๋“ฑ ๋ฐ˜๋ณต์ ์ด๊ณ  ์‹œ๊ฐ„์ด ๋งŽ์ด ์†Œ์š”๋˜๋Š” ์ž‘์—…์„ ์‹ ๋ขฐ์„ฑ ์žˆ๊ฒŒ ์ˆ˜ํ–‰ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ์ธ๊ฐ„์ด ์ง€๋ฃจํ•˜๊ณ  ๋ฐ˜๋ณต์ ์ธ ์—…๋ฌด์—์„œ ๋ฒ—์–ด๋‚˜ ๋” ๊ฐ€์น˜ ์žˆ๋Š” ์ผ์— ์ง‘์ค‘ํ•  ์ˆ˜ ์žˆ๋„๋ก ๋•์Šต๋‹ˆ๋‹ค.

์ธ๊ฐ„์˜ ๋…๋ณด์  ์—ญํ• : ์ƒŒ๋“œ์œ„์น˜์˜ โ€˜๋นตโ€™์ด ๋˜๋Š” ์ˆœ๊ฐ„

ํ•˜์ง€๋งŒ ์ƒŒ๋“œ์œ„์น˜๋Š” ๋นต ์—†์ด๋Š” ์™„์„ฑ๋˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค. ํ‚ค์–ด๋Ÿฐ๊ณผ ๋Œ„์€ ์ธ๊ฐ„์˜ ์—ญํ• ์ด ์ƒŒ๋“œ์œ„์น˜์˜ โ€˜์‹œ์ž‘โ€™๊ณผ โ€˜๋โ€™์— ์žˆ๋‹ค๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค.

1. ์‹œ์ž‘์ : ์•„์ด๋””์–ด ๋ฐœ์ƒ๊ณผ ๋ฌธ์ œ ์ •์˜ (๋‡Œ์šฐ ๋‹จ๊ณ„)

๊ฐ€์žฅ ์ฒซ ๋‹จ๊ณ„์ธ โ€˜์•„์ด๋””์–ด ๊ตฌ์ƒโ€™๊ณผ โ€˜๋ธŒ๋ ˆ์ธ์Šคํ† ๋ฐโ€™์€ ์ธ๊ฐ„์˜ ๊นŠ์€ ๊ฐœ์ž…์ด ํ•„์ˆ˜์ ์ž…๋‹ˆ๋‹ค. ์ธ๊ฐ„์€ ๋ฌธ์ œ์˜ ๋ณธ์งˆ์„ ํŒŒ๊ณ ๋“ค๊ณ , ๋‹ค์–‘ํ•œ ๊ฐ๋„์—์„œ ์งˆ๋ฌธ์„ ๋˜์ง€๋ฉฐ, ์–ด๋–ค ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ• ์ง€ โ€˜ํ”„๋ ˆ์ž„(frame)โ€˜์„ ์„ค์ •ํ•˜๋Š” ๋ฐ ํƒ์›”ํ•ฉ๋‹ˆ๋‹ค. AI๋Š” ์ด ๊ณผ์ •์—์„œ ์ธ๊ฐ„์„ ์ง€์›ํ•  ์ˆ˜ ์žˆ์ง€๋งŒ, ๊ถ๊ทน์ ์œผ๋กœ ๋ฌธ์ œ์˜ ๊ฒฝ๊ณ„๋ฅผ ์ •ํ•˜๊ณ  ํ•ด๊ฒฐ ๋ฐฉํ–ฅ์„ ์ œ์‹œํ•˜๋Š” ๊ฒƒ์€ ์ธ๊ฐ„์˜ ๋ชซ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ๋‹จ์ˆœํ•œ ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ ์ด์ƒ์˜ ๊ฒฝํ—˜, ์ง๊ด€, ๊ทธ๋ฆฌ๊ณ  ๋งฅ๋ฝ์  ์ดํ•ด๋ฅผ ์š”๊ตฌํ•˜๋Š” ์˜์—ญ์ž…๋‹ˆ๋‹ค. ํ‚ค์–ด๋Ÿฐ์€ โ€œ์ธ๊ฐ„์€ AI๊ฐ€ ๋ฒˆ์„ฑํ•  ์ˆ˜ ์žˆ๋Š” ํ™˜๊ฒฝ์„ ๊ตฌ์ถ•ํ•ด์•ผ ํ•˜๋ฉฐ, ์˜ฌ๋ฐ”๋ฅธ ๊ฒƒ์„ ์„ ํƒํ•ด์•ผ ํ•œ๋‹คโ€๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค.

2. ์ข…์ฐฉ์ : ์ตœ์ข… ๊ฒ€์ฆ๊ณผ ์˜ˆ์ˆ ์  ์™„์„ฑ (ํด๋ฆฌ์‹ฑ ๋‹จ๊ณ„)

๋ชจ๋“  ์ž๋™ํ™”๋œ ์ž‘์—…์ด ๋๋‚œ ํ›„์—๋„ ์ธ๊ฐ„์˜ ์—ญํ• ์€ ์—ฌ์ „ํžˆ ์ค‘์š”ํ•ฉ๋‹ˆ๋‹ค. AI๊ฐ€ ์ƒ์„ฑํ•œ ๊ฒฐ๊ณผ๋ฌผ์ด ๋ชจ๋“  ์š”๊ตฌ ์‚ฌํ•ญ์„ ์ถฉ์กฑํ•˜๊ณ  ํ…Œ์ŠคํŠธ๋ฅผ ํ†ต๊ณผํ•˜๋”๋ผ๋„, ์ตœ์ข…์ ์œผ๋กœ โ€˜์ด๊ฒƒ์ด ์ข‹์€๊ฐ€?โ€˜๋ฅผ ํŒ๋‹จํ•˜๊ณ  โ€˜์•„๋ฆ„๋‹ค์›€โ€™์„ ๋”ํ•˜๋Š” ๊ฒƒ์€ ์ธ๊ฐ„์˜ ๋ชซ์ž…๋‹ˆ๋‹ค. ์›น ๋ธŒ๋ผ์šฐ์ € ์ž๋™ํ™” ํ…Œ์ŠคํŠธ๋Š” ๋ชจ๋“  ๊ธฐ๋Šฅ์ด ์ž‘๋™ํ•œ๋‹ค๊ณ  ๋งํ•  ์ˆ˜ ์žˆ์ง€๋งŒ, ์ธ๊ฐ„์ด ์ง์ ‘ ํด๋ฆญํ•˜๊ณ  ์‚ฌ์šฉํ•ด ๋ณด๋ฉฐ โ€œ์ด๊ฒƒ์€ ๋А๋‚Œ์ด ์ข‹์ง€ ์•Š๋‹คโ€, โ€œ๋” ๋‹ค๋“ฌ์„ ์ˆ˜ ์žˆ๋‹คโ€, โ€œ๋” ์•„๋ฆ„๋‹ต๊ฒŒ ๋งŒ๋“ค ์ˆ˜ ์žˆ๋‹คโ€๊ณ  ํŒ๋‹จํ•˜๋Š” ์ˆœ๊ฐ„์ด ์žˆ์Šต๋‹ˆ๋‹ค.

ํ‚ค์–ด๋Ÿฐ์€ ๋ฝ€๋ชจ๋„๋กœ(Pomodoro) ํ…Œํฌ๋‹‰์„ ์˜ˆ๋กœ ๋“ค๋ฉฐ, ์ •ํ•ด์ง„ ์‹œ๊ฐ„ ๋™์•ˆ ํ•˜๋‚˜์˜ ์ž‘์—…์— ๊นŠ์ด ๋ชฐ์ž…ํ•  ๋•Œ ์˜ˆ์ƒ์น˜ ๋ชปํ•œ โ€˜์•„๋ฆ„๋‹ค์šด ๊ฒฐ๊ณผโ€™๊ฐ€ ๋‚˜ํƒ€๋‚œ๋‹ค๊ณ  ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค. ์ด์ฒ˜๋Ÿผ AI๊ฐ€ ๋งŒ๋“  ๊ฒฐ๊ณผ๋ฌผ์„ โ€˜์ตœ์ข…์ ์œผ๋กœ ๋Œ์–ด์˜ฌ๋ ค ๋”์šฑ ํ›Œ๋ฅญํ•˜๊ฒŒ ๋งŒ๋“œ๋Š”โ€™ ํด๋ฆฌ์‹ฑ(polishing) ๋‹จ๊ณ„๋Š” ์ธ๊ฐ„์˜ ์ทจํ–ฅ, ๊ฒฝํ—˜, ๊ทธ๋ฆฌ๊ณ  ์˜ˆ์ˆ ์  ๊ฐ๊ฐ์ด ๋ฐœํœ˜๋˜๋Š” ์ง€์ ์ž…๋‹ˆ๋‹ค. โ€œ๋งŒ์•ฝ ์šฐ๋ฆฌ๊ฐ€ ์ด ์ž‘์—…์„ ํ•˜์ง€ ์•Š๋Š”๋‹ค๋ฉด, ๋ชจ๋“  ๊ฒฐ๊ณผ๋ฌผ์€ ๋˜‘๊ฐ™๊ณ  ํ‰๋ฒ”ํ•ด์งˆ ๊ฒƒ์ž…๋‹ˆ๋‹ค.โ€

AI ์‹œ๋Œ€, ์ธ๊ฐ„์˜ ์ผ์ž๋ฆฌ๋Š” ์‚ฌ๋ผ์งˆ๊นŒ? ์†Œํ”„ํŠธ์›จ์–ด ์—”์ง€๋‹ˆ์–ด์˜ ์‚ฌ๋ก€

AI๊ฐ€ ์ธ๊ฐ„์˜ ์—ญํ• ์„ ๋Œ€์ฒดํ•  ๊ฒƒ์ด๋ผ๋Š” ์šฐ๋ ค์— ๋Œ€ํ•ด ๋Œ„์€ ์†Œํ”„ํŠธ์›จ์–ด ์—”์ง€๋‹ˆ์–ด๋ฅผ โ€˜ํƒ„๊ด‘ ์† ์นด๋‚˜๋ฆฌ์•„(canary in the coal mine)โ€˜์— ๋น„์œ ํ•˜๋ฉฐ, ๊ทธ๋“ค์˜ ๊ฒฝํ—˜์ด ๋‹ค๋ฅธ ์ง€์‹ ๋…ธ๋™์ž๋“ค์—๊ฒŒ ์ค‘์š”ํ•œ ํ†ต์ฐฐ์„ ์ œ๊ณตํ•œ๋‹ค๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ์—๋ธŒ๋ฆฌ ๋‚ด๋ถ€์—์„œ๋Š” AI ์—์ด์ „ํŠธ์˜ ๋„์ž…์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ์—ฌ์ „ํžˆ ์†Œํ”„ํŠธ์›จ์–ด ์—”์ง€๋‹ˆ์–ด๋ฅผ ๊ณ ์šฉํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋‹ค๋งŒ, ๊ทธ๋“ค์˜ ์—…๋ฌด ๋ฐฉ์‹์€ ๋ณ€ํ™”ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด์ œ ์—”์ง€๋‹ˆ์–ด๋Š” ์ฝ”๋“œ๋ฅผ ์ง์ ‘ ์ž‘์„ฑํ•˜๋Š” ๊ฒƒ๋ณด๋‹ค โ€˜๊ด€๋ฆฌโ€™์— ๊ฐ€๊นŒ์šด ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•˜๊ฒŒ ๋ฉ๋‹ˆ๋‹ค. ์ฆ‰, โ€˜AI ์ƒŒ๋“œ์œ„์น˜โ€™์˜ ์‹œ์ž‘๊ณผ ๋์— ์ฐธ์—ฌํ•˜๋Š” ๊ฒƒ์ด์ฃ .

์ด๋Š” ์นดํ”ผ๋ผ์ดํŒ…, ์ „๋žต ์ˆ˜๋ฆฝ, ๋””์ž์ธ ๋“ฑ ๋‹ค๋ฅธ ๋ชจ๋“  ์ง€์‹ ๋…ธ๋™์—๋„ ๋™์ผํ•˜๊ฒŒ ์ ์šฉ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ธ๊ฐ„์€ ๋ฌธ์ œ์˜ โ€˜ํ”„๋ ˆ์ž„โ€™์„ ์„ค์ •ํ•˜๊ณ  ์ƒํ™ฉ์— ๋”ฐ๋ผ ํ”„๋ ˆ์ž„์„ ์œ ์—ฐํ•˜๊ฒŒ ์ „ํ™˜ํ•˜๋Š” ๋ฐ ๋งค์šฐ ๋Šฅ์ˆ™ํ•ฉ๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ๋ฌด๋ฆŽ ํ†ต์ฆ์ด๋ผ๋Š” ๋ฌธ์ œ๊ฐ€ ์žˆ์„ ๋•Œ, AI๋Š” ์ฆ‰์‹œ ์ง„ํ†ต์ œ๋ฅผ ์ถ”์ฒœํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ธ๊ฐ„์€ ๋” ํฐ ํ”„๋ ˆ์ž„ ์•ˆ์—์„œ โ€˜IT ๋ฐด๋“œ๋ฅผ ์ŠคํŠธ๋ ˆ์นญํ•ด์•ผ ํ•  ์ˆ˜๋„ ์žˆ๋‹คโ€™, โ€˜๋งค์ผ ๋”ฑ๋”ฑํ•œ ํ‘œ๋ฉด์—์„œ ๋‹ฌ๋ฆฌ๋Š” ๊ฒƒ์„ ๋ฉˆ์ถฐ์•ผ ํ•œ๋‹คโ€™์™€ ๊ฐ™์ด ๋ฌธ์ œ์˜ ๊ทผ๋ณธ ์›์ธ์„ ํŒŒ์•…ํ•˜๊ณ  ๋” ๋†’์€ ์ˆ˜์ค€์˜ ํ•ด๊ฒฐ์ฑ…์„ ์ œ์‹œํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. AI ์—์ด์ „ํŠธ๊ฐ€ ์ด๋Ÿฌํ•œ ํ”„๋ ˆ์ž„ ์ „ํ™˜์„ ์Šค์Šค๋กœ ์ž˜ ์ˆ˜ํ–‰ํ•˜๊ธฐ๋Š” ๋งค์šฐ ์–ด๋ ค์šธ ๊ฒƒ์ด๋ผ๋Š” ๊ฒƒ์ด ๊ทธ๋“ค์˜ ์ฃผ์žฅ์ž…๋‹ˆ๋‹ค.

AI์˜ ํ•œ๊ณ„์™€ ์ธ๊ฐ„์˜ ๊ณ ์œ ํ•œ ๊ฐ€์น˜: ์˜ˆ์ˆ ๊ณผ ๊ฒฝํ—˜์˜ ์˜์—ญ

AI๋Š” 100๋ช…์˜ ๊ฐ€์ƒ ์ธ๋ฌผ์„ ์‹œ๋ฎฌ๋ ˆ์ด์…˜ํ•˜์—ฌ ์•„์ด๋””์–ด๋ฅผ ๊ตฌ์ƒํ•˜๋Š” ๋“ฑ ์ž๋™ํ™” ์˜์—ญ์„ ๋„“ํ˜€๊ฐˆ ๊ฒƒ์ž…๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ํ‚ค์–ด๋Ÿฐ์€ โ€œ๊ถ๊ทน์ ์œผ๋กœ ์„ธ์ƒ์— ๋ฌด์–ธ๊ฐ€๋ฅผ ๋‚ด๋†“๊ฑฐ๋‚˜, ์–ด๋–ค ์ฃผ์žฅ์„ ํ•˜๊ฑฐ๋‚˜, ๋‹น์‹ ๋งŒ์˜ ๊ฒƒ์œผ๋กœ ๋งŒ๋“ค๊ณ  ์‹ถ๋‹ค๋ฉด, ๋ชจ๋“  ๊ฒƒ์„ ์™„์ „ํžˆ ์ž๋™ํ™”ํ•  ์ˆ˜๋Š” ์—†๋‹คโ€๊ณ  ๋‹จ์–ธํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๋งˆ์น˜ ์˜ˆ์ˆ ์„ ๋งŒ๋“œ๋Š” ๊ฒƒ๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค. ์ง„์ •์œผ๋กœ โ€˜๋‚˜๋งŒ์˜ ๊ฒƒโ€™์„ ๋งŒ๋“ค๊ณ  ์‹ถ๋‹ค๋ฉด, ๊ทธ๊ฒƒ์€ ๋‹น์‹ ์—๊ฒŒ์„œ ๋‚˜์˜ค๊ฑฐ๋‚˜ ์–ด๋–ค ์‹์œผ๋กœ๋“  ๋‹น์‹ ๊ณผ ์—ฐ๊ฒฐ๋˜์–ด์•ผ ํ•ฉ๋‹ˆ๋‹ค.

๋Œ€๊ทœ๋ชจ ์–ธ์–ด ๋ชจ๋ธ(LLM)์€ ์ง€๋‚œ ์ˆ˜๋…„๊ฐ„ โ€˜์ƒ์ž ์•ˆ์— ๊ฐ‡ํ˜€โ€™ ํ•™์Šตํ–ˆ๊ธฐ ๋•Œ๋ฌธ์— ์„ธ์ƒ์˜ ๋งฅ๋ฝ์„ ์™„์ „ํžˆ ์ดํ•ดํ•˜์ง€ ๋ชปํ•˜๋ฉฐ, ๊ทธ ๊ฒฐ๊ณผ๋ฌผ์€ ๋‹ค์†Œ โ€˜์ œ๋„ค๋ฆญ(generic)โ€˜ํ•˜๊ณ  ๊ฐœ์ธ์ ์ธ ์ƒํ™ฉ์— ๋œ ๋งž์ถคํ™”๋  ์ˆ˜๋ฐ–์— ์—†์Šต๋‹ˆ๋‹ค. ์ง„์ •์œผ๋กœ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๊ฑฐ๋‚˜ ์‚ฌ๋žŒ๋“ค์—๊ฒŒ ๊ณต๊ฐ์„ ์–ป๋Š” ์ œํ’ˆ, ์˜ˆ์ˆ ์„ ๋งŒ๋“ค๋ ค๋ฉด, ์ •ํ™•ํ•œ ๋ฌธ์ œ์™€ ํ˜•ํƒœ์— ๋งž๊ฒŒ ์„ธ๋ฐ€ํ•˜๊ฒŒ ์กฐ์ •๋˜์–ด์•ผ ํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด ๊ณผ์ •์—์„œ LLM์€ ์ธ๊ฐ„์˜ ๋งŽ์€ ๋„์›€์ด ํ•„์š”ํ•ฉ๋‹ˆ๋‹ค.

๋Œ„์€ ์ธ๊ณต ์ผ๋ฐ˜ ์ง€๋Šฅ(AGI, Artificial General Intelligence)์˜ ๊ธฐ์ค€์„ โ€œ์—์ด์ „ํŠธ๊ฐ€ 24์‹œ๊ฐ„ ๋‚ด๋‚ด ๊ฒฝ์ œ์ ์œผ๋กœ ์ˆ˜์ต์„ฑ์ด ์žˆ๊ฒŒ ์ž‘๋™ํ•˜๋Š” ์‹œ์ โ€์œผ๋กœ ์ œ์‹œํ•˜๋ฉฐ, ์šฐ๋ฆฌ๋Š” ์•„์ง ๊ทธ ๋‹จ๊ณ„์— ํ›จ์”ฌ ๋ชป ๋ฏธ์นœ๋‹ค๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ํ˜„์žฌ์˜ AI๋Š” ์ž˜ ์ •์˜๋œ ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜๋Š” ์žˆ์ง€๋งŒ, ์Šค์Šค๋กœ ํ”„๋ ˆ์ž„์„ ๋ณ€๊ฒฝํ•˜๊ฑฐ๋‚˜, ํ•œ ์ž‘์—…์„ ๋งˆ์น˜๊ณ  ๋‹ค์Œ ์ž‘์—…์„ ์„ ํƒํ•˜๋Š” ๋“ฑ ๋Š์ž„์—†์ด ์ฐฝ์˜์ ์ธ ๊ฒฐ์ •์„ ๋‚ด๋ฆฌ๋Š” ์ˆ˜์ค€์—๋Š” ๋„๋‹ฌํ•˜์ง€ ๋ชปํ–ˆ์Šต๋‹ˆ๋‹ค.

ํ‚ค์–ด๋Ÿฐ์€ ์Œ์•… ๋ถ„์•ผ์˜ ๊ฒฝํ—˜์„ ๋ฐ”ํƒ•์œผ๋กœ ์ด ์ ์„ ๋”์šฑ ๋ช…ํ™•ํžˆ ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค. ์Œ์•…์€ ์ž‘๊ณก(์‹œ์ž‘), ์—ฐ์Šต(์ค‘๊ฐ„), ์—ฐ์ฃผ(๋)์˜ ๊ณผ์ •์„ ๊ฑฐ์นฉ๋‹ˆ๋‹ค. AI๊ฐ€ ์—ฐ์Šต์ฒ˜๋Ÿผ ๋ฐ˜๋ณต์ ์ธ ์ค‘๊ฐ„ ๊ณผ์ •์„ ์ž๋™ํ™”ํ•  ์ˆ˜ ์žˆ์ง€๋งŒ, ์•„๋ฌด๊ฒƒ๋„ ์—†๋Š” ์ƒํƒœ์—์„œ ๋ฉœ๋กœ๋””๋ฅผ ์ฐฝ์กฐํ•˜๋Š” โ€˜์ž‘๊ณกโ€™์˜ ์ˆœ๊ฐ„๊ณผ, ๊ด€๊ฐ ์•ž์—์„œ ๊ฐ์ •์„ ๋‹ด์•„ ๊ณก์„ โ€˜์—ฐ์ฃผโ€™ํ•˜๋Š” ๋ผ์ด๋ธŒ ํผํฌ๋จผ์Šค์˜ ์ˆœ๊ฐ„์€ ์ธ๊ฐ„๋งŒ์ด ํ•  ์ˆ˜ ์žˆ๋Š” ํŠน๋ณ„ํ•œ ์˜์—ญ์ž…๋‹ˆ๋‹ค. ์ด์ฒ˜๋Ÿผ AI ์‹œ๋Œ€์—๋„ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ์ด๋‚˜ ๋‹ค๋ฅธ ์ง€์‹ ๋…ธ๋™์—์„œ โ€˜์‹œ์ž‘โ€™๊ณผ โ€˜๋โ€™์˜ ํŠน๋ณ„ํ•œ ์ˆœ๊ฐ„๋“ค์€ ์ธ๊ฐ„์˜ ๋ชซ์œผ๋กœ ๋‚จ์„ ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๋ฏธ๋ž˜๋ฅผ ์œ„ํ•œ ์ œ์–ธ: ๋‹น์‹ ์˜ โ€˜์•„๋ฆ„๋‹ค์›€โ€™์„ ์ฐพ์•„๋ผ

์ด๋Ÿฌํ•œ ๋ณ€ํ™”๋Š” ๋‘๋ ค์šธ ์ˆ˜๋„ ์žˆ์ง€๋งŒ, ๋™์‹œ์— ํฐ ๊ธฐํšŒ๊ฐ€ ๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ฐ˜๋ณต์ ์ด๊ณ  ์ง€๋ฃจํ•œ ์—…๋ฌด๋Š” AI์— ๋งก๊ธฐ๊ณ , ์ธ๊ฐ„์€ ๋”์šฑ ์ฐฝ์˜์ ์ด๊ณ  ํฅ๋ฏธ๋กœ์šด ์ผ์— ์ง‘์ค‘ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋ฉ๋‹ˆ๋‹ค. ํ‚ค์–ด๋Ÿฐ์€ โ€œ๋ฌด์—‡์ด ๋‹น์‹ ์—๊ฒŒ ๊ธฐ์จ์„ ์ฃผ๊ณ , ๋ถˆ์„ ์ง€ํ”ผ๊ณ , ํฅ๋ถ„ํ•˜๊ฒŒ ๋งŒ๋“œ๋Š”์ง€โ€ ์ฐพ์•„์•ผ ํ•œ๋‹ค๊ณ  ์กฐ์–ธํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๊ฒƒ์ด ์•„๋ฆ„๋‹ค์šด ์ฝ”๋“œ๋“ , ์ •๊ตํ•œ ์ถ”์ƒํ™”๋“ , ๋งค๋ ฅ์ ์ธ ๋””์ž์ธ์ด๋“ , ์•„๋‹ˆ๋ฉด ํ›Œ๋ฅญํ•œ ๋ฌธ๊ตฌ๋“  ์ƒ๊ด€์—†์Šต๋‹ˆ๋‹ค.

AI ์‹œ๋Œ€์˜ ์—”์ง€๋‹ˆ์–ด๋Š” ๋‹จ์ˆœํžˆ ์ฝ”๋“œ๋ฅผ ์ž‘์„ฑํ•˜๋Š” ๊ฒƒ์„ ๋„˜์–ด, ๊ด€๋ฆฌ์ž๋‚˜ ์ œํ’ˆ ์ฑ…์ž„์ž์™€ ๊ฐ™์€ ๋” ๋„“์€ ์—ญํ• ์„ ์ˆ˜ํ–‰ํ•˜๊ฒŒ ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ํ•ต์‹ฌ์€ โ€˜์•„๋ฆ„๋‹ค์šด ๊ฒƒโ€™์„ ๋งŒ๋“œ๋Š” ๋ฐ ์ง‘์ค‘ํ•˜๊ณ , AI๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์—๋„ˆ์ง€๋ฅผ ์†Œ๋ชจํ•˜๋Š” ๋Œ€์‹  ์—๋„ˆ์ง€๋ฅผ ์–ป๋Š” ๋ฐฉ์‹์œผ๋กœ ์ผํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๊ฒฐ๋ก ์ ์œผ๋กœ โ€˜AI ์ƒŒ๋“œ์œ„์น˜โ€™ ๋ชจ๋ธ์€ AI๊ฐ€ ์ธ๊ฐ„์˜ ์ผ์ž๋ฆฌ๋ฅผ ์™„์ „ํžˆ ๋นผ์•—์„ ๊ฒƒ์ด๋ผ๋Š” ๋ง‰์—ฐํ•œ ๋‘๋ ค์›€ ๋Œ€์‹ , ์ธ๊ฐ„๊ณผ AI๊ฐ€ ์ƒํ˜ธ ๋ณด์™„์ ์œผ๋กœ ํ˜‘๋ ฅํ•˜์—ฌ ๋” ํฐ ๊ฐ€์น˜๋ฅผ ์ฐฝ์ถœํ•  ์ˆ˜ ์žˆ๋Š” ๋ฏธ๋ž˜๋ฅผ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค. AI๋Š” ํšจ์œจ์ ์ธ ์กฐ๋ ฅ์ž์ด์ž ๋„๊ตฌ์ด๋ฉฐ, ์ธ๊ฐ„์€ ๊ทธ ๋„๊ตฌ๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์„ธ์ƒ์— ์ž์‹ ๋งŒ์˜ ๋…์ฐฝ์ ์ธ โ€˜๋ง›โ€™๊ณผ โ€˜์•„๋ฆ„๋‹ค์›€โ€™์„ ๋”ํ•˜๋Š” ์กด์žฌ๋กœ ๊ฑฐ๋“ญ๋‚  ๊ฒƒ์ž…๋‹ˆ๋‹ค.


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๋‰ด์š•์˜ โ€˜์ฅ ์ „์Ÿโ€™ ๊ทธ ์ด๋ฉด: ํ˜์˜ค์˜ ์—ญ์‚ฌ์™€ ๊ณต์กด์˜ ๊ฐ€๋Šฅ์„ฑ

๋‰ด์š•์‹œ์˜ ๋ด„์€ ํ‘ธ๋ฅธ ๋‚˜๋ญ‡์žŽ๊ณผ ํ™œ๊ธฐ ๋„˜์น˜๋Š” ์•ผ์™ธ ์นดํŽ˜, ๊ทธ๋ฆฌ๊ณ  ์–ด๊น€์—†์ด ๋ชจ์Šต์„ ๋“œ๋Ÿฌ๋‚ด๋Š” ์ฅ๋“ค๋กœ ํŠน์ง•์ง€์–ด์ง‘๋‹ˆ๋‹ค. ๋„์‹œ์˜ ๊ทธ๋ฆผ์ž ์†์—์„œ ์ธ๊ฐ„๊ณผ ๊ฐ€์žฅ ๊ฐ€๊นŒ์ด ๊ณต์กดํ•˜๋Š” ์ด ์ž‘์€ ์ƒ๋ช…์ฒด๋“ค์€ ์˜ค๋žซ๋™์•ˆ ํ˜์˜ค์™€ ๊ฒฝ๋ฉธ์˜ ๋Œ€์ƒ์ด์—ˆ์ฃ . ํ•˜์ง€๋งŒ ๊ณผ์—ฐ ์ฅ๋“ค์€ ์šฐ๋ฆฌ๊ฐ€ ์ƒ๊ฐํ•˜๋Š” ๋งŒํผ โ€˜์•…๋‹นโ€™์ผ๊นŒ์š”? <ํ”„๋ฆฌ์ฝ”๋…ธ๋ฏน์Šค ๋ผ๋””์˜ค(Freakonomics Radio)>๋Š” ๋‰ด์š•์‹œ์˜ โ€˜์ฅ ์ „์Ÿโ€™์„ ํ†ตํ•ด ์ฅ์— ๋Œ€ํ•œ ์šฐ๋ฆฌ์˜ ๋ฟŒ๋ฆฌ ๊นŠ์€ ์ธ์‹์„ ํŒŒํ—ค์น˜๊ณ , ๊ทธ ์ด๋ฉด์— ์ˆจ๊ฒจ์ง„ ์—ญ์‚ฌ์ , ๋ฌธํ™”์ , ์ƒ๋ฌผํ•™์  ์ง„์‹ค์„ ํƒ๊ตฌํ•ฉ๋‹ˆ๋‹ค.

๋‰ด์š•์‹œ์˜ โ€˜์ฅ ์ „์Ÿโ€™: ๋„์‹œ์˜ ๋Š์ž„์—†๋Š” ๋„์ „

2022๋…„ ๊ฐ€์„, ๋‰ด์š•์‹œ ์ •๋ถ€ ์›น์‚ฌ์ดํŠธ์—๋Š” ์ด์ƒ‰์ ์ธ ์ฑ„์šฉ ๊ณต๊ณ ๊ฐ€ ์˜ฌ๋ผ์™”์Šต๋‹ˆ๋‹ค. โ€œ์ด์ƒ์ ์ธ ํ›„๋ณด์ž๋Š” ๋†’์€ ๋™๊ธฐ ๋ถ€์—ฌ์™€ ๋‹ค์†Œ ํ”ผ์— ๊ตถ์ฃผ๋ฆฐ(bloodthirsty) ์„ฑํ–ฅ์„ ๊ฐ€์ง€๊ณ  ์žˆ์œผ๋ฉฐ, ๋ฐ์ดํ„ฐ ์ˆ˜์ง‘, ๊ธฐ์ˆ  ํ˜์‹ , ๊ทธ๋ฆฌ๊ณ  ๋Œ€๋Ÿ‰ ํ•™์‚ด(wholesale slaughter)์„ ํฌํ•จํ•œ ๋‹ค์–‘ํ•œ ๊ฐ๋„์—์„œ ๋ชจ๋“  ํ•ด๊ฒฐ์ฑ…์„ ๋ชจ์ƒ‰ํ•  ์˜์ง€๊ฐ€ ์žˆ๋Š” ์‚ฌ๋žŒ์ด์–ด์•ผ ํ•œ๋‹ค.โ€ ๋Œ€๋Ÿ‰ ํ•™์‚ด์„ ์š”๊ตฌํ•˜๋Š” ์ •๋ถ€ ์ง์ฑ…์ด๋ผ๋‹ˆ, ๋†€๋ผ์›€์„ ๊ธˆ์น˜ ๋ชปํ•  ๋‚ด์šฉ์ด์—ˆ์ฃ . ์ด ๊ณต๊ณ ์˜ ๋ฐฐํ›„์—๋Š” ๋‹น์‹œ ๋‰ด์š• ์‹œ์žฅ์ด์—ˆ๋˜ ์—๋ฆญ ์•„๋‹ด์Šค(Eric Adams)๊ฐ€ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ฅ์— ๋Œ€ํ•œ ๋งน๋ ฌํ•œ ํ˜์˜ค๊ฐ์„ ๊ณต๊ณต์—ฐํžˆ ๋“œ๋Ÿฌ๋‚ด๋ฉฐ โ€œ์ฅ๋Š” ๋‹น์‹ ์—๊ฒŒ ํŠธ๋ผ์šฐ๋งˆ๋ฅผ ์•ˆ๊ฒจ์ค€๋‹ค. ๋‚˜๋Š” ์ฅ๋ฅผ ์ฆ์˜คํ•œ๋‹คโ€๊ณ  ๋งํ–ˆ์Šต๋‹ˆ๋‹ค.

์•„๋‹ด์Šค ์‹œ์žฅ์˜ โ€˜์ฅ ์ „์Ÿโ€™์€ ๋‰ด์š•์‹œ์˜ ๊ณ ์งˆ์ ์ธ ๋ฌธ์ œ์— ๋Œ€ํ•œ ๊ฐ•๋ ฅํ•œ ๋Œ€์‘์ฑ…์œผ๋กœ ์‹œ์ž‘๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด โ€˜์˜์›…โ€™์„ ์ฐพ๋˜ ๊ทธ์˜ ๋…ธ๋ ฅ์€ ์ผ€์ดํ‹ฐ ์ฝ”๋ผ๋””(Katy Corradi)๋ผ๋Š” ์ธ๋ฌผ์„ ๋งŒ๋‚˜ ๊ฒฐ์‹ค์„ ๋งบ์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋…€๋Š” โ€œ๋Œ€๋‹ดํ•œ ํƒœ๋„, ๊ธฐ๋ฐœํ•œ ์œ ๋จธ, ๊ทธ๋ฆฌ๊ณ  ์ „๋ฐ˜์ ์ธ โ€˜๋ฐฐ๋“œ์• ์Šค(badass)โ€™ ๊ธฐ์šดโ€์„ ๊ฐ–์ถ˜ ์ธ๋ฌผ์ด๋ผ๋Š” ์ฑ„์šฉ ๊ณต๊ณ ์˜ ๋ฌ˜์‚ฌ์— ์™„๋ฒฝํ•˜๊ฒŒ ๋ถ€ํ•ฉํ•˜๋Š” ๋“ฏํ–ˆ์Šต๋‹ˆ๋‹ค. ์ฝ”๋ผ๋””๋Š” ๋‰ด์š•์‹œ์˜ โ€˜์‹œ ์ „์—ญ ์„ค์น˜๋ฅ˜ ์™„ํ™” ์ฑ…์ž„์ž(citywide director of rodent mitigation)โ€™, ์ผ๋ช… โ€˜์ฅ ์ฐจ๋ฅด(rat czar)โ€˜๋กœ ์ž„๋ช…๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋…€๋Š” ์ฅ ๋ฌธ์ œ์— ๋Œ€ํ•ด ๋” ๋งŽ์€ ์‚ฌ๋žŒ์ด ์ด์•ผ๊ธฐํ• ์ˆ˜๋ก ํ•ด๊ฒฐ์— ๋„์›€์ด ๋  ๊ฒƒ์ด๋ผ๊ณ  ๋ฏฟ์—ˆ์Šต๋‹ˆ๋‹ค.

๋‰ด์š•์„ ๋น„๋กฏํ•œ ๋งŽ์€ ๋Œ€๋„์‹œ๋“ค์€ ์ฝ”๋กœ๋‚˜19 ํŒฌ๋ฐ๋ฏน ์ดํ›„ ์ฅ ๊ฐœ์ฒด์ˆ˜๊ฐ€ ๊ธ‰์ฆํ•˜๋Š” ํ˜„์ƒ์„ ๊ฒช์—ˆ์Šต๋‹ˆ๋‹ค. ์ฝ”๋ผ๋””๋Š” ์ฅ ๋ฌธ์ œ ํ•ด๊ฒฐ์˜ ํ•ต์‹ฌ์ด ๋ฐ”๋กœ โ€˜์œ„์ƒ(sanitation)โ€˜์— ์žˆ๋‹ค๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋…€๋Š” ์–ด๋ฆฐ ์‹œ์ ˆ, ์ง‘ ๋’คํŽธ ์ฒ ๋กœ๋ณ€์˜ ๋ฌด์„ฑํ•œ ์žก์ดˆ๊ฐ€ ์ฅ๋“ค์˜ ์™„๋ฒฝํ•œ ์„œ์‹์ง€๊ฐ€ ๋˜๋Š” ๊ฒƒ์„ ๋ชฉ๊ฒฉํ•˜๊ณ  ์ด์›ƒ๋“ค๊ณผ ํ•จ๊ป˜ ์ฒญ์› ์šด๋™์„ ๋ฒŒ์—ฌ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•œ ๊ฒฝํ—˜์ด ์žˆ์Šต๋‹ˆ๋‹ค. ์ƒ๋ฌผํ•™ ํ•™์‚ฌ ํ•™์œ„์™€ ๋„์‹œ ์ง€์†๊ฐ€๋Šฅ์„ฑ ์„์‚ฌ ํ•™์œ„๋ฅผ ๊ฐ€์ง„ ๊ทธ๋…€๋Š” ๋‰ด์š•์‹œ ๊ต์œก๋ถ€์˜ ์ง€์†๊ฐ€๋Šฅ์„ฑ ๋ถ€์„œ์—์„œ ์“ฐ๋ ˆ๊ธฐ ๊ฐ์ถ• ํ”„๋กœ๊ทธ๋žจ์„ ์šด์˜ํ•˜๋ฉฐ ์ฅ ๋ฌธ์ œ์— ๊นŠ์ด ๊ด€์—ฌํ•˜๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋…€๋Š” โ€œ์“ฐ๋ ˆ๊ธฐ์™€ ์ฅ๋Š” ๋–ผ๋ ค์•ผ ๋—„ ์ˆ˜ ์—†๋Š” ๊ด€๊ณ„โ€๋ผ๋ฉฐ, ํ•™๊ต์˜ ์“ฐ๋ ˆ๊ธฐ ๊ด€๋ฆฌ ๊ฐœ์„ ์„ ํ†ตํ•ด ์ฅ๋“ค์˜ ๋จน์ด ์ ‘๊ทผ์„ฑ์„ ์ค„์ด๋Š” ๋ฐ ์ง‘์ค‘ํ–ˆ์Šต๋‹ˆ๋‹ค.

๋‰ด์š•์‹œ์˜ ์ฅ ๊ฐœ์ฒด์ˆ˜๋ฅผ ์ •ํ™•ํžˆ ํŒŒ์•…ํ•˜๊ธฐ๋Š” ์–ด๋ ต์ง€๋งŒ, ์ผ๋ถ€ ์ถ”์ •์น˜์— ๋”ฐ๋ฅด๋ฉด 300๋งŒ ๋งˆ๋ฆฌ์— ๋‹ฌํ•  ์ˆ˜๋„ ์žˆ๋‹ค๊ณ  ํ•ฉ๋‹ˆ๋‹ค. ์ฝ”๋ผ๋””๋Š” ์ˆซ์ž์— ์ง‘์ฐฉํ•˜๊ธฐ๋ณด๋‹ค ์ฅ๊ฐ€ ์ธ๊ฐ„๊ณผ โ€˜์‹ํƒ์„ ๊ณต์œ ํ•˜๋Š” ๋™๋ฌผ(commensal)โ€˜์ด๋ผ๋Š” ์ ์— ์ฃผ๋ชฉํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ์ฅ๋“ค์ด ์ธ๊ฐ„์ด ๋งŒ๋“ค์–ด ๋†“์€ ๋„์‹œ ๊ณต๊ฐ„์—์„œ ์ธ๊ฐ„์˜ ์Œ์‹๋ฌผ ์“ฐ๋ ˆ๊ธฐ๋ฅผ ๋จน์œผ๋ฉฐ ์‚ด์•„๊ฐ€๋Š” ์กด์žฌ์ž„์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค.

์ฅ์˜ ์ง€๋Šฅ๊ณผ ์ƒ์กด ์ „๋žต: ๋„์‹œ์˜ ์ˆจ๊ฒจ์ง„ ์ง€๋ฐฐ์ž

์šฐ๋ฆฌ๋Š” ์ฅ๋ฅผ ํ”ํžˆ โ€˜ํ˜์˜ค์Šค๋Ÿฌ์šดโ€™ ์กด์žฌ๋กœ ์—ฌ๊ธฐ์ง€๋งŒ, ๊ทธ๋“ค์˜ ์ง€๋Šฅ๊ณผ ์ƒ์กด ๋Šฅ๋ ฅ์€ ๋†€๋ผ์šธ ์ •๋„์ž…๋‹ˆ๋‹ค. ๊ณผํ•™ ์ €๋„๋ฆฌ์ŠคํŠธ์ด์ž <ํ•ด์ถฉ(Pests)>์˜ ์ €์ž์ธ ๋ฒ ์„œ๋‹ˆ ๋ธŒ๋ฃฉ์…”(Bethany Brookshire)๋Š” ์ฅ๊ฐ€ โ€œ์ธ๊ฐ„์„ ์ œ์™ธํ•˜๊ณ ๋Š” ๋„์‹œ ๊ณต๊ฐ„์„ ๊ฐ€์žฅ ์ž˜ ํ™œ์šฉํ•˜๋Š” ์ƒ๋ฌผโ€์ด๋ผ๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ์ฝ”๋ผ๋”” ์—ญ์‹œ ์ฅ์˜ โ€˜๊ตํ™œํ•จ(savviness)โ€˜๊ณผ โ€˜์ ์‘๋ ฅ(adaptability)โ€˜์ด ๋งค์šฐ ๋›ฐ์–ด๋‚˜๋‹ค๊ณ  ํ‰๊ฐ€ํ•˜๋ฉฐ, ์ตœ๊ทผ ์—ฐ๊ตฌ๋“ค์€ ์ฅ์˜ โ€˜๊ณต๊ฐ(empathy)โ€™, โ€˜์›ƒ์Œ(laughing)โ€™, โ€˜์ดํƒ€์ฃผ์˜(altruism)โ€˜์™€ ๊ฐ™์€ ํŠน์„ฑ๊นŒ์ง€ ๋ฐํ˜€๋‚ด๊ณ  ์žˆ๋‹ค๊ณ  ์–ธ๊ธ‰ํ•ฉ๋‹ˆ๋‹ค. ์‹ฌ์ง€์–ด ์ฅ๋“ค์€ ์ƒˆ๋กœ์šด ๋จน์ด์›์— ์ ‘๊ทผํ•  ๋•Œ ๋œ ์ง€๋ฐฐ์ ์ธ ์ฅ๋ฅผ ๋จผ์ € ๋ณด๋‚ด ์•ˆ์ „์„ฑ์„ ํ™•์ธํ•˜๋Š” ์˜๋ฆฌํ•œ ์ƒ์กด ์ „๋žต์„ ๊ตฌ์‚ฌํ•˜๊ธฐ๋„ ํ•ฉ๋‹ˆ๋‹ค.

์˜ค๋Š˜๋‚  ์šฐ๋ฆฌ๊ฐ€ ํ”ํžˆ ๋ณด๋Š” ๊ฐˆ์ƒ‰ ์ฅ(Rattus norvegicus), ์ผ๋ช… ๋…ธ๋ฅด์›จ์ด ์ฅ๋Š” 18์„ธ๊ธฐ ์œ ๋Ÿฝ ์„ ๋ฐ•์„ ํ†ตํ•ด ๋‰ด์š•์— ๋“ค์–ด์˜จ ๊ฒƒ์œผ๋กœ ์ถ”์ •๋ฉ๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ด ์ฅ์˜ ๊ธฐ์›์€ ๋…ธ๋ฅด์›จ์ด๊ฐ€ ์•„๋‹Œ ๋ชฝ๊ณจ ์ง€์—ญ์ด๋ฉฐ, ์ฅ๋ฅผ ์‹ซ์–ดํ•˜๋Š” ์‚ฌ๋žŒ๋“ค์ด ๊ทธ ์ด๋ฆ„์„ ์‹ซ์–ดํ•˜๋Š” ๋Œ€์ƒ์— ๋ถ™์ธ ๊ฒฐ๊ณผ๋ผ๊ณ  ๋ธŒ๋ฃฉ์…”๋Š” ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค.

์ฅ์— ๋Œ€ํ•œ ํ˜์˜ค์˜ ์—ญ์‚ฌ: ํ‘์‚ฌ๋ณ‘์˜ ์˜ค๋ช…

์ฅ๊ฐ€ ์ธ๋ฅ˜์—๊ฒŒ ํ˜์˜ค์Šค๋Ÿฌ์šด ์กด์žฌ๋กœ ๊ฐ์ธ๋œ ๊ฐ€์žฅ ํฐ ์ด์œ ๋Š” ๋ฐ”๋กœ โ€˜์งˆ๋ณ‘ ์ „ํŒŒโ€™์— ๋Œ€ํ•œ ์ธ์‹, ํŠนํžˆ โ€˜ํ‘์‚ฌ๋ณ‘(Black Death)โ€˜๊ณผ์˜ ์—ฐ๊ด€์„ฑ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. 14์„ธ๊ธฐ ์œ ๋Ÿฝ์„ ํœฉ์“ธ๋ฉฐ ์ธ๊ตฌ์˜ ์ ˆ๋ฐ˜์„ ์ฃฝ์Œ์œผ๋กœ ๋ชฐ์•„๋„ฃ์—ˆ๋˜ ํ‘์‚ฌ๋ณ‘์€ ์˜ค๋žซ๋™์•ˆ ์ฅ์™€ ์ฅ๋ฒผ๋ฃฉ์ด ์ฃผ๋ฒ”์œผ๋กœ ์ง€๋ชฉ๋˜์–ด ์™”์Šต๋‹ˆ๋‹ค.

ํ•˜์ง€๋งŒ ์ตœ๊ทผ ๊ณผํ•™๊ณ„์—์„œ๋Š” ์ฅ์™€ ํ‘์‚ฌ๋ณ‘์˜ ์—ฐ๊ด€์„ฑ์— ๋Œ€ํ•œ ๊ธฐ์กด์˜ ํ†ต๋…์— ๋„์ „ํ•˜๋Š” ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋“ค์ด ๋‚˜์˜ค๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์˜ค์Šฌ๋กœ ๋Œ€ํ•™์˜ ์ƒํƒœ ๋ฐ ์ง„ํ™”ํ•™ ๊ต์ˆ˜์ธ ๋‹์Šค ํฌ๋ฆฌ์Šคํ‹ฐ์•ˆ ์Šคํ…์„ธ์Šค(Nils Christian Stenseth)๋Š” 2018๋…„ <๋ฏธ๊ตญ ๊ตญ๋ฆฝ๊ณผํ•™์› ํšŒ๋ณด(Proceedings of the National Academy of Sciences)>์— ๋ฐœํ‘œํ•œ ๋…ผ๋ฌธ์—์„œ ๋‹ค๋ฅธ ๋ชจ๋ธ์„ ์ œ์‹œํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” 1300๋…„๋Œ€๋ถ€ํ„ฐ 1700๋…„๋Œ€๊นŒ์ง€์˜ ํ‘์‚ฌ๋ณ‘ ์‚ฌ๋ง๋ฅ ๊ณผ ์ „ํŒŒ ์†๋„๋ฅผ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ, โ€œ์ฅ๊ฐ€ ์œ ๋Ÿฝ์—์„œ ํ‘์‚ฌ๋ณ‘ ํ™•์‚ฐ์— ์ฃผ์š” ์—ญํ• ์„ ํ–ˆ์„ ๊ฐ€๋Šฅ์„ฑ์€ ๋งค์šฐ ๋‚ฎ๋‹คโ€๊ณ  ๊ฒฐ๋ก  ๋‚ด๋ ธ์Šต๋‹ˆ๋‹ค. ์ฅ๋ฒผ๋ฃฉ์ด ์ฅ์˜ ์ฃฝ์Œ ์ดํ›„์—์•ผ ์ธ๊ฐ„์—๊ฒŒ ์˜ฎ๊ฒจ๊ฐ€๋Š” ์†๋„๋ฅผ ๊ฐ์•ˆํ•  ๋•Œ, ํ‘์‚ฌ๋ณ‘์˜ ๋น ๋ฅธ ์ „ํŒŒ ์†๋„๋Š” ์ฅ ๋ชจ๋ธ๋กœ๋Š” ์„ค๋ช…ํ•˜๊ธฐ ์–ด๋ ต๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๋Œ€์‹  ๊ทธ์˜ ์—ฐ๊ตฌํŒ€์€ โ€˜์ธ๊ฐ„ ์ฒด์™ธ ๊ธฐ์ƒ์ถฉ(human ectoparasites)โ€™, ์ฆ‰ โ€˜๋ชธ๋‹ˆ(body lice)โ€˜๋‚˜ โ€˜์ธ๊ฐ„ ๋ฒผ๋ฃฉ(human fleas)โ€˜์ด ๋” ์œ ๋ ฅํ•œ ์ „ํŒŒ ๋งค๊ฐœ์ฒด์˜€์„ ๊ฐ€๋Šฅ์„ฑ์ด ๋†’๋‹ค๊ณ  ์ฃผ์žฅํ–ˆ์Šต๋‹ˆ๋‹ค.

ํ•˜๋ฒ„๋“œ ๋Œ€ํ•™๊ต ๊ฒฝ์ œํ•™ ๊ต์ˆ˜์ด์ž ๋„์‹œ ์ „๋ฌธ๊ฐ€์ธ ์—๋“œ ๊ธ€๋ ˆ์ด์ €(Ed Glaeser) ์—ญ์‹œ ์ด ๊ฒฌํ•ด์— ๋™์˜ํ•˜๋ฉฐ, ์ฅ๊ฐ€ โ€˜์ฃ„์ฑ…๊ฐ(guilt)โ€˜์„ ๊ฐ€์งˆ ๋ฆฌ ์—†์œผ๋‹ˆ ๊ทธ ๋น„๋‚œ์€ ํ‘์‚ฌ๋ณ‘์˜ ์›์ธ๊ท ์ธ โ€˜์˜ˆ๋ฅด์‹œ๋‹ˆ์•„ ํŽ˜์Šคํ‹ฐ์Šค(Yersinia pestis)โ€˜์—๊ฒŒ ๋Œ๋ ค์•ผ ํ•œ๋‹ค๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ๋น„๋ก ์ฅ๊ฐ€ 19์„ธ๊ธฐ ์ดํ›„์˜ ์„ธ ๋ฒˆ์งธ ํ‘์‚ฌ๋ณ‘ ํŒฌ๋ฐ๋ฏน์—๋Š” ์ค‘์š”ํ•œ ์—ญํ• ์„ ํ–ˆ์„์ง€๋ผ๋„, ๊ฐ€์žฅ ์œ ๋ช…ํ•œ ์ค‘์„ธ ํ‘์‚ฌ๋ณ‘์˜ ์ฃผ๋ฒ”์€ ์•„๋‹ˆ๋ผ๋Š” ๊ฒƒ์ด์ฃ .

ํ˜„๋Œ€ ๋„์‹œ์—์„œ ์ฅ๊ฐ€ ๋ฏธ์น˜๋Š” ์˜ํ–ฅ: ๊ฒฝ์ œ์ , ์ •์‹ ์ , ๊ทธ๋ฆฌ๊ณ  ์ž ์žฌ์  ์œ„ํ˜‘

๊ทธ๋ ‡๋‹ค๋ฉด ํ˜„๋Œ€ ๋„์‹œ์—์„œ ์ฅ๋Š” ์–ด๋–ค ์˜ํ–ฅ์„ ๋ฏธ์น ๊นŒ์š”? ์ „์ง ์ฅ ์ฐจ๋ฅด ์ฝ”๋ผ๋””๋Š” ์ฅ๊ฐ€ ์—ฌ๋Ÿฌ ๊ฐ€์ง€ ํ˜•ํƒœ๋กœ โ€˜๋ถ€์ •์ ์ธ ์™ธ๋ถ€ ํšจ๊ณผ(negative externalities)โ€˜๋ฅผ ์œ ๋ฐœํ•œ๋‹ค๊ณ  ์ง€์ ํ•ฉ๋‹ˆ๋‹ค.

  • ๊ฒฝ์ œ์  ํ”ผํ•ด: ์ฅ๋Š” ์ „์„ , ๊ฑด๋ฌผ ๊ธฐ์ดˆ ๋“ฑ ๊ฑฐ์˜ ๋ชจ๋“  ๊ฒƒ์„ ๊ฐ‰์•„๋จน๋Š” ์Šต์„ฑ ๋•Œ๋ฌธ์— ์žฌ์‚ฐ์— ์ƒ๋‹นํ•œ ํ”ผํ•ด๋ฅผ ์ž…ํž™๋‹ˆ๋‹ค. ์ €์žฅ๋œ ์‹๋Ÿ‰๊ณผ ๊ณก๋ฌผ์—๋„ ์†์ƒ์„ ์ž…ํ˜€ ๊ฒฝ์ œ์  ์†์‹ค์„ ์ดˆ๋ž˜ํ•ฉ๋‹ˆ๋‹ค.
  • ์ •์‹ ์  ๊ฑด๊ฐ•: ์ฅ๊ฐ€ ์ถœ๋ชฐํ•˜๋Š” ํ™˜๊ฒฝ์— ์‚ฌ๋Š” ์‚ฌ๋žŒ๋“ค์€ ์ŠคํŠธ๋ ˆ์Šค, ๋ถˆ์•ˆ, ์šฐ์šธ์ฆ ๋“ฑ ์ •์‹ ์  ๊ณ ํ†ต์„ ๊ฒช๋Š”๋‹ค๋Š” ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๊ฐ€ ๋งŽ์Šต๋‹ˆ๋‹ค. ์ฅ์— ๋Œ€ํ•œ ํ˜์˜ค๊ฐ์€ ๋ถˆ์พŒ๊ฐ๊ณผ ๋ถˆ์•ˆ๊ฐ์„ ์œ ๋ฐœํ•˜๋ฉฐ ์‚ถ์˜ ์งˆ์„ ๋–จ์–ด๋œจ๋ฆฝ๋‹ˆ๋‹ค.
  • ๊ณต์ค‘ ๋ณด๊ฑด ์œ„ํ—˜: ์ฅ๋Š” ์†Œ๋ณ€์„ ํ†ตํ•ด โ€˜๋ ™ํ† ์Šคํ”ผ๋ผ์ฆ(Leptospirosis)โ€˜๊ณผ ๊ฐ™์€ ์งˆ๋ณ‘์„ ์ „ํŒŒํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. 2023๋…„ ๋‰ด์š•์‹œ์—์„œ 24๋ช…์˜ ๋ ™ํ† ์Šคํ”ผ๋ผ์ฆ ํ™˜์ž๊ฐ€ ๋ฐœ์ƒํ–ˆ์ง€๋งŒ, 800๋งŒ ๋ช…์ด ๋„˜๋Š” ๋„์‹œ ์ธ๊ตฌ๋ฅผ ๊ณ ๋ คํ•  ๋•Œ ์น˜๋ช…์ ์ธ ์ˆ˜์ค€์€ ์•„๋‹™๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ฝœ๋กฌ๋น„์•„ ๋Œ€ํ•™์˜ ์—ฐ๊ตฌ์— ๋”ฐ๋ฅด๋ฉด ๋‰ด์š•์‹œ ์ฅ๋“ค์—๊ฒŒ์„œ๋Š” ๋‹ค์–‘ํ•œ ์‹ ์ข… ๋ฐ”์ด๋Ÿฌ์Šค์™€ ๋ณ‘์›๊ท ์ด ๋ฐœ๊ฒฌ๋˜์—ˆ์œผ๋ฉฐ, ๋ฐ”์ด๋Ÿฌ์Šค๊ฐ€ ๋Œ์—ฐ๋ณ€์ด๋ฅผ ์ผ์œผ์ผœ ์ˆ™์ฃผ๋ฅผ ๋ฐ”๊ฟ€ ์ž ์žฌ์  ์œ„ํ˜‘์€ ํ•ญ์ƒ ์กด์žฌํ•ฉ๋‹ˆ๋‹ค. ์ฅ๊ฐ€ ์ธ๊ฐ„๊ณผ ๋งค์šฐ ๊ฐ€๊นŒ์ด ์‚ด๊ธฐ ๋•Œ๋ฌธ์— ์ด๋Ÿฌํ•œ ์œ„ํ˜‘์€ ๋”์šฑ ์ปค์งˆ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

โ€˜ํ•ด์ถฉโ€™์ด๋ผ๋Š” ๊ฐœ๋…์— ๋Œ€ํ•œ ๋น„ํŒ์  ๊ณ ์ฐฐ: ์ฅ๋Š” ์ •๋ง ์•…๋‹น์ธ๊ฐ€?

๋ฒ ์„œ๋‹ˆ ๋ธŒ๋ฃฉ์…”๋Š” โ€œํ•ด์ถฉ(pest)โ€œ์ด๋ผ๋Š” ๋‹จ์–ด๊ฐ€ ์šฐ๋ฆฌ์˜ ์‚ฌํšŒ์—์„œ ๋งŽ์€ ์—ญํ• ์„ ํ•œ๋‹ค๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. โ€œํ•ด์ถฉ์€ ์šฐ๋ฆฌ๊ฐ€ ์›ํ•˜์ง€ ์•Š๋Š” ๊ณณ์— ์žˆ๋Š” ๋™๋ฌผ์„ ์ง€์นญํ•˜๋Š” ๋‹จ์–ดโ€์ด๋ฉฐ, ์šฐ๋ฆฌ๊ฐ€ ํŠน์ • ๋™๋ฌผ์„ ์‹ซ์–ดํ•˜๋Š” ๊ฒƒ์€ ๊ทธ ๋™๋ฌผ์ด ์–ด๋–ค ํ–‰๋™์„ ํ•˜๋Š”์ง€๋ณด๋‹ค โ€œ์šฐ๋ฆฌ๊ฐ€ ๋™๋ฌผ์ด ์–ด๋””์— ์†ํ•˜๊ณ  ๋ฌด์—‡์„ ํ•ด์•ผ ํ•œ๋‹ค๊ณ  ์ƒ๊ฐํ•˜๋Š”์ง€โ€์— ๋‹ฌ๋ ค์žˆ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๊ทธ๋…€๋Š” ๋น„๋‘˜๊ธฐ๋ฅผ ์˜ˆ๋กœ ๋“ค์–ด ์ด๋Ÿฌํ•œ ์ฃผ๊ด€์„ฑ์„ ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค. 8,000๋…„ ์ „๋ถ€ํ„ฐ ๊ธธ๋“ค์—ฌ์ง„ ๋น„๋‘˜๊ธฐ๋Š” ํ•œ๋•Œ ์‹๋Ÿ‰, ๋ฉ”์‹ ์ €(๋กœ์ดํ„ฐ ํ†ต์‹ ์€ ๋น„๋‘˜๊ธฐ๋ฅผ ์ด์šฉํ•ด ์ฃผ์‹ ์ •๋ณด๋ฅผ ์ „๋‹ฌํ•˜๊ธฐ๋„ ํ–ˆ์Šต๋‹ˆ๋‹ค), ์‹ฌ์ง€์–ด ๋น„๋ฃŒ์˜ ์›์ฒœ์œผ๋กœ์„œ ๋งค์šฐ ์ค‘์š”ํ–ˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ํ™”ํ•™ ๋น„๋ฃŒ, ์ด๋ฉ”์ผ, ๋‹ญ๊ณ ๊ธฐ๊ฐ€ ๋ณดํŽธํ™”๋˜๋ฉด์„œ ๋น„๋‘˜๊ธฐ๋Š” ๋” ์ด์ƒ ์ธ๊ฐ„์—๊ฒŒ ์œ ์šฉํ•˜์ง€ ์•Š๊ฒŒ ๋˜์—ˆ๊ณ , โ€˜๋‚ ๊ฐœ ๋‹ฌ๋ฆฐ ์ฅ(rats with wings)โ€˜๋กœ ๋ถˆ๋ฆฌ๋ฉฐ โ€˜ํ•ด์ถฉโ€™์œผ๋กœ ์ „๋ฝํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ์ธ๊ฐ„์˜ ํ•„์š”์™€ ์ธ์‹์ด ์–ด๋–ป๊ฒŒ ๋™๋ฌผ์˜ ํ‰ํŒ์„ ์™„์ „ํžˆ ๋ฐ”๊ฟ€ ์ˆ˜ ์žˆ๋Š”์ง€๋ฅผ ๋ณด์—ฌ์ฃผ๋Š” ๊ทน๋ช…ํ•œ ์‚ฌ๋ก€์ž…๋‹ˆ๋‹ค.

๋ธŒ๋ฃฉ์…”๋Š” ๋˜ํ•œ ์ฅ์— ๋Œ€ํ•œ ํ˜์˜ค๊ฐ€ ๋ฌธํ™”์— ๋”ฐ๋ผ ์–ผ๋งˆ๋‚˜ ๋‹ค๋ฅธ์ง€๋„ ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ์ธ๋„ ๋ฐ์‰ฌ๋…ธํฌ(Deshnoke)์— ์žˆ๋Š” โ€˜๊นŒ๋ฅด๋‹ˆ ๋งˆํƒ€ ์‚ฌ์›(Karni Mata Temple)โ€˜์—๋Š” ์•ฝ 2๋งŒ 5์ฒœ ๋งˆ๋ฆฌ์˜ ๊ฒ€์€ ์ฅ๊ฐ€ ์‚ด๊ณ  ์žˆ์œผ๋ฉฐ, ์ด ์ฅ๋“ค์€ โ€˜์‹ ์„ฑํ•œ(sacred)โ€™ ์กด์žฌ๋กœ ์—ฌ๊ฒจ์ง‘๋‹ˆ๋‹ค. ์ „์„ค์— ๋”ฐ๋ฅด๋ฉด, ์ด ์ฅ๋“ค์€ ๊นŒ๋ฅด๋‹ˆ ๋งˆํƒ€ ์—ฌ์‹ ์˜ ๊ฐ€์กฑ๋“ค์ด ํ™˜์ƒํ•œ ๊ฒƒ์ด๋ฉฐ, ์ฃฝ์œผ๋ฉด ๋‹ค์‹œ ์ธ๊ฐ„์œผ๋กœ ํƒœ์–ด๋‚œ๋‹ค๊ณ  ๋ฏฟ์Šต๋‹ˆ๋‹ค. ์ด ์‚ฌ์›์˜ ์ฅ๋“ค์€ ์€์œผ๋กœ ์žฅ์‹๋œ ๋ฌธ๊ณผ ๋Œ€๋ฆฌ์„ ๋ฐ”๋‹ฅ ์œ„์—์„œ ์šฐ์œ ๋ฅผ ๋งˆ์‹œ๊ณ , ํ†ต๋ฐ€ ๋นต, ๊ณผ์ผ, ์ฑ„์†Œ ๋“ฑ ๊ฑด๊ฐ•ํ•œ ์‹๋‹จ์„ ์ œ๊ณต๋ฐ›์œผ๋ฉฐ ์ˆญ๋ฐฐ๋ฐ›์Šต๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ๋ฌธํ™”์  ์ฐจ์ด๋Š” ์šฐ๋ฆฌ๊ฐ€ ๋™๋ฌผ์„ ๋Œ€ํ•˜๋Š” ๋ฐฉ์‹์— ๋Œ€ํ•œ ๊ทผ๋ณธ์ ์ธ ์งˆ๋ฌธ์„ ๋˜์ง‘๋‹ˆ๋‹ค. ๋ธŒ๋ฃฉ์…”๋Š” ์šฐ๋ฆฌ๊ฐ€ ์ฅ๋ฅผ ์‹ซ์–ดํ•˜๋Š” ์ด์œ  ์ค‘ ํ•˜๋‚˜๊ฐ€ โ€œ์šฐ๋ฆฌ๊ฐ€ ๋™๋ฌผ๋“ค์ด ์‹คํŒจํ•  ๊ฒƒ์ด๋ผ๊ณ  ์˜ˆ์ƒํ•˜๊ธฐ ๋•Œ๋ฌธโ€์ด๋ผ๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ์šฐ๋ฆฌ๊ฐ€ ์–ด๋–ค ์ง€์—ญ์„ ๊ฐœ๋ฐœํ•˜๊ณ  ๊ฑด๋ฌผ์„ ์„ธ์šฐ๋ฉด ๋™๋ฌผ๋“ค์€ ๋– ๋‚  ๊ฒƒ์ด๋ผ๊ณ  ์ƒ๊ฐํ•˜์ง€๋งŒ, ๋งŒ์•ฝ ๊ทธ๋“ค์ด ์—ฌ์ „ํžˆ ๋‚จ์•„ ๋ฒˆ์„ฑํ•œ๋‹ค๋ฉด ์šฐ๋ฆฌ๋Š” ํ™”๋ฅผ ๋‚ธ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ํŠนํžˆ ๊ทธ๋“ค์ด ์šฐ๋ฆฌ๊ฐ€ ๊ฐ€์น˜ ์žˆ๊ฒŒ ์—ฌ๊ธฐ๋Š” ๊ฒƒ(์šฐ๋ฆฌ์˜ ์ •์›, ๋†์ž‘๋ฌผ, ์‹ฌ์ง€์–ด ๊ณ ์–‘์ด)์„ ํ†ตํ•ด ๋ฒˆ์„ฑํ•  ๋•Œ ๋”์šฑ ๊ทธ๋ ‡์Šต๋‹ˆ๋‹ค. โ€œ์šฐ๋ฆฌ๋Š” ๊ทธ๋“ค์˜ ์„ฑ๊ณต์„ ์‹ซ์–ดํ•ฉ๋‹ˆ๋‹ค. ์™œ๋ƒํ•˜๋ฉด ๊ทธ๋“ค์˜ ์„ฑ๊ณต์ด ์šฐ๋ฆฌ์˜ ์‹คํŒจ์ฒ˜๋Ÿผ ๋А๊ปด์ง€๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.โ€

์ฅ์™€์˜ ๊ณต์กด์„ ๋ชจ์ƒ‰ํ•˜๋ฉฐ: ๋„์‹œ์˜ ๋™๋ฐ˜์ž๋ฅผ ์œ„ํ•œ ์ƒˆ๋กœ์šด ์‹œ๊ฐ

์ฅ์— ๋Œ€ํ•œ ํƒ€๊ณ ๋‚œ ํ˜์˜ค๊ฐ์€ ๋„์‹œ ํ™˜๊ฒฝ ์†์—์„œ ์“ฐ๋ ˆ๊ธฐ์™€ ๋ถˆ๊ฒฐํ•จ์— ๋Œ€ํ•œ ์šฐ๋ฆฌ์˜ ์ธ์‹๊ณผ ๊นŠ์ด ์—ฐ๊ด€๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์—๋“œ ๊ธ€๋ ˆ์ด์ €๋Š” ์ฅ๊ฐ€ ์ด์ œ ๋” ์ด์ƒ ์ฃผ์š” ์งˆ๋ณ‘ ๋งค๊ฐœ์ฒด๊ฐ€ ์•„๋‹Œ ํ•œ, ๊ทธ๋“ค์— ๋Œ€ํ•œ ์šฐ๋ฆฌ์˜ ๋‘๋ ค์›€์€ ์‹œ๋Œ€์— ๋’ค๋–จ์–ด์ง„ ๊ฒƒ์ผ ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ง€์ ํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ฅ๊ฐ€ ๋„์‹œ์—์„œ ์ธ๊ฐ„์˜ โ€˜๋ถ€์ •์ ์ธ ์™ธ๋ถ€ ํšจ๊ณผโ€™๋ฅผ ์œ ๋ฐœํ•˜๋Š” ์กด์žฌ์ด๊ธด ํ•˜์ง€๋งŒ, โ€œ๋งค์šฐ ์‚ฌ์†Œํ•œ ๋ฌธ์ œโ€์ผ ์ˆ˜ ์žˆ๋‹ค๊ณ  ๋ง๋ถ™์ž…๋‹ˆ๋‹ค.

๊ทธ๋ ‡๋‹ค๊ณ  ์ฅ๋ฅผ ๋ฐฉ์น˜ํ•˜์ž๋Š” ์˜๋ฏธ๋Š” ์•„๋‹™๋‹ˆ๋‹ค. ๊ธ€๋ ˆ์ด์ €๋Š” โ€œ์ฅ ๊ฐœ์ฒด์ˆ˜๋ฅผ ๊ด€๋ฆฌ ๊ฐ€๋Šฅํ•œ ์ˆ˜์ค€์œผ๋กœ ์œ ์ง€ํ•˜๋Š” ์ •์ฑ…์—๋Š” ์ฐฌ์„ฑํ•˜์ง€๋งŒ, ์™„์ „ํ•œ ๋ฐ•๋ฉธ์— ์ง‘์ฐฉํ•  ํ•„์š”๋Š” ์—†๋‹คโ€๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ฅ๋ฅผ โ€œ๋„์‹œ์˜ ์ž์—ฐ์ ์ธ ํŒŒํŠธ๋„ˆโ€๋กœ ๋ณด๊ณ , ๊ณผ๋„ํ•œ ๊ณตํฌ ๋Œ€์‹  โ€œ์—ฐ๋ฏผ(sympathy)โ€œ์„ ๊ฐ€์ ธ์•ผ ํ•œ๋‹ค๊ณ  ์ œ์•ˆํ•ฉ๋‹ˆ๋‹ค.

๋‰ด์š•์‹œ์˜ โ€˜์ฅ ์ „์Ÿโ€™์€ ์—ฌ์ „ํžˆ ์ง„ํ–‰ ์ค‘์ž…๋‹ˆ๋‹ค. ์ฅ ์ฐจ๋ฅด ์ผ€์ดํ‹ฐ ์ฝ”๋ผ๋””์˜ ํ›„์ž„์ธ ์กฐ๋ž€ ๋ชธ๋‹ค๋‹ˆ(Zoran Momdani) ์‹œ์žฅ์€ 2031๋…„ ๋ง๊นŒ์ง€ ๋„์‹œ ์ „์ฒด์— ์“ฐ๋ ˆ๊ธฐ ์ปจํ…Œ์ด๋„ˆํ™”๋ฅผ ๋‹ฌ์„ฑํ•˜๊ฒ ๋‹ค๋Š” ๊ณ„ํš์„ ๋ฐœํ‘œํ•˜๋ฉฐ ์ฅ ๋ฌธ์ œ ํ•ด๊ฒฐ์— ๋Œ€ํ•œ ์˜์ง€๋ฅผ ๋ณด์ด๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

์ฅ๋Š” ์ธ๊ฐ„์ด ๋งŒ๋“  ๋„์‹œ๋ผ๋Š” ์ƒํƒœ๊ณ„์—์„œ ๋ฒˆ์„ฑํ•˜๋Š” ๊ฐ€์žฅ ์„ฑ๊ณต์ ์ธ ์ƒ๋ช…์ฒด ์ค‘ ํ•˜๋‚˜์ž…๋‹ˆ๋‹ค. ๊ทธ๋“ค์„ ๋ฌด์กฐ๊ฑด์ ์ธ ํ˜์˜ค์˜ ๋Œ€์ƒ์œผ๋กœ๋งŒ ๋ณผ ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ๋„์‹œ ํ™˜๊ฒฝ์—์„œ ์ธ๊ฐ„๊ณผ ํ•จ๊ป˜ ์‚ด์•„๊ฐ€๋Š” โ€˜๋™๋ฐ˜์žโ€™๋กœ์„œ ์ดํ•ดํ•˜๊ณ  ๊ด€๋ฆฌํ•˜๋Š” ์ƒˆ๋กœ์šด ์‹œ๊ฐ์ด ํ•„์š”ํ•  ๋•Œ์ž…๋‹ˆ๋‹ค. ์ฅ์— ๋Œ€ํ•œ ์šฐ๋ฆฌ์˜ ์ธ์‹ ๋ณ€ํ™”๋Š” ๊ฒฐ๊ตญ ์ธ๊ฐ„์ด ๋‹ค๋ฅธ ์ƒ๋ช…์ฒด์™€ ์–ด๋–ป๊ฒŒ ๊ณต์กดํ•ด์•ผ ํ•˜๋Š”๊ฐ€์— ๋Œ€ํ•œ ๋” ๋„“์€ ์งˆ๋ฌธ์œผ๋กœ ์ด์–ด์งˆ ๊ฒƒ์ž…๋‹ˆ๋‹ค.


โ€œClaude Design is slow and I love it anyway (plus why I love ChatGPT Images 2.0)โ€ โ€” How I AI ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

AI ๋””์ž์ธ ๋„๊ตฌ์˜ ์ƒˆ๋กœ์šด ์ง€ํ‰: Claude Design๊ณผ GPT Image 2 ์‹ฌ์ธต ๋ถ„์„

์ธ๊ณต์ง€๋Šฅ(AI)์ด ๋””์ž์ธ ๋ถ„์•ผ์— ํ˜๋ช…์ ์ธ ๋ณ€ํ™”๋ฅผ ๊ฐ€์ ธ์˜ค๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ฝ”๋“œ ์ž‘์„ฑ๋ถ€ํ„ฐ ๊ณ ๊ฐ ๋ฐ์ดํ„ฐ ๋ถ„์„, ์‹ฌ์ง€์–ด ๊ณ ๊ฐ ์ง€์›์— ์ด๋ฅด๊ธฐ๊นŒ์ง€ AI ๋„๊ตฌ๋“ค์€ ์ด๋ฏธ ์šฐ๋ฆฌ ์—…๋ฌด ๋ฐฉ์‹์„ ๋ณ€ํ™”์‹œํ‚ค๊ณ  ์žˆ์ฃ . ์ด๋ฒˆ ์—ํ”ผ์†Œ๋“œ์—์„œ๋Š” Anthropic์˜ Claude Design๊ณผ OpenAI์˜ GPT Image 2 ๋ชจ๋ธ์ด ๋””์ž์ธ ์ž‘์—… ํ๋ฆ„์„ ์–ด๋–ป๊ฒŒ ๋ฐ”๊พธ๊ณ  ์žˆ๋Š”์ง€, ๊ทธ๋ฆฌ๊ณ  ์ด ์ƒˆ๋กœ์šด ๋„๊ตฌ๋“ค์ด ๊ฐ€์ง„ ์žฅ๋‹จ์ ๊ณผ ์‹ค์ œ ํ™œ์šฉ ์‚ฌ๋ก€๋“ค์„ ์‹ฌ์ธต์ ์œผ๋กœ ์‚ดํŽด๋ณด๊ฒ ์Šต๋‹ˆ๋‹ค. ํ˜ธ์ŠคํŠธ ํด๋ ˆ์–ด ๋ฐœ๋ ˆ(Claire Valle)๋Š” AI ๊ธฐ์ˆ ์„ ํ™œ์šฉํ•ด ๋” ๋‚˜์€ ๊ฒฐ๊ณผ๋ฌผ์„ ๋งŒ๋“ค๊ณ ์ž ํ•˜๋Š” ์‚ฌ๋žŒ๋“ค์„ ๋•๊ธฐ ์œ„ํ•ด, ์ด ํ˜์‹ ์ ์ธ ๋„๊ตฌ๋“ค์— ๋Œ€ํ•œ ์†”์งํ•œ ๊ฒฌํ•ด๋ฅผ ๊ณต์œ ํ•ฉ๋‹ˆ๋‹ค.


1. ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ์ตœ์šฐ์„ ์œผ๋กœ: Anthropic์˜ Claude Design

Anthropic์ด ์ตœ๊ทผ ์ถœ์‹œํ•œ Claude Design์€ ์›น ๊ธฐ๋ฐ˜ ๋””์ž์ธ ๋„๊ตฌ๋กœ, ํ”„๋กœํ† ํƒ€์ž…(prototype) ์ œ์ž‘(์™€์ด์–ดํ”„๋ ˆ์ž„(wireframe) ๋ฐ ๊ณ ํ’ˆ์งˆ ํ”„๋กœํ† ํƒ€์ž… ํฌํ•จ), ์Šฌ๋ผ์ด๋“œ, ๋น„๋””์˜ค ์ œ์ž‘์— ์ค‘์ ์„ ๋‘ก๋‹ˆ๋‹ค. ๋งŽ์€ ์‚ฌ๋žŒ๋“ค์ด Claude Design์ด Figma๋ฅผ ๋Œ€์ฒดํ•  ์ˆ˜ ์žˆ์„์ง€์— ๋Œ€ํ•ด ๊ถ๊ธˆํ•ดํ•˜์ง€๋งŒ, ํด๋ ˆ์–ด๋Š” ์ด ๋„๊ตฌ๊ฐ€ ์—”์ง€๋‹ˆ์–ด๋ง ๋‹จ๊ณ„๋กœ ๋„˜์–ด๊ฐ€๊ธฐ ์ „ ์‚ฌ์šฉํ•˜๋Š” ์ผ๋ถ€ ํ”„๋กœํ† ํƒ€์ดํ•‘ ๋„๊ตฌ๋“ค์„ ๋Œ€์ฒดํ•  ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ „๋งํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ ํฅ๋ฏธ๋กœ์šด ์ ์€ ์• ๋‹ˆ๋ฉ”์ด์…˜ ๋ฐ ๋น„๋””์˜ค ํ…œํ”Œ๋ฆฟ๋„ ์ œ๊ณตํ•œ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.

1.1. ํ•ต์‹ฌ ๊ฐ•์ : ๋””์ž์ธ ์‹œ์Šคํ…œ ํ†ตํ•ฉ

Claude Design์ด ๊ฐ€์žฅ ์ฃผ๋ชฉ๋ฐ›๋Š” ์ด์œ ๋Š” ๋ฐ”๋กœ โ€˜๋””์ž์ธ ์‹œ์Šคํ…œ(design system)์„ ํ•ต์‹ฌ ์š”์†Œ๋กœ ๊ฒฉ์ƒ์‹œ์ผœ ์ตœ์šฐ์„ ์œผ๋กœ ๋‹ค๋ฃฌ๋‹คโ€™๋Š” ์ ์ž…๋‹ˆ๋‹ค. ํด๋ ˆ์–ด๋Š” ์ด ๋„๊ตฌ๋ฅผ ์ฒ˜์Œ ์‚ฌ์šฉํ–ˆ์„ ๋•Œ ๊ฐ€์žฅ ๋จผ์ € ์ž์‹ ์˜ ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ๊ฐ€์ ธ์™€ ๋ณด์•˜๋‹ค๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๋งค์šฐ ์˜๋ฆฌํ•œ ์ ‘๊ทผ ๋ฐฉ์‹์ธ๋ฐ, ์ œํ’ˆ ๊ฐœ๋ฐœ ๊ณผ์ •์—์„œ ํ”„๋กœํ† ํƒ€์ž…์„ ์‚ฌ์šฉํ•  ๋•Œ ์‚ฌ๋žŒ๋“ค์ด ๊ฐ€์žฅ ๋งŽ์ด ๋ถˆํ‰ํ•˜๋Š” ๊ฒƒ์ด ๋ฐ”๋กœ โ€œ์šฐ๋ฆฌ ๋ธŒ๋žœ๋“œ์™€ ๋งž์ง€ ์•Š๋Š”๋‹คโ€, โ€œ์šฐ๋ฆฌ ๋””์ž์ธ ์‹œ์Šคํ…œ๊ณผ ์ผ์น˜ํ•˜์ง€ ์•Š๋Š”๋‹คโ€๋Š” ์ ์ด๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ๊ธฐ์กด์˜ ์—ฌ๋Ÿฌ ํ”„๋กœํ† ํƒ€์ดํ•‘ ๋„๊ตฌ๋“ค๋„ ๋””์ž์ธ ์‹œ์Šคํ…œ ๊ฐ€์ ธ์˜ค๊ธฐ ๊ธฐ๋Šฅ์„ ์ œ๊ณตํ•˜์ง€๋งŒ, ์ฝ”๋“œ ๋ฒ ์ด์Šค์— ์žˆ๋Š” ๊ธฐ์กด ๋””์ž์ธ์„ ์™„๋ฒฝํ•˜๊ฒŒ ์žฌํ˜„ํ•˜๋Š” ๋ฐ๋Š” ํ•œ๊ณ„๊ฐ€ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค.

ํด๋ ˆ์–ด๋Š” Claude Design์ด ์ด ๋ฌธ์ œ๋ฅผ ์–ผ๋งˆ๋‚˜ ์ž˜ ํ•ด๊ฒฐํ•˜๋Š”์ง€ ํ…Œ์ŠคํŠธํ•˜๊ธฐ ์œ„ํ•ด ๋ ˆ๋‹ˆ ๋‰ด์Šค๋ ˆํ„ฐ(Lennyโ€™s Newsletter)์˜ ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ๊ฐ€์ ธ์˜ค๋Š” ๊ณผ์ •์„ ์‹œ์—ฐํ–ˆ์Šต๋‹ˆ๋‹ค. ๋‹จ์ˆœํžˆ ๋ ˆ๋‹ˆ์˜ ํ™ˆํŽ˜์ด์ง€ HTML์„ ์ €์žฅํ•˜๊ณ , ๋กœ๊ณ ์™€ ์ด๋ฏธ์ง€๋“ค์„ ์—…๋กœ๋“œํ•œ ํ›„ ํฐํŠธ๋ฅผ ์ถ”๊ฐ€ํ•˜๋Š” ๊ฒƒ๋งŒ์œผ๋กœ Claude Design์€ ํ•ด๋‹น ์ž๋ฃŒ๋“ค์„ ํƒ์ƒ‰ํ•˜๊ณ  ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ๊ตฌ์ถ•ํ•˜๊ธฐ ์‹œ์ž‘ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ๊ณผ์ •์€ ์•ฝ 5๋ถ„ ์ •๋„ ์†Œ์š”๋˜๋ฉฐ, Claude Design์€ HTML๊ณผ ํ•ต์‹ฌ ์ด๋ฏธ์ง€๋ฅผ ๋ถ„์„ํ•˜์—ฌ ์‹œ๊ฐ์  ์ •๋ณด๋ฅผ ํŒŒ์•…ํ•˜๊ณ , ์ฃผ์š” ์ƒ‰์ƒ ๋ฐ ๊ตฌ์กฐ๋ฅผ ์ถ”์ถœํ•˜์—ฌ ์ž์ฒด์ ์ธ ๋””์ž์ธ ์‹œ์Šคํ…œ์œผ๋กœ ๊ตฌ์„ฑํ•ฉ๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ์ ‘๊ทผ ๋ฐฉ์‹์€ ๋””์ž์ธ ์‹œ์Šคํ…œ์„ UI ํ‚คํŠธ, ํƒ€์ดํฌ๊ทธ๋ž˜ํ”ผ(typography), ์ƒ‰์ƒ, ์ปดํฌ๋„ŒํŠธ(component), ๋ธŒ๋žœ๋“œ ๋งˆํฌ ๋“ฑ์œผ๋กœ ์„ธ๋ถ„ํ™”ํ•˜์—ฌ AI ๋„๊ตฌ๊ฐ€ ์ผ๊ด€์„ฑ ์žˆ๊ณ  ๊ณ ํ’ˆ์งˆ์˜ UI๋ฅผ ๋ Œ๋”๋งํ•˜๋Š” ๋ฐ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•ฉ๋‹ˆ๋‹ค. ์‹ค์ œ๋กœ ๊ตฌ๊ธ€ ๋žฉ์Šค(Google Labs)๋Š” ์ตœ๊ทผ design.md๋ผ๋Š” ํ‘œ์ค€์„ ๋ฐœํ‘œํ–ˆ๋Š”๋ฐ, ์ด๋Š” AI ์—์ด์ „ํŠธ(agent)๊ฐ€ ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ์ดํ•ดํ•˜๊ณ  ํ™œ์šฉํ•˜๋Š” ํ‘œ์ค€ ๋ฐฉ์‹์„ ์ œ์‹œํ•˜๋ ค๋Š” ๋…ธ๋ ฅ์˜ ์ผํ™˜์ž…๋‹ˆ๋‹ค. ์ด๋Š” AI๊ฐ€ ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ๊ตฌ์กฐํ™”๋œ ํ˜•ํƒœ๋กœ ์ธ์‹ํ•˜๊ณ  ์‚ฌ์šฉํ•˜๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ์—…๊ณ„๊ฐ€ ๋‚˜์•„๊ฐ€๊ณ  ์žˆ์Œ์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค.

1.2. ์‹ค์šฉ์ ์ธ ํ™œ์šฉ ์‚ฌ๋ก€

Claude Design์€ ํŠนํžˆ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ์ƒํ™ฉ์—์„œ ๋งค์šฐ ์œ ์šฉํ•˜๊ฒŒ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

  • ๋งˆ์ผ€ํŒ… ๋žœ๋”ฉ ํŽ˜์ด์ง€ ๋ฐ ์›น์‚ฌ์ดํŠธ: Claude Design์€ ๋งˆ์ผ€ํŒ… ์ „์šฉ ๋žœ๋”ฉ ํŽ˜์ด์ง€๋‚˜ ์›น์‚ฌ์ดํŠธ์— ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ์ ์šฉํ•˜๋Š” ๋ฐ ํƒ์›”ํ•œ ๋Šฅ๋ ฅ์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ๋ธŒ๋žœ๋“œ ์ž์‚ฐ์„ ์•„๋ฆ„๋‹ค์šด ์›Œํฌํ”Œ๋กœ์šฐ์— ํ†ตํ•ฉํ•˜๊ธฐ ์–ด๋ ค์›Œ ํ”„๋กœํ† ํƒ€์ดํ•‘์„ ๊บผ๋ ธ๋˜ ๋งˆ์ผ€ํ„ฐ๋“ค์—๊ฒŒ ํŠนํžˆ ์œ ์šฉํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค.

    • ์˜ˆ์‹œ: LennyDoc PRD ๋นŒ๋” ํด๋ ˆ์–ด๋Š” ๋ ˆ๋‹ˆ์˜ ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ํ™œ์šฉํ•˜์—ฌ โ€˜LennyDocโ€™์ด๋ผ๋Š” PRD(Product Requirements Document) ์ƒ์„ฑ๊ธฐ ๋žœ๋”ฉ ํŽ˜์ด์ง€๋ฅผ ๋งŒ๋“ค์—ˆ์Šต๋‹ˆ๋‹ค. โ€œ๋ ˆ๋‹ˆ ๋‰ด์Šค๋ ˆํ„ฐ์˜ ๋ชจ๋“  ๋ฐ์ดํ„ฐ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ PRD ์ƒ์„ฑ๊ธฐ ๋ฐ AI PM ์ฝ”์น˜๋ฅผ ์œ„ํ•œ ๋žœ๋”ฉ ํŽ˜์ด์ง€๋ฅผ ๋งŒ๋“ค์–ด ๋‹ฌ๋ผ. ๋ ˆ๋‹ˆ ๋‰ด์Šค๋ ˆํ„ฐ ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ๋”ฐ๋ฅด๊ณ , ๋ฉ‹์ง€๊ฒŒ ๋งŒ๋“ค์–ด ๋‹ฌ๋ผโ€๋Š” ๊ฐ„๋‹จํ•œ ํ”„๋กฌํ”„ํŠธ(prompt)๋งŒ์œผ๋กœ Claude Design์€ ๋‹ค์–‘ํ•œ ์งˆ๋ฌธ๊ณผ ๋‹ต๋ณ€์„ ํ†ตํ•ด ๋””์ž์ธ์„ ๊ตฌ์ฒดํ™”ํ–ˆ์Šต๋‹ˆ๋‹ค. ํ—ค๋“œ๋ผ์ธ ์Šคํƒ€์ผ, ๋ ˆ์ด์•„์›ƒ, ๋ฐฐ๊ฒฝ์ƒ‰, CTA(Call To Action) ๋ฌธ๊ตฌ ๋“ฑ ์—ฌ๋Ÿฌ ์˜ต์…˜์„ ์ œ๊ณตํ•˜์—ฌ ์‚ฌ์šฉ์ž๊ฐ€ ์‰ฝ๊ฒŒ ์„ ํƒํ•˜๊ณ  ๋ณ€๊ฒฝํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ๋””์ž์ธ ๋„๊ตฌ ๊ด€์ ์—์„œ ๋งค์šฐ ์˜๋ฆฌํ•œ ๊ธฐ๋Šฅ์ธ๋ฐ, ๋Œ€๋ถ€๋ถ„์˜ ์‚ฌ์šฉ์ž๋Š” ์ •ํ™•ํžˆ ์–ด๋–ค ๋ณ€๊ฒฝ์„ ์›ํ•˜๋Š”์ง€ ๋ช…ํ™•ํžˆ ์„ค๋ช…ํ•˜๊ธฐ ์–ด๋ ต๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
    • ํ”ผ๋“œ๋ฐฑ ๋ฐ ์ˆ˜์ • ๊ธฐ๋Šฅ: Claude Design์€ ํŠน์ • ์ปดํฌ๋„ŒํŠธ์— ๋Œ“๊ธ€์„ ๋‹ฌ์•„ AI๊ฐ€ ์ง์ ‘ ์ˆ˜์ •ํ•˜๋„๋ก ์š”์ฒญํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, โ€œCTA ํ…์ŠคํŠธ๋ฅผ ๊ฐœ์„ ํ•ด ๋‹ฌ๋ผโ€๊ณ  ์š”์ฒญํ•˜๋ฉด AI๊ฐ€ ์ด๋ฅผ ๋ฐ˜์˜ํ•˜์—ฌ ๋ณ€๊ฒฝํ•ด ์ค๋‹ˆ๋‹ค. ์ด๋Š” ํ”„๋กœํ† ํƒ€์ž…, ์ธ๋น„์ „(InVision)์˜ ๋Œ“๊ธ€ ๊ธฐ๋Šฅ, ํ”ผ๊ทธ์žผ(FigJam)์˜ ์•„์ด๋””์–ด ๊ณต์œ , ํ”ผ๊ทธ๋งˆ(Figma)์˜ ๋Œ“๊ธ€ ๊ธฐ๋Šฅ ๋“ฑ ๋‹ค์–‘ํ•œ ํ˜‘์—… ๋„๊ตฌ์˜ ์žฅ์ ์„ AI ๊ธฐ๋ฐ˜์œผ๋กœ ํ†ตํ•ฉํ•œ ํ˜•ํƒœ์ž…๋‹ˆ๋‹ค.
  • ๊ณ ํ’ˆ์งˆ ํ”„๋ ˆ์  ํ…Œ์ด์…˜ ์Šฌ๋ผ์ด๋“œ: Claude Design์€ ๊ธฐ์กด ์ฝ˜ํ…์ธ ์™€ ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ๊ฒฐํ•ฉํ•˜์—ฌ ์•„๋ฆ„๋‹ค์šด ํ”„๋ ˆ์  ํ…Œ์ด์…˜ ์Šฌ๋ผ์ด๋“œ๋ฅผ ๋งŒ๋“œ๋Š” ๋ฐ๋„ ๊ฐ•์ ์„ ๋ณด์ž…๋‹ˆ๋‹ค. ํด๋ ˆ์–ด๋Š” ์ž์‹ ์ด ์ž‘์„ฑํ•œ Open Claw ๊ธฐ์‚ฌ PDF๋ฅผ ์—…๋กœ๋“œํ•˜๊ณ , ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ Open Claw ์„ค์ • ๋ฐฉ๋ฒ•์„ ๊ฐ€๋ฅด์น˜๋Š” ์Šฌ๋ผ์ด๋“œ ๋ฑ์„ ๋งŒ๋“ค์–ด ๋‹ฌ๋ผ๊ณ  ์š”์ฒญํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ฒฐ๊ณผ๋ฌผ์€ ๋””์ž์ธ ์‹œ์Šคํ…œ์— ์ถฉ์‹คํ•˜๋ฉด์„œ๋„ ๋‚ด์šฉ ์ „๋‹ฌ์— ํšจ๊ณผ์ ์ธ ๋งค์šฐ ๋ฉ‹์ง„ ํ”„๋ ˆ์  ํ…Œ์ด์…˜์ด์—ˆ์Šต๋‹ˆ๋‹ค. ํ„ฐ๋ฏธ๋„(terminal) ๋ช…๋ น์–ด๋ฅผ ์œ„ํ•œ ๊นœ๋นก์ด๋Š” ์ปค์„œ๊ฐ€ ์žˆ๋Š” ๊ฐ€์งœ ํ„ฐ๋ฏธ๋„ ํ™”๋ฉด๊ณผ ๊ฐ™์€ ๊ท€์—ฌ์šด ๋””์ž์ธ ์š”์†Œ๋“ค์€ ์Šฌ๋ผ์ด๋“œ๊ฐ€ ์‹ค์ œ๋กœ๋Š” ์ฝ”๋“œ ๊ธฐ๋ฐ˜์œผ๋กœ ๋งŒ๋“ค์–ด์ง„๋‹ค๋Š” ๊ฒƒ์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ์ด๋Š” ์ œํ’ˆ ๋งˆ์ผ€ํ„ฐ๋“ค์ด ๊ต์œก ์ž๋ฃŒ, ๊ณ ๊ฐ์šฉ ๋ฐํฌ ๋“ฑ์„ ๋งŒ๋“ค ๋•Œ ๋ธŒ๋žœ๋“œ ์ผ๊ด€์„ฑ์„ ์œ ์ง€ํ•˜๋ฉด์„œ๋„ ํšจ์œจ์ ์œผ๋กœ ์ž‘์—…ํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•ด ์ค„ ๊ฒƒ์ž…๋‹ˆ๋‹ค.

  • ์žฌ๋ฏธ์žˆ๋Š” ์›น์‚ฌ์ดํŠธ ์žฌํ•ด์„: Claude Design์— ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ์ œ๊ณตํ•˜์ง€ ์•Š์œผ๋ฉด, ๋งค์šฐ ๋…ํŠนํ•˜๊ณ  ์ฐฝ์˜์ ์ธ ๊ฒฐ๊ณผ๋ฌผ์„ ์–ป์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ํด๋ ˆ์–ด๋Š” โ€˜90๋…„๋Œ€ ์ง€์˜ค์‹œํ‹ฐ(GeoCities) ์Šคํƒ€์ผ์˜ ๋ ˆ๋‹ˆ ๋‰ด์Šค๋ ˆํ„ฐ ํ™ˆํŽ˜์ด์ง€โ€™๋ฅผ ๋งŒ๋“ค์–ด ๋‹ฌ๋ผ๊ณ  ์š”์ฒญํ–ˆ๋Š”๋ฐ, โ€˜๋ ˆ๋‹ˆ์˜ ์ œํ’ˆ ์กด(Lennyโ€™s Product Zone)โ€˜์ด๋ผ๋Š” ์ด๋ฆ„์œผ๋กœ ํƒ„์ƒํ•œ ๊ฒฐ๊ณผ๋ฌผ์€ ์ •๋ง ๋†€๋ผ์› ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ Claude Design์€ ๋›ฐ์–ด๋‚œ ์นดํ”ผ๋ผ์ดํŒ… ๋Šฅ๋ ฅ๋„ ๊ฐ€์ง€๊ณ  ์žˆ์–ด, โ€œ๋‹น์‹ ์˜ OKR์€ ๋”์ฐํ•˜๋‹ค(Your OKRs are cringe)โ€œ์™€ ๊ฐ™์€ ์žฌ์น˜ ์žˆ๋Š” ๋ฌธ๊ตฌ๋“ค์„ ์ƒ์„ฑํ•ด ๋ƒ…๋‹ˆ๋‹ค. ์ด๋Š” ๋ ˆํผ๋Ÿฐ์Šค ์Šคํƒ€์ผ์„ ์ž˜ ์ดํ•ดํ•˜๊ณ  ์žˆ๋‹ค๋ฉด, ๋””์ž์ธ ์‹œ์Šคํ…œ์˜ ์ œ์•ฝ ์—†์ด AI๊ฐ€ ์ž์œ ๋กญ๊ฒŒ ์ฐฝ์ž‘ํ•˜๋„๋ก ํ•˜์—ฌ ๋งค์šฐ ๋…ํŠนํ•˜๊ณ  ๋ฉ‹์ง„ ๋””์ž์ธ์„ ์–ป์„ ์ˆ˜ ์žˆ์Œ์„ ์‹œ์‚ฌํ•ฉ๋‹ˆ๋‹ค.

1.3. Claude Design์˜ ํ•œ๊ณ„

Claude Design์€ ๋งŽ์€ ์žฅ์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ์ง€๋งŒ, ์•„์ง ํ•ด๊ฒฐํ•ด์•ผ ํ•  ๊ณผ์ œ๋„ ์žˆ์Šต๋‹ˆ๋‹ค. ๊ฐ€์žฅ ํฐ ๋‹จ์ ์€ ๋ฐ”๋กœ ๋А๋ฆฐ ์†๋„์ž…๋‹ˆ๋‹ค. ๋žœ๋”ฉ ํŽ˜์ด์ง€ ํ•˜๋‚˜๋ฅผ ์ƒ์„ฑํ•˜๋Š” ๋ฐ 5๋ถ„์—์„œ 10๋ถ„ ์ •๋„๊ฐ€ ์†Œ์š”๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋””์ž์ธ ์ž‘์—…์—์„œ๋Š” ๋น ๋ฅธ ํ”ผ๋“œ๋ฐฑ ๋ฃจํ”„(feedback loop)๊ฐ€ ๋งค์šฐ ์ค‘์š”ํ•œ๋ฐ, Figma์™€ ๊ฐ™์€ ๋„๊ตฌ๋Š” ๋“œ๋ž˜๊ทธ ์•ค ๋“œ๋กญ(drag and drop)์œผ๋กœ ์ฆ‰์‹œ ์š”์†Œ๋ฅผ ๋ณ€๊ฒฝํ•˜๊ณ  ํฐํŠธ๋ฅผ ์ˆ˜์ •ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ฐ˜๋ฉด Claude Design์€ LLM(Large Language Model) ํ˜ธ์ถœ์„ ๊ธฐ๋‹ค๋ฆฌ๊ฑฐ๋‚˜ ํฌ๋ ˆ๋”ง(credit)์„ ์ถฉ์ „ํ•ด์•ผ ํ•˜๋Š” ๋“ฑ ์ง€์—ฐ์ด ๋ฐœ์ƒํ•ฉ๋‹ˆ๋‹ค. ๋ชจ๋ธ์ด ๊ฐœ์ž…ํ•˜์ง€ ์•Š๋Š” ๋น ๋ฅธ ๋ฐ˜๋ณต ์ž‘์—…์˜ ๊ฐ€์น˜๋ฅผ ๊ณผ์†Œํ‰๊ฐ€ํ•ด์„œ๋Š” ์•ˆ ๋ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ, ํฌ๋ ˆ๋”ง ์ œํ•œ์œผ๋กœ ์ธํ•ด ์ž‘์—… ๋„์ค‘ ์ง„ํ–‰์ด ๋ง‰ํžˆ๋Š” ๊ฒฝ์šฐ๋„ ์žˆ์–ด ์‚ฌ์šฉ์ž ๊ฒฝํ—˜์— ์˜ํ–ฅ์„ ๋ฏธ ๋ฏธ์นฉ๋‹ˆ๋‹ค.

2. ์ด๋ฏธ์ง€ ์ƒ์„ฑ์˜ ์ƒˆ๋กœ์šด ์‹œ๋Œ€: OpenAI์˜ GPT Image 2

OpenAI๋Š” ์ตœ๊ทผ GPT Image 2 ๋ชจ๋ธ์„ ์ถœ์‹œํ•˜๋ฉฐ ์ด๋ฏธ์ง€ ์ƒ์„ฑ์˜ ์ƒˆ๋กœ์šด ์‹œ๋Œ€๋ฅผ ์—ด์—ˆ์Šต๋‹ˆ๋‹ค. ์ด ๋ชจ๋ธ์€ โ€˜์‚ฌ๊ณ ํ•˜๋Š”(thinking)โ€™ ๋Šฅ๋ ฅ์„ ๊ฐ–์ถ˜ ์ตœ์ดˆ์˜ ๋ชจ๋ธ๋กœ, ํŠนํžˆ ํ…์ŠคํŠธ ๋ Œ๋”๋ง(rendering)๊ณผ ๊ฐœ์ฒด(object)์˜ ์ •ํ™•ํ•œ ํ‘œํ˜„์— ์ค‘์ ์„ ๋‘์—ˆ์Šต๋‹ˆ๋‹ค. ํด๋ ˆ์–ด๋Š” GPT Image 2๊ฐ€ ์ด ๋‘ ๊ฐ€์ง€ ์ธก๋ฉด์—์„œ ์–ผ๋งˆ๋‚˜ ๋›ฐ์–ด๋‚œ ์„ฑ๋Šฅ์„ ๋ณด์ด๋Š”์ง€ ๋‘ ๊ฐ€์ง€ ํ™œ์šฉ ์‚ฌ๋ก€๋ฅผ ํ†ตํ•ด ๋ณด์—ฌ์ฃผ์—ˆ์Šต๋‹ˆ๋‹ค.

2.1. ๋ธŒ๋žœ๋”ฉ ๋ฐ ๋งˆ์ผ€ํŒ… ํ™œ์šฉ

  • ๋ฉ€ํ‹ฐ ํŽ˜์ด์ง€ ๋ธŒ๋žœ๋“œ ํ‚คํŠธ ์ƒ์„ฑ: ํด๋ ˆ์–ด๋Š” ์ž์‹ ์˜ ํšŒ์‚ฌ์ธ Chat PRD๋ฅผ ์œ„ํ•œ ๋ฉ€ํ‹ฐ ํŽ˜์ด์ง€ ๋ธŒ๋žœ๋“œ ํ‚คํŠธ๋ฅผ ๋งŒ๋“ค์–ด ๋‹ฌ๋ผ๊ณ  ์š”์ฒญํ–ˆ์Šต๋‹ˆ๋‹ค. ์ผ๋ฐ˜์ ์ธ ๋ธŒ๋žœ๋“œ ๋””์ž์ธ ์ง€์นจ์„ ์ œ๊ณตํ•˜์ž, GPT Image 2๋Š” ํ…์ŠคํŠธ ํ’ˆ์งˆ ๋ฉด์—์„œ ๋งค์šฐ ํ›Œ๋ฅญํ•œ ๊ฒฐ๊ณผ๋ฌผ์„ ๋‚ด๋†“์•˜์Šต๋‹ˆ๋‹ค. ๊ธฐ์กด GPT ์ด๋ฏธ์ง€ ๋ชจ๋ธ์˜ ํŠน์ง•์ ์ธ โ€˜AI ์ด๋ฏธ์ง€ ํ…์ŠคํŠธโ€™ ๋А๋‚Œ์ด ๊ฑฐ์˜ ์‚ฌ๋ผ์กŒ๊ณ , ํƒ€์ดํฌ๊ทธ๋ž˜ํ”ผ๋„ ํฌ๊ฒŒ ๊ฐœ์„ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. 9๊ทธ๋ฆฌ๋“œ ๋ ˆ์ด์•„์›ƒ์œผ๋กœ ๋‹ค์–‘ํ•œ ๋ธŒ๋žœ๋“œ ์š”์†Œ๋ฅผ ๊ตฌ์„ฑํ•˜๋Š” ๋Šฅ๋ ฅ๋„ ์ธ์ƒ์ ์ด์—ˆ์Šต๋‹ˆ๋‹ค.
  • ์ฐธ์กฐ ์ด๋ฏธ์ง€๋ฅผ ํ†ตํ•œ ๊ฐœ์„ : ์ฒ˜์Œ ์ƒ์„ฑ๋œ ๋ธŒ๋žœ๋“œ ํ‚คํŠธ๋Š” Chat PRD์˜ ๊ธฐ์กด ๋ธŒ๋žœ๋“œ ์ด๋ฏธ์ง€์™€๋Š” ๋‹ค์†Œ ๊ฑฐ๋ฆฌ๊ฐ€ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค. ์ด์— ํด๋ ˆ์–ด๋Š” ๋ฏธ๋“œ์ €๋‹ˆ(Midjourney)์—์„œ ์‚ฌ์šฉํ•˜๋˜ ๋ฐ๊ณ  ํ•‘ํฌ์ƒ‰ ํ†ค์˜ ํ”ฝ์…€ํ™”๋œ ์ด๋ฏธ์ง€๋ฅผ ์ฐธ์กฐ ์ด๋ฏธ์ง€๋กœ ์ œ๊ณตํ•˜๋ฉฐ ๋ธŒ๋žœ๋“œ ํ‚คํŠธ๋ฅผ ์—…๋ฐ์ดํŠธํ•ด ๋‹ฌ๋ผ๊ณ  ์š”์ฒญํ–ˆ์Šต๋‹ˆ๋‹ค. GPT Image 2๋Š” ์ด ์ฐธ์กฐ ์ด๋ฏธ์ง€์˜ ์Šคํƒ€์ผ์„ ์„ฑ๊ณต์ ์œผ๋กœ ํ•™์Šตํ•˜์—ฌ ํ›จ์”ฌ ๋” ํ•‘ํฌ์ƒ‰์ด๊ณ  ํ”ฝ์…€ํ™”๋œ ๋А๋‚Œ์˜ ๋ธŒ๋žœ๋“œ ํ‚คํŠธ๋ฅผ ์ƒ์„ฑํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ๋งˆ์ผ€ํ„ฐ๋“ค์ด ๊ธฐ์กด ์ด๋ฏธ์ง€์™€ ํ…์ŠคํŠธ, ํƒ€์ดํฌ๊ทธ๋ž˜ํ”ผ, ๋ณด์ด์Šค(voice)๋ฅผ ํ†ตํ•ฉํ•˜๋Š” ๋ฐ ์–ด๋ ค์›€์„ ๊ฒช๋Š” ์ƒํ™ฉ์—์„œ GPT Image 2๊ฐ€ ํ›Œ๋ฅญํ•œ ์‹œ์ž‘์ ์ด ๋  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค.

2.2. ๊ฐœ์ธ์ ์ธ ํ™œ์šฉ ์‚ฌ๋ก€: ์ปฌ๋Ÿฌ ๋ถ„์„

ํด๋ ˆ์–ด๋Š” GPT Image 2์˜ ๋˜ ๋‹ค๋ฅธ ์žฌ๋ฏธ์žˆ๋Š” ํ™œ์šฉ ์‚ฌ๋ก€๋กœ โ€˜์ปฌ๋Ÿฌ ๋ถ„์„(color analysis)โ€˜์„ ์†Œ๊ฐœํ–ˆ์Šต๋‹ˆ๋‹ค. ์ž์‹ ์˜ ์‚ฌ์ง„์„ ์—…๋กœ๋“œํ•˜๊ณ  ์ปฌ๋Ÿฌ ๋ถ„์„์„ ์š”์ฒญํ•˜์ž, ๋ชจ๋ธ์€ โ€˜์›œ ๋‰ดํŠธ๋Ÿด(warm neutral)โ€™ ํ†ค์„ ์ œ์•ˆํ•˜๋ฉฐ ์–ด์šธ๋ฆฌ๋Š” ์ƒ‰์ƒ ํŒ”๋ ˆํŠธ๋ฅผ ์ œ์‹œํ•˜๊ณ , ์‹ฌ์ง€์–ด ๊ทธ ์ƒ‰์ƒ์˜ ์˜ท์„ ์ž…์€ ํด๋ ˆ์–ด์˜ ๋ชจ์Šต์„ ํ•ฉ์„ฑํ•ด ๋ณด์—ฌ์ฃผ์—ˆ์Šต๋‹ˆ๋‹ค. ์–ผ๊ตด ๋ถ€๋ถ„์ด ๋‹ค์†Œ ๋ถ€์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ํ‘œํ˜„๋˜๊ธฐ๋„ ํ–ˆ์ง€๋งŒ, ์ „๋ฐ˜์ ์ธ ๋ ˆ์ด์•„์›ƒ, ์ƒ‰์ƒ, ํ…์ŠคํŠธ ๋ถ„์„ ๋Šฅ๋ ฅ์€ ๋งค์šฐ ์ธ์ƒ์ ์ด์—ˆ์Šต๋‹ˆ๋‹ค.

ํด๋ ˆ์–ด๋Š” ์ž์‹ ์ด ์‹ค์ œ๋กœ๋Š” โ€˜๋‹คํฌ ์œˆํ„ฐ(dark winter)โ€™ ํ†ค์ž„์„ ์•Œ๋ ค์ฃผ๋ฉฐ ๋‹ค์‹œ ๋ถ„์„์„ ์š”์ฒญํ–ˆ๊ณ , GPT Image 2๋Š” ์ •ํ™•ํ•œ ์ƒ‰์ƒ ํŒ”๋ ˆํŠธ์™€ ๋ ˆ์ด์•„์›ƒ์„ ์ƒ์„ฑํ•ด ์ฃผ์—ˆ์Šต๋‹ˆ๋‹ค. ํ…์ŠคํŠธ, ์ƒ‰์ƒ, ์ด๋ฏธ์ง€ ๋ถ„์„, ๋ ˆ์ด์•„์›ƒ์„ ์ด์ฒ˜๋Ÿผ ํšจ๊ณผ์ ์œผ๋กœ ๊ฒฐํ•ฉํ•˜๋Š” ๋ชจ๋ธ์€ ๋“œ๋ฌผ๋ฉฐ, ๊ธฐ์กด์˜ ์ธํฌ๊ทธ๋ž˜ํ”ฝ(infographic)์ด๋‚˜ ๊ทธ๋ž˜ํ”ฝ ์ƒ์„ฑ ๋„๊ตฌ๋ณด๋‹ค ํ›จ์”ฌ ๋” ๊ณ ๊ธ‰์Šค๋Ÿฝ๊ณ  ๊น”๋”ํ•œ ๊ฒฐ๊ณผ๋ฌผ์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.

3. AI ๋””์ž์ธ ๋„๊ตฌ์˜ ๋ฏธ๋ž˜์™€ ์‹œ์‚ฌ์ 

์ด๋ฒˆ ์—ํ”ผ์†Œ๋“œ์—์„œ ์‚ดํŽด๋ณธ Claude Design๊ณผ GPT Image 2๋Š” AI๊ฐ€ ๋””์ž์ธ ๋ถ„์•ผ์—์„œ ์–ผ๋งˆ๋‚˜ ๋น ๋ฅด๊ฒŒ ๋ฐœ์ „ํ•˜๊ณ  ์žˆ๋Š”์ง€๋ฅผ ์—ฌ์‹คํžˆ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค.

  • Claude Design์€ ๋””์ž์ธ ์‹œ์Šคํ…œ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ๋งˆ์ผ€ํŒ… ๋žœ๋”ฉ ํŽ˜์ด์ง€, ์Šฌ๋ผ์ด๋“œ ๋ฐํฌ๋ฅผ ํšจ์œจ์ ์œผ๋กœ ๋งŒ๋“ค๊ณ , ๊ธฐ์กด ์›น์‚ฌ์ดํŠธ๋ฅผ ์žฌํ•ด์„ํ•˜๋Š” ๋ฐ ๊ฐ•์ ์„ ๋ณด์ž…๋‹ˆ๋‹ค.
  • GPT Image 2๋Š” ๋ ˆ์ด์•„์›ƒ๊ณผ ํƒ€์ดํฌ๊ทธ๋ž˜ํ”ผ์—์„œ ํ˜์‹ ์ ์ธ ๋ฐœ์ „์„ ์ด๋ฃจ์—ˆ์œผ๋ฉฐ, โ€˜์‚ฌ๊ณ ํ•˜๋Š”โ€™ ๋Šฅ๋ ฅ์„ ํ†ตํ•ด ๋””์ž์ธ ํ’ˆ์งˆ์„ ํ•œ ๋‹จ๊ณ„ ๋Œ์–ด์˜ฌ๋ ธ์Šต๋‹ˆ๋‹ค.

๋ฌผ๋ก , ์ด ๋ชจ๋“  ๋„๊ตฌ๋“ค์€ ์•„์ง ์ดˆ๊ธฐ ๋‹จ๊ณ„์ด๋ฉฐ, ๋А๋ฆฐ ์†๋„์™€ ํฌ๋ ˆ๋”ง ๋น„์šฉ๊ณผ ๊ฐ™์€ ๊ณตํ†ต์ ์ธ ํ•œ๊ณ„๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ตฌ๊ธ€์˜ design.md ํ‘œ์ค€ํ™” ๋…ธ๋ ฅ์—์„œ ๋ณผ ์ˆ˜ ์žˆ๋“ฏ์ด, AI๊ฐ€ ๋””์ž์ธ ์‹œ์Šคํ…œ๊ณผ ๋ธŒ๋žœ๋“œ๋ฅผ ์ดํ•ดํ•˜๋Š” ๋ฐฉ์‹์€ ๊ณ„์†ํ•ด์„œ ๋ฐœ์ „ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

๊ฒฐ๋ก ์ ์œผ๋กœ, ์ด ์ƒˆ๋กœ์šด AI ๋””์ž์ธ ๋„๊ตฌ๋“ค์€ ๊ฐ์ž์˜ ์žฅ์ ์„ ๊ฐ€์ง€๊ณ  ์žˆ์œผ๋ฉฐ, ์–ด๋–ค ๋„๊ตฌ๋„ โ€˜์ฃฝ์—ˆ๋‹คโ€™๊ณ  ๋งํ•˜๊ธฐ๋Š” ์ด๋ฆ…๋‹ˆ๋‹ค. ์ด๋“ค์€ ๋ชจ๋‘ ๋А๋ฆฌ์ง€๋งŒ ๊พธ์ค€ํžˆ ๋ฐœ์ „ํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์šฐ๋ฆฌ์˜ ๋””์ž์ธ ์ž‘์—… ๋ฐฉ์‹์„ ๋”์šฑ ํ˜์‹ ์ ์œผ๋กœ ๋ณ€ํ™”์‹œ์ผœ ๋‚˜๊ฐˆ ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์•ž์œผ๋กœ AI ๋„๊ตฌ๋“ค์ด ์–ด๋–ป๊ฒŒ ๋ฐœ์ „ํ•ด ๋‚˜๊ฐˆ์ง€ ๊ธฐ๋Œ€๋ฉ๋‹ˆ๋‹ค.


โ€œInside Kash Patelโ€™s F.B.I.โ€ โ€” New York Times Podcasts ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

์นด์‰ฌ ํŒŒํ…”์˜ FBI: ์ •์น˜ํ™”๋œ ์กฐ์ง, ํ”๋“ค๋ฆฌ๋Š” ์‚ฌ๋ช…

๋‰ด์š•ํƒ€์ž„์ฆˆ์˜ ํŒŸ์บ์ŠคํŠธ โ€˜๋” ๋ฐ์ผ๋ฆฌโ€™๋Š” ์นด์‰ฌ ํŒŒํ…”์ด ์—ฐ๋ฐฉ์ˆ˜์‚ฌ๊ตญ(FBI) ๊ตญ์žฅ์œผ๋กœ ์ž„๋ช…๋œ ์ดํ›„ ๊ทธ์˜ ๋ฆฌ๋”์‹ญ์ด ๋ถˆ๋Ÿฌ์˜จ ๋…ผ๋ž€๊ณผ ์šฐ๋ ค๋ฅผ ์‹ฌ์ธต ๋ณด๋„ํ–ˆ์Šต๋‹ˆ๋‹ค. ์—๋ฐ€๋ฆฌ ๋ฐ”์‹ค๋ก (Emily Basilon)๊ณผ ๋ ˆ์ด์ฒผ ํฌ์ €(Rachel Poser) ๋‘ ๊ธฐ์ž๋Š” ์ˆ˜์‹ญ ๋ช…์˜ ํ˜„์ง ๋ฐ ์ „์ง FBI ์ง์›๋“ค๊ณผ์˜ ์ธํ„ฐ๋ทฐ๋ฅผ ํ†ตํ•ด ์กฐ์ง์ด ์–ด๋–ป๊ฒŒ ๋ณ€๋ชจํ–ˆ๋Š”์ง€ ๋ฉด๋ฐ€ํžˆ ์ถ”์ ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋“ค์˜ ๋ณด๊ณ ์„œ๋Š” ํŠธ๋Ÿผํ”„ ํ–‰์ •๋ถ€ ํ•˜์—์„œ FBI๊ฐ€ ๊ฒช์—ˆ๋˜ ์ •์น˜์  ์••๋ ฅ๊ณผ ๊ทธ๋กœ ์ธํ•œ ๋‚ด๋ถ€ ํ˜ผ๋ž€, ๊ทธ๋ฆฌ๊ณ  ๊ตญ๊ฐ€ ์•ˆ๋ณด์— ๋ฏธ์น  ์ˆ˜ ์žˆ๋Š” ์ž ์žฌ์  ์œ„ํ—˜์„ ์ƒ์ƒํ•˜๊ฒŒ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค.

์นด์‰ฌ ํŒŒํ…”, ๋…ผ๋ž€์˜ ์ค‘์‹ฌ์— ์„œ๋‹ค

์นด์‰ฌ ํŒŒํ…”์€ FBI ๊ตญ์žฅ์ด๋ผ๋Š” ์ค‘์ฑ…์— ๋งค์šฐ ์ด๋ก€์ ์ธ ์ธ๋ฌผ์ด์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” FBI์—์„œ ์ผํ•œ ๊ฒฝํ—˜์ด ์ „๋ฌดํ–ˆ๊ณ , ์—ฐ๋ฐฉ ๋ฒ• ์ง‘ํ–‰ ๊ธฐ๊ด€์—์„œ์˜ ๊ฒฝํ—˜๋„ ๋ฏธ๋ฏธํ–ˆ์Šต๋‹ˆ๋‹ค. ์ „์ง ๊ตญ์„  ๋ณ€ํ˜ธ์ธ์ด์ž ํŠธ๋Ÿผํ”„ ํ–‰์ •๋ถ€ 1๊ธฐ์—์„œ ์ •๋ณด ๊ณ ์œ„ ๊ด€๋ฃŒ๋กœ ์ผํ–ˆ๋˜ ๊ทธ๋Š”, ์ฃผ๋ณ€ ์‚ฌ๋žŒ๋“ค๋กœ๋ถ€ํ„ฐ โ€œ๋”ฑํžˆ ์—ด์‹ฌํžˆ ์ผํ•˜์ง€๋Š” ์•Š์•˜์ง€๋งŒ ๋งค์šฐ ๊ฑด๋ฐฉ์ง€๊ณ  ์•ผ์‹ฌ๋งŒ๋งŒํ•˜๋ฉฐ ํ—ˆํ’์ด ์‹ฌํ•œโ€ ์ธ๋ฌผ๋กœ ๋ฌ˜์‚ฌ๋ฉ๋‹ˆ๋‹ค.

๋ฌด์—‡๋ณด๋‹ค ํŒŒํ…”์€ ๊ณผ๊ฑฐ FBI์— ๋Œ€ํ•œ ์Œ๋ชจ๋ก ์„ ์ œ๊ธฐํ•˜๋ฉฐ ์กฐ์ง์— ๋Œ€ํ•œ ๊นŠ์€ ๋ถˆ์‹ ์„ ๋“œ๋Ÿฌ๋ƒˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” 2020๋…„ ๋Œ€์„ ์ด ์กฐ ๋ฐ”์ด๋“ (Joe Biden)์— ์˜ํ•ด ์กฐ์ž‘๋˜์—ˆ๋‹ค๊ณ  ์ฃผ์žฅํ–ˆ์œผ๋ฉฐ, 1์›” 6์ผ ๋ฏธ๊ตญ ๊ตญํšŒ์˜์‚ฌ๋‹น ๋‚œ์ž… ์‚ฌํƒœ์—๋„ FBI ์š”์›๋“ค์ด ๊ฐœ์ž…ํ–ˆ๋‹ค๊ณ  ๋ฏฟ์—ˆ์Šต๋‹ˆ๋‹ค. ํŠธ๋Ÿผํ”„ ์ „ ๋Œ€ํ†ต๋ น์ด ๊ทธ๋ฅผ ๋ฐœํƒํ•œ ์ด์œ  ์ค‘ ํ•˜๋‚˜๋„ ๋ฐ”๋กœ ์ด๋Ÿฌํ•œ ์‹œ๊ฐ ๋•Œ๋ฌธ์ด์—ˆ์Šต๋‹ˆ๋‹ค. ํŒŒํ…”์€ ์‹ฌ์ง€์–ด FBI ๋ณธ๋ถ€๋ฅผ ํ์‡„ํ•˜๊ณ  โ€œ๋”ฅ ์Šคํ…Œ์ดํŠธ(deep state) ๋ฐ•๋ฌผ๊ด€โ€์œผ๋กœ ์žฌ๊ฐœ์žฅํ•ด์•ผ ํ•œ๋‹ค๊ณ  ์ฃผ์žฅํ•˜๊ธฐ๋„ ํ–ˆ์Šต๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ๋ฐฐ๊ฒฝ ๋•Œ๋ฌธ์— ํŒŒํ…”์˜ ์ž„๋ช…์€ FBI ๋‚ด์™ธ๋ถ€์—์„œ ํฐ ํšŒ์˜๊ฐ๊ณผ ์šฐ๋ ค๋ฅผ ๋ถˆ๋Ÿฌ์ผ์œผ์ผฐ์Šต๋‹ˆ๋‹ค. ์ •๋ณด๊ตญ์žฅ ํƒ€๋ƒ ์šฐ๊ณ ๋ฆฌ์ธ (Tanya Ugoritz)์™€ ๊ฐ™์€ ๊ณ ์œ„ ๊ฐ„๋ถ€๋“ค์€ ํŒŒํ…”์˜ ๋ฐฐ๊ฒฝ๊ณผ ์—…๋ฌด ๋ฐฉ์‹์— ๋Œ€ํ•œ ์ดํ•ด๋ฅผ ๋†’์ด๊ธฐ ์œ„ํ•ด ๊ทธ์˜ ์ฑ…์„ ์ฝ๊ณ  ํŒŸ์บ์ŠคํŠธ๋ฅผ ์ฒญ์ทจํ•˜๋Š” ๋“ฑ ๊ฐœ์ธ์ ์ธ ๋…ธ๋ ฅ์„ ๊ธฐ์šธ์˜€์ง€๋งŒ, ๊ณง ์ด๊ฒƒ์ด ํ‰์†Œ์™€ ๋‹ค๋ฅธ ์ƒํ™ฉ์ž„์„ ๊นจ๋‹ซ๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.

๊ธ‰์ง„์  ๋ณ€ํ™”์™€ ์กฐ์ง ๋‚ด๋ถ€์˜ ๋™์š”

ํŒŒํ…”์˜ ๋ฆฌ๋”์‹ญ ํ•˜์—์„œ FBI๋Š” ๊ณผ๊ฑฐ์˜ ๋…๋ฆฝ์„ฑ์„ ์ƒ์‹คํ•˜๊ณ  ์ •์น˜์  ์••๋ ฅ์— ์‹œ๋‹ฌ๋ฆฌ๋Š” ์กฐ์ง์œผ๋กœ ๋ณ€๋ชจํ–ˆ์Šต๋‹ˆ๋‹ค.

1. ๋ฌด๋ถ„๋ณ„ํ•œ ์กฐ์ง ๊ฐœํŽธ๊ณผ ์ธ์‚ฌ (Staffing Changes and Appointments)

ํŒŒํ…”์˜ ์ดˆ๊ธฐ ์ง€์‹œ ์ค‘ ํ•˜๋‚˜๋Š” ์ˆ˜๋ฐฑ ๋ช…์˜ ํ˜„์žฅ ์š”์›์„ ์›Œ์‹ฑํ„ด D.C. ๋ณธ๋ถ€์—์„œ ๊ฐ ์ง€๋ฐฉ ์‚ฌ๋ฌด์†Œ๋กœ ์žฌ๋ฐฐ์น˜ํ•˜๋Š” ๊ฒƒ์ด์—ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” D.C.์— ๋„ˆ๋ฌด ๋งŽ์€ ์ธ๋ ฅ์ด ์ง‘์ค‘๋˜์–ด ์žˆ๋‹ค๋Š” FBI ๋‚ด๋ถ€์˜ ์˜๊ฒฌ๋„ ์žˆ์—ˆ๊ธฐ์— ์ผ๋ถ€์—์„œ๋Š” ๊ธ์ •์ ์œผ๋กœ ํ‰๊ฐ€๋˜๊ธฐ๋„ ํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ๋ฌธ์ œ๋Š” ๊ทธ ๋ฐฉ์‹์ด์—ˆ์Šต๋‹ˆ๋‹ค. ์žฌ๋ฐฐ์น˜๊ฐ€ ๋ฌด์ž‘์œ„์ ์ด๊ณ  ์ž„์˜์ ์œผ๋กœ ์ด๋ฃจ์–ด์กŒ์œผ๋ฉฐ, ์š”์›๋“ค์ด ์ƒˆ๋กœ์šด ํ™˜๊ฒฝ์—์„œ ์ œ๋Œ€๋กœ ์—…๋ฌด๋ฅผ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์„์ง€์— ๋Œ€ํ•œ ๊ณ ๋ ค๊ฐ€ ๋ถ€์กฑํ–ˆ์Šต๋‹ˆ๋‹ค. ํƒ€๋ƒ ์šฐ๊ณ ๋ฆฌ์ธ ๋Š” ์ด๋ฅผ โ€œ๋ณธ๋ถ€์˜ ์—…๋ฌด์— ๋Œ€ํ•œ ์ดํ•ด ๋ถ€์กฑโ€์—์„œ ๋น„๋กฏ๋œ ๊ฒฐ์ •์ด๋ผ๊ณ  ์ง€์ ํ•˜๋ฉฐ, โ€œ์ผ๋‹จ ๊ฒฐ์ •ํ•˜๊ณ  ๋‚˜์ค‘์— ์ˆ˜์Šตํ•˜๋Š”โ€ ํŒจํ„ด์˜ ์‹œ์ž‘์ด์—ˆ๋‹ค๊ณ  ํšŒ๊ณ ํ–ˆ์Šต๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ๊ฒฝํ–ฅ์€ ํŒŒํ…”์ด ๋Œ„ ๋ด‰๊ธฐ๋…ธ(Dan Bongino)๋ฅผ ๋ถ€๊ตญ์žฅ์œผ๋กœ ์ž„๋ช…ํ•˜๋ฉด์„œ ๋”์šฑ ์‹ฌํ™”๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ์ „์ง ๋น„๋ฐ€๊ฒฝํ˜ธ๊ตญ ์š”์›์ด์ž ์นœ(่ฆช)ํŠธ๋Ÿผํ”„ ํŒŸ์บ์Šคํ„ฐ, ํญ์Šค ๋‰ด์Šค(Fox News) ํ‰๋ก ๊ฐ€์˜€๋˜ ๋ด‰๊ธฐ๋…ธ๋Š” FBI ์š”์›๋“ค์„ โ€œ๋ฏผ์ฃผ๋‹น์˜ ๊นกํŒจโ€๋ผ๊ณ  ๋ฌ˜์‚ฌํ•˜๊ณ  FBI ํ•ด์ฒด๋ฅผ ์ฃผ์žฅํ–ˆ๋˜ ์ธ๋ฌผ์ด์—ˆ์Šต๋‹ˆ๋‹ค. ์กด ์„ค๋ฆฌ๋ฒˆ(John Sullivan)๊ณผ ๊ฐ™์€ ์ •๋ณด ๋ถ€์„œ์˜ ์š”์›๋“ค์€ ๋ด‰๊ธฐ๋…ธ์˜ ์ž„๋ช…์„ ๋ณด๋ฉฐ โ€œ์ด์ œ ๋ชจ๋“  ๊ฒƒ์ด ๊ดœ์ฐฎ์ง€ ์•Š์„ ๊ฒƒโ€์ด๋ผ๊ณ  ์ง๊ฐํ–ˆ์Šต๋‹ˆ๋‹ค.

2. โ€˜๋ณด์—ฌ์ฃผ๊ธฐ์‹โ€™ ํ–‰์ •๊ณผ ์ž„๋ฌด์˜ ์ •์น˜ํ™” (Prioritizing Optics and Politicized Mission)

ํŒŒํ…”๊ณผ ๋ด‰๊ธฐ๋…ธ์˜ ๋ฆฌ๋”์‹ญ์—์„œ ๊ฐ€์žฅ ๋‘๋“œ๋Ÿฌ์ง„ ํŠน์ง•์€ โ€˜๋ณด์—ฌ์ฃผ๊ธฐโ€™ ์ฆ‰, ํ™๋ณด ํšจ๊ณผ๋ฅผ ์ง€๋‚˜์น˜๊ฒŒ ์ค‘์‹œํ–ˆ๋‹ค๋Š” ์ ์ž…๋‹ˆ๋‹ค. ํŠธ๋Ÿผํ”„ ์ „ ๋Œ€ํ†ต๋ น์ด ์ˆ˜์‚ฌ ํ˜„์žฅ์—์„œ FBI ๋ฐฉํƒ„์กฐ๋ผ(flak jackets)๋ฅผ ๋ณด์ง€ ๋ชปํ•ด ๋ถˆ๋งŒ์„ ํ‘œ์ถœํ•œ ์ผํ™”๋Š” ์ด๋Ÿฌํ•œ ๊ฒฝํ–ฅ์„ ๋‹จ์ ์œผ๋กœ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ํŒŒํ…”์€ ์ฝดํ‹ฐ์ฝ”(Quantico) ํ›ˆ๋ จ์žฅ์—์„œ โ€˜๋žŒ๋ณดโ€™์ฒ˜๋Ÿผ ํญ๋ฐœ ์žฅ๋ฉด๊ณผ ํ—ฌ๋ฆฌ์ฝฅํ„ฐ ๋ ˆํŽ  ํ›ˆ๋ จ์„ ๋ฐฐ๊ฒฝ์œผ๋กœ ์ดฌ์˜ํ•œ ๋น„๋””์˜ค๋ฅผ ๊ณต๊ฐœํ•˜๊ธฐ๋„ ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” FBI๊ฐ€ ๊ฐ•์ธํ•œ ์กฐ์ง์ด๋ผ๋Š” ์ด๋ฏธ์ง€๋ฅผ ์‹ฌ์–ด์ฃผ๊ธฐ ์œ„ํ•จ์ด์—ˆ์ง€๋งŒ, ์‹ค์ œ๋กœ๋Š” ๊ท€์ค‘ํ•œ ์ž์›๊ณผ ์‹œ๊ฐ„์„ ๋‚ญ๋น„ํ•˜๊ณ  ์กฐ์ง์˜ ์ „๋ฌธ์„ฑ์„ ํ›ผ์†ํ•˜๋Š” ํ–‰์œ„๋กœ ๋น„ํŒ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ โ€˜๋ณด์—ฌ์ฃผ๊ธฐ์‹โ€™ ํ–‰์ •์€ ์ฐฐ๋ฆฌ ์ปคํฌ(Charlie Kirk) ์ด๊ฒฉ ์‚ฌ๊ฑด ์ˆ˜์‚ฌ์—์„œ ์‹ฌ๊ฐํ•œ ๋ฌธ์ œ๋ฅผ ์•ผ๊ธฐํ–ˆ์Šต๋‹ˆ๋‹ค. FBI ๊ตญ์žฅ์œผ๋กœ์„œ๋Š” ์ด๋ก€์ ์œผ๋กœ ํŒŒํ…”์€ ์ˆ˜์‚ฌ ์ดˆ๊ธฐ ๋‹จ๊ณ„๋ถ€ํ„ฐ ๊ฐœ์ž…ํ•˜์—ฌ ํ˜„์žฅ ์š”์›๋“ค์„ ์งˆ์ฑ…ํ•˜๊ณ  ์†Œ์…œ ๋ฏธ๋””์–ด ์ „๋žต์„ ์ง์ ‘ ์ง€์‹œํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ๊ณผ์ •์—์„œ ์ž˜๋ชป๋œ ์ •๋ณด๊ฐ€ ์œ ํฌ๋˜์–ด ์ˆ˜์‚ฌ์˜ ํ˜ผ์„ ์„ ์ดˆ๋ž˜ํ–ˆ๊ณ , ํ˜„์žฅ ์š”์›๋“ค์€ ์‚ฌ์‹ค ํ™•์ธ๋ณด๋‹ค ์–ธ๋ก  ๋Œ€์‘์— ๊ธ‰๊ธ‰ํ•œ ์ƒํ™ฉ์— ๊นŠ์€ ์ขŒ์ ˆ๊ฐ์„ ๋А๊ผˆ์Šต๋‹ˆ๋‹ค. ์ˆ˜์‚ฌ ์ค‘ ์‚ฌ์ง„ ์ดฌ์˜์„ ๊ฐ•์š”ํ•˜๋Š” ๋“ฑ์˜ ์ง€์‹œ๋Š” ์ž‘์ „ ๋ณด์•ˆ๊ณผ ์š”์›๋“ค์˜ ์•ˆ์ „๊นŒ์ง€ ์œ„ํ˜‘ํ–ˆ์Šต๋‹ˆ๋‹ค.

์‹ฌ์ง€์–ด ํ•ด์™ธ ๋™๋งน๊ตญ๊ณผ์˜ ๊ด€๊ณ„์—๋„ ์•…์˜ํ–ฅ์„ ๋ฏธ์ณค์Šต๋‹ˆ๋‹ค. ํŒŒํ…”์€ ์˜๊ตญ์—์„œ ์—ด๋ฆฐ ๋น„๋ฐ€ ์ •๋ณด ํšŒ์˜์— ์ฐธ์„ํ•œ ๋’ค, ์ฐธ๊ฐ€์ž๋“ค์˜ ์‹ ์›์ด ๊ณต๊ฐœ๋˜์ง€ ์•Š๋„๋ก ์š”์ฒญ๋œ ๋‹จ์ฒด ์‚ฌ์ง„์„ ์ž์‹ ์˜ ์†Œ์…œ ๋ฏธ๋””์–ด์— ๊ฒŒ์‹œํ•˜๋ ค ํ•ด ๊ตญ์ œ์  ์™ธ๊ต ๋ฌธ์ œ๋ฅผ ์ผ์œผํ‚ฌ ๋ป”ํ–ˆ์Šต๋‹ˆ๋‹ค. ์˜๊ตญ ์ •๋ถ€๊ฐ€ ๊ฐ•๋ ฅํ•˜๊ฒŒ ๋งŒ๋ฅ˜ํ•œ ํ›„์—์•ผ ๊ฒŒ์‹œ๋ฅผ ์ฒ ํšŒํ–ˆ์ง€๋งŒ, ์ด๋Š” ํŒŒํ…”์˜ โ€˜๋ณด์—ฌ์ฃผ๊ธฐโ€™ ์ง‘์ฐฉ์ด ์–ผ๋งˆ๋‚˜ ์‹ฌ๊ฐํ•œ ์ˆ˜์ค€์ด์—ˆ๋Š”์ง€๋ฅผ ๋ณด์—ฌ์ฃผ๋Š” ์‚ฌ๋ก€์ž…๋‹ˆ๋‹ค.

FBI ๋Œ€๋ณ€์ธ ๋ฒค ์œŒ๋ฆฌ์—„์Šจ(Ben Williamson)์€ ์ด ๋ชจ๋“  ๋ณด๋„๋ฅผ โ€œํ˜„์‹ค๊ณผ ๋™๋–จ์–ด์ง„ ์ต๋ช…์˜ ์ถœ์ฒ˜์—์„œ ๋‚˜์˜จ ๊ฐ€์งœ ์ด์•ผ๊ธฐ์™€ ์ถ”์ธกโ€์ด๋ผ๊ณ  ์ผ์ถ•ํ–ˆ์ง€๋งŒ, ๊ธฐ์ž๋“ค์€ ์—ฌ๋Ÿฌ ๋ช…์˜ ์‹ค๋ช… ์ถœ์ฒ˜๋ฅผ ํ†ตํ•ด ํŒŒํ…”์˜ ๋ฆฌ๋”์‹ญ์ด ์˜ค์ง โ€œ๋Œ€ํ†ต๋ น์ด๋ผ๋Š” ๋‹จ ํ•œ ๋ช…์˜ ์ฒญ์ค‘โ€์„ ๋งŒ์กฑ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ์ •์น˜์™€ ์ด๋ฏธ์ง€๋ฅผ ์ตœ์šฐ์„ ์œผ๋กœ ์‚ผ์•˜์Œ์„ ๋ฐํ˜€๋ƒˆ์Šต๋‹ˆ๋‹ค.

์ž„๋ฌด ์žฌ์ •์˜์™€ โ€˜์ •์น˜์  ์ˆ™์ฒญโ€™

ํŒŒํ…”์˜ ๋ฆฌ๋”์‹ญ์€ FBI์˜ ํ•ต์‹ฌ ์ž„๋ฌด๋ฅผ ์žฌ์ •์˜ํ•˜๊ณ , ์กฐ์ง ๋‚ด๋ถ€์— โ€˜์ •์น˜์  ์ˆ™์ฒญโ€™์ด๋ผ๋Š” ์•”์šธํ•œ ๊ทธ๋ฆผ์ž๋ฅผ ๋“œ๋ฆฌ์› ์Šต๋‹ˆ๋‹ค.

1. ์ด๋ฏผ ๋‹จ์†์œผ๋กœ์˜ ์ž„๋ฌด ์ „ํ™˜ (Shift to Immigration Enforcement)

ํŠธ๋Ÿผํ”„ ํ–‰์ •๋ถ€์˜ ์ด๋ฏผ ๋‹จ์† ๊ฐ•ํ™” ๊ธฐ์กฐ์— ๋”ฐ๋ผ FBI์˜ ์ผ์ƒ์ ์ธ ์—…๋ฌด๋Š” ํฌ๊ฒŒ ๋ณ€์งˆ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ์ „ํ†ต์ ์œผ๋กœ ์ด๋ฏผ ๋‹จ์†์— ๊ด€์—ฌํ•˜์ง€ ์•Š๋˜ FBI๋Š” ์ „๊ตญ์ ์œผ๋กœ ์ˆ˜๋งŽ์€ ์š”์›๊ณผ ๋ถ„์„๊ฐ€๋“ค์„ ์ด๋ฏผ ๊ด€๋ จ ์—…๋ฌด์— ์žฌ๋ฐฐ์น˜ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋กœ ์ธํ•ด ๊ณต๊ณต ๋ถ€ํŒจ, ์‚ฌ์ด๋ฒ„ ๋ฒ”์ฃ„, ํ™”์ดํŠธ์นผ๋ผ ๋ฒ”์ฃ„, ๋งˆ์•ฝ ๋ฐ€๋งค, ํ…Œ๋Ÿฌ๋ฆฌ์ฆ˜ ๋“ฑ FBI์˜ ํ•ต์‹ฌ ์šฐ์„ ์ˆœ์œ„์˜€๋˜ ๋ถ„์•ผ์—์„œ ์ธ๋ ฅ ๊ณต๋ฐฑ์ด ๋ฐœ์ƒํ–ˆ์Šต๋‹ˆ๋‹ค.

๋กœ์Šค์•ค์ ค๋ ˆ์Šค์—์„œ ๊ฐ•๋ ฅ ๋ฒ”์ฃ„๋ฅผ ๋‹ด๋‹นํ•˜๋˜ ์ •๋ณด ๋ถ„์„๊ฐ€ ์งˆ ํ•„์ฆˆ(Jill Fields)์˜ ์‚ฌ๋ก€๋Š” ์ด๋Ÿฌํ•œ ๋ณ€ํ™”์˜ ๋‹จ๋ฉด์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ๊ทธ๋…€๋Š” ๋‚จํŽธ๊ณผ ํ•จ๊ป˜ FBI์— ํ—Œ์‹ ํ•˜๋ฉฐ ์ž๋…€์—๊ฒŒ๋„ โ€˜์ฃผ๋‹ˆ์–ด ์š”์›โ€™ ์žฌํ‚ท์„ ์ž…ํž ์ •๋„๋กœ ์กฐ์ง์— ๋Œ€ํ•œ ์ž๋ถ€์‹ฌ์ด ์ปธ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํŠธ๋Ÿผํ”„ ํ–‰์ •๋ถ€์˜ ์ด๋ฏผ ๋‹จ์†์ด ๊ฐ•ํ™”๋˜๋ฉด์„œ ๊ทธ๋…€๋Š” ์ด๋ฏผ ๊ด€๋ จ ์—…๋ฌด์— ํˆฌ์ž…๋˜์—ˆ๊ณ , ๊ฒฐ๊ตญ โ€˜๋ ˆ๋“œ ๋ผ์ธโ€™์„ ๋„˜๋Š” ์ง€์‹œ๋ฅผ ๋ฐ›๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.

๊ทธ๋…€๋Š” ์‹œ์œ„๋Œ€๊ฐ€ ์ด๋ฏผ์„ธ๊ด€์ง‘ํ–‰๊ตญ(ICE) ์š”์›๋“ค์˜ ์ฒดํฌ๋ฅผ ๋ฐฉํ•ดํ–ˆ๋‹ค๋Š” ์ฃผ์žฅ์— ๋Œ€ํ•ด ์˜ˆ๋น„ ํ‰๊ฐ€(preassessment)๋ฅผ ์‹ค์‹œํ•˜๋ผ๋Š” ์ง€์‹œ๋ฅผ ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค. ์‹œ์œ„๋Œ€๋Š” ํ™•์„ฑ๊ธฐ๋ฅผ ์‚ฌ์šฉํ–ˆ์ง€๋งŒ, ์š”์›๋“ค์ด ์„ค์ •ํ•œ ์„ ์„ ๋„˜์ง€ ์•Š์•˜์œผ๋ฉฐ ๋ฒ•์— ์ €์ด‰๋˜๋Š” ์–ด๋– ํ•œ ํ–‰์œ„๋„ ํ•˜์ง€ ์•Š์•˜๋‹ค๋Š” ๊ฒƒ์ด ํ˜„์žฅ ์š”์›๋“ค์˜ ํŒ๋‹จ์ด์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿผ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ํ•„์ฆˆ๋Š” ์ˆ˜์‚ฌ๋ฅผ ๊ฐ•ํ–‰ํ•˜๋ผ๋Š” ์••๋ ฅ์„ ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค. ๊ทธ๋…€๋Š” ์ด๋ฅผ โ€œํ—Œ๋ฒ•์œผ๋กœ ๋ณดํ˜ธ๋ฐ›๋Š” ํ™œ๋™โ€์ด๋ผ๋ฉฐ ๊ฑฐ๋ถ€ํ–ˆ๊ณ , โ€œ์ง€๊ธˆ ํ•ด๊ณ ๋˜๊ฑฐ๋‚˜, ์•„๋‹ˆ๋ฉด 40๋…„ ํ›„์— ๋‹ค๋ฅธ ํ–‰์ •๋ถ€๊ฐ€ ๋“ค์–ด์™€ ๋ฒ•์„ ์œ„๋ฐ˜ํ•œ ์‚ฌ๋žŒ๋“ค์„ ์ฐพ์•„๋‚ผ ๋•Œ ํ•ด๊ณ ๋  ๊ฒƒโ€์ด๋ผ๋Š” ๊ฒฝ๊ณ ๋ฅผ ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค. ๊ฒฐ๊ตญ ๊ทธ๋…€๋Š” ๋ถ€์„œ์—์„œ ๋ฐฐ์ œ๋˜๊ณ  ๊ฐ์‹œ๋ฅผ ๋ฐ›๋‹ค๊ฐ€ FBI๋ฅผ ๋– ๋‚˜๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.

์ด ์‚ฌ๊ฑด์€ FBI๊ฐ€ ๊ณผ๊ฑฐ J. ์—๋“œ๊ฑฐ ํ›„๋ฒ„(J. Edgar Hoover) ๊ตญ์žฅ ์‹œ์ ˆ ์‹œ๋ฏผ๋“ค์˜ ํ—Œ๋ฒ•์  ๊ถŒ๋ฆฌ๋ฅผ ์นจํ•ดํ–ˆ๋˜ ๊ณผ์˜ค๋ฅผ ๋˜ํ’€์ดํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์šฐ๋ ค๋ฅผ ๋ถˆ๋Ÿฌ์ผ์œผ์ผฐ์Šต๋‹ˆ๋‹ค. ์ฝดํ‹ฐ์ฝ” ์•„์นด๋ฐ๋ฏธ์—์„œ๋ถ€ํ„ฐ ์ž„๋ฌด์™€ ์‹œ๋ฏผ๊ถŒ์„ ๊ท ํ˜• ์žˆ๊ฒŒ ๋‹ค๋ฃจ๋„๋ก ๊ต์œก๋ฐ›์•˜๋˜ FBI ์š”์›๋“ค์—๊ฒŒ ์ด๋Ÿฌํ•œ ์ง€์‹œ๋Š” ์กฐ์ง์˜ ๊ทผ๋ณธ์ ์ธ ๊ฐ€์น˜๋ฅผ ํ›ผ์†ํ•˜๋Š” ๊ฒƒ์ด์—ˆ์Šต๋‹ˆ๋‹ค.

2. ๊ณผ๊ฑฐ ์—…๋ฌด๊ฐ€ โ€˜์กฑ์‡„โ€™๊ฐ€ ๋˜๋‹ค (Past Work as a Liability)

ํŒŒํ…”์€ ๊ณผ๊ฑฐ ๋Œ€ํ†ต๋ น์„ ์ˆ˜์‚ฌํ–ˆ๋˜ ์ง์›๋“ค์„ ์กฐ์ง์—์„œ ์ˆ™์ฒญํ•˜๊ฒ ๋‹ค๊ณ  ๊ณต์–ธํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ โ€˜์ •์น˜์  ์ˆ™์ฒญโ€™์€ ํƒ€๋ƒ ์šฐ๊ณ ๋ฆฌ์ธ ์˜ ์‚ฌ๋ก€์—์„œ๋„ ๋ช…ํ™•ํžˆ ๋“œ๋Ÿฌ๋‚ฉ๋‹ˆ๋‹ค.

2020๋…„ 9์›”, FBI๋Š” ์ค‘๊ตญ ์ •๋ถ€๊ฐ€ 2020๋…„ ๋Œ€์„ ์—์„œ ์กฐ ๋ฐ”์ด๋“ ์„ ์œ„ํ•ด ๊ฐ€์งœ ์‹ ๋ถ„์ฆ์„ ๋งŒ๋“ค์—ˆ๋‹ค๋Š” ์ •๋ณด ๋ณด๊ณ ์„œ๋ฅผ ๋ฐœํ‘œํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ์ •๋ณด์˜ ์‹ ๋ขฐ์„ฑ์— ๋Œ€ํ•œ ๋…ผ๋ž€ ๋์— FBI๋Š” ๋ณด๊ณ ์„œ๋ฅผ ์ฒ ํšŒํ–ˆ์Šต๋‹ˆ๋‹ค. ์ดํ›„ ์ฒ™ ๊ทธ๋ž˜์Šฌ๋ฆฌ(Chuck Grassley) ์ƒ์›์˜์›์ด FBI์˜ ๋‚ด๋ถ€ ๋ฌธ์„œ๋ฅผ ์š”๊ตฌํ•˜๋Š” ๊ณผ์ •์—์„œ, ํ•œ FBI ์ง์›์ด ํƒ€๋ƒ ์šฐ๊ณ ๋ฆฌ์ธ ๋ฅผ ์ด ๋ณด๊ณ ์„œ ์ฒ ํšŒ๋ฅผ ์ง€์‹œํ•œ ์ธ๋ฌผ๋กœ ์ž˜๋ชป ์ง€๋ชฉํ•œ ์ด๋ฉ”์ผ์ด ๋ฐœ๊ฒฌ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.

ํŒŒํ…”๊ณผ ๋ด‰๊ธฐ๋…ธ๋Š” ์ด ์‚ฌ์•ˆ์ด โ€œ์ž์‹ ๋“ค์˜ ์†์„ ๋– ๋‚ฌ๋‹คโ€๊ณ  ๋งํ•˜๋ฉฐ ๊ทธ๋…€๋ฅผ ํ–‰์ • ํœด์ง(administrative leave)์— ์ฒ˜ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ดํ›„ ๋‘ ์ฐจ๋ก€์˜ ์‹ฌ๋ฌธ๊ณผ ๊ฑฐ์ง“๋ง ํƒ์ง€๊ธฐ ์กฐ์‚ฌ๋ฅผ ๊ฑฐ์ณค์ง€๋งŒ, ๋‚ด๋ถ€ ์กฐ์‚ฌ ๊ฒฐ๊ณผ ๊ทธ๋…€์˜ ์–ด๋– ํ•œ ์œ„๋ฒ• ํ–‰์œ„๋„ ๋ฐœ๊ฒฌ๋˜์ง€ ์•Š์•˜์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿผ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ๊ทธ๋…€๋Š” ์ด์ „ ์ง์ฑ…์œผ๋กœ ๋ณต๊ท€ํ•˜๋Š” ๊ฒƒ์„ ๊ฑฐ๋ถ€๋‹นํ–ˆ๊ณ , ๋‹ค๋ฅธ ์ง€๋ฐฉ ์‚ฌ๋ฌด์†Œ๋กœ ์ „์ถœ ๋ฐ ๊ฐ•๋“ฑ๋  ๊ฒƒ์ด๋ผ๋Š” ํ†ต๋ณด๋ฅผ ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค. ๊ฒฐ๊ตญ ๊ทธ๋…€๋Š” 24๋…„๊ฐ„ ํ—Œ์‹ ํ–ˆ๋˜ FBI๋ฅผ ๋– ๋‚  ์ˆ˜๋ฐ–์— ์—†์—ˆ์Šต๋‹ˆ๋‹ค. ๊ธฐ์ž๋“ค์€ ์ด๋ฅผ โ€œ๋’ค์–ฝํžŒ ์ด์•ผ๊ธฐ์˜ ํฌ์ƒ์–‘โ€์ด์ž โ€œ๋ˆ„๊ตฌ์˜ ๋จธ๋ฆฌ๋“  ๊ตด๋Ÿฌ๊ฐ€์•ผ ํ•œ๋‹คโ€๋Š” ํŒŒํ…”๊ณผ ๋ด‰๊ธฐ๋…ธ์˜ ๋ฉ”์‹œ์ง€์˜€๋‹ค๊ณ  ๋ถ„์„ํ–ˆ์Šต๋‹ˆ๋‹ค.

๋ธ”๋ ˆ์–ด ํ†จ๋จผ(Blair Tolman)์˜ ์‚ฌ๋ก€๋„ ์œ ์‚ฌํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋…€๋Š” ํŠธ๋Ÿผํ”„ ํ–‰์ •๋ถ€ 2๊ธฐ ์ด์ „์— FBI์˜ ์—˜๋ฆฌํŠธ ๊ณต๊ณต ๋ถ€ํŒจ ์ˆ˜์‚ฌํŒ€(CR15)์˜ ํŒ€์žฅ์ด์—ˆ์Šต๋‹ˆ๋‹ค. ์ด ํŒ€์€ ํŠธ๋Ÿผํ”„ ์ „ ๋Œ€ํ†ต๋ น์˜ 2020๋…„ ๋Œ€์„  ๊ฐœ์ž… ์—ฌ๋ถ€๋ฅผ ์ˆ˜์‚ฌํ–ˆ๋Š”๋ฐ, ์ด๋Š” โ€˜์•„ํฌํ‹ฑ ํ”„๋กœ์ŠคํŠธ(Arctic Frost)โ€˜๋ผ๋Š” ์ฝ”๋“œ๋„ค์ž„์œผ๋กœ ๋ถˆ๋ ธ์Šต๋‹ˆ๋‹ค. ์ด ์ˆ˜์‚ฌ๋Š” ํŠธ๋Ÿผํ”„์™€ ๊ทธ๋ž˜์Šฌ๋ฆฌ ์ƒ์›์˜์›์˜ ์ฃผ์š” ํ‘œ์ ์ด ๋˜์—ˆ๊ณ , ํ†จ๋จผ์€ ์ž์‹ ์ด ์„ ๋ฐœํ–ˆ๋˜ ์œ ๋Šฅํ•œ ์š”์›๋“ค์ด ํ•ด๊ณ ๋˜๋Š” ๊ฒƒ์„ ์ง€์ผœ๋ด์•ผ ํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ฒฐ๊ตญ ๊ทธ๋…€ ์ž์‹ ๋„ โ€œํŒ๋‹จ๋ ฅ ๋ถ€์กฑ๊ณผ ๊ณต์ •์„ฑ ๊ฒฐ์—ฌโ€๋ฅผ ์ด์œ ๋กœ ํ•ด๊ณ ๋˜์—ˆ๋Š”๋ฐ, ์ด๋Š” ์‚ฌ์‹ค์ƒ ์ž์‹ ์ด ๋‹ด๋‹นํ–ˆ๋˜ ์ˆ˜์‚ฌ ๋•Œ๋ฌธ์ด์—ˆ๋‹ค๊ณ  ๊ทธ๋…€๋Š” ํšŒ๊ณ ํ–ˆ์Šต๋‹ˆ๋‹ค.

ํ”๋“ค๋ฆฌ๋Š” FBI์˜ ๋ฏธ๋ž˜

์ด๋Ÿฌํ•œ ์ผ๋ จ์˜ ์‚ฌ๊ฑด๋“ค์€ FBI ๋‚ด๋ถ€์— ๊นŠ์€ ๊ณตํฌ์™€ ํŽธ์ง‘์ฆ์˜ ๋ฌธํ™”๋ฅผ ์กฐ์„ฑํ–ˆ์Šต๋‹ˆ๋‹ค. ํŒŒํ…”์ด ๊ตญ์žฅ์œผ๋กœ ์ทจ์ž„ํ•œ ์ดํ›„ ์ˆ˜์‹ญ ๋ช…์˜ ์ง์›์ด ํ•ด๊ณ ๋˜์—ˆ๊ณ , ์ด๋Ÿฌํ•œ ํ•ด๊ณ ๋Š” ๊ณ„์†๋˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์š”์›๋“ค์€ ๋‹ค์Œ ํ–‰์ •๋ถ€๊ฐ€ ์ž์‹ ์˜ ์—…๋ฌด๋ฅผ ์ •์น˜์ ์œผ๋กœ ํ•ด์„ํ•˜์—ฌ ํ•ด๊ณ  ์‚ฌ์œ ๋กœ ์‚ผ์„๊นŒ ๋ด ์ •์น˜์ ์œผ๋กœ ๋ฏผ๊ฐํ•œ ์ž„๋ฌด๋ฅผ ๋งก๋Š” ๊ฒƒ์„ ์ฃผ์ €ํ•˜๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ๊ฒฐ๊ตญ ๋ถ€ํŒจ๋‚˜ ํ…Œ๋Ÿฌ ์œ„ํ˜‘๊ณผ ๊ฐ™์€ ์ค‘์š”ํ•œ ์ •๋ณด๊ฐ€ ์€ํ๋  ์ˆ˜ ์žˆ์œผ๋ฉฐ, ๋ฏธ๊ตญ์ธ๋“ค์˜ ์•ˆ์ „์ด ์œ„ํ˜‘๋ฐ›์„ ์ˆ˜ ์žˆ์Œ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค.

FBI ์ง์›๋“ค์€ ์กฐ์ง์˜ ๋‚ด๋ถ€ ๊ฒฌ์ œ ์‹œ์Šคํ…œ์ด๋‚˜ ์ƒ๊ธ‰์ž์™€์˜ ์†Œํ†ต ์ฑ„๋„์ด ์ œ๋Œ€๋กœ ์ž‘๋™ํ•˜์ง€ ์•Š๋Š”๋‹ค๊ณ  ๋А๋ผ๋ฉด์„œ, ํ‰์†Œ์—๋Š” ๋น„๋ฐ€์Šค๋Ÿฌ์šด ์ด๋“ค์ด ์–ธ๋ก ๊ณผ ๋ฒ•์›์— ์˜์ง€ํ•˜๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๋ธ”๋ ˆ์–ด ํ†จ๋จผ์€ ํ˜„์žฌ FBI๋ฅผ ์ƒ๋Œ€๋กœ ํ•œ ์ง‘๋‹จ ์†Œ์†ก์˜ ์ฃผ์š” ์›๊ณ  ์ค‘ ํ•œ ๋ช…์ž…๋‹ˆ๋‹ค. ์ด ์†Œ์†ก์€ โ€˜์ •์น˜์  ์ˆ™์ฒญโ€™์œผ๋กœ ์ธํ•œ ํ•ด๊ณ ์— ์ด์˜๋ฅผ ์ œ๊ธฐํ•˜๊ณ , ์ •๋‹นํ•œ ์ ˆ์ฐจ๋ฅผ ์š”๊ตฌํ•˜๋ฉฐ, ๋‹ค๋ฅธ ์š”์›๋“ค์„ ๋ณดํ˜ธํ•˜๊ธฐ ์œ„ํ•œ ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๊ธฐ์ž๋“ค์€ FBI๊ฐ€ ์™„๋ฒฝํ•˜์ง€ ์•Š์œผ๋ฉฐ ๊ฐœํ˜์ด ํ•„์š”ํ•˜๋‹ค๋Š” ์ ์—๋Š” ๋ชจ๋‘๊ฐ€ ๋™์˜ํ•˜์ง€๋งŒ, ํ˜„์žฌ ์ง„ํ–‰๋˜๋Š” ๋ณ€ํ™” ๋ฐฉ์‹์€ ์กฐ์ง์˜ ๊ทผ๋ณธ์ ์ธ ๋…๋ฆฝ์„ฑ์„ ํ›ผ์†ํ•˜๊ณ  ๊ตญ๊ฐ€๋ฅผ ๋œ ์•ˆ์ „ํ•˜๊ฒŒ ๋งŒ๋“ค๊ณ  ์žˆ๋‹ค๊ณ  ์ง€์ ํ•ฉ๋‹ˆ๋‹ค. ์ด๋“ค์€ โ€œ์šฐ๋ฆฌ๊ฐ€ ๋ฌด์—‡์„ ๋†“์น˜๊ณ  ์žˆ๋Š”์ง€, ์–ด๋–ค ์œ„ํ˜‘์„ ๋ณด์ง€ ๋ชปํ•˜๋Š”์ง€ ์˜๋ฌธ์ด ๋“ ๋‹ค. ์ด ์ดํ›„์— ์–ด๋–ป๊ฒŒ ์กฐ์ง์„ ์žฌ๊ฑดํ•  ์ˆ˜ ์žˆ์„์ง€ ๋ชจ๋ฅด๊ฒ ๋‹คโ€๋ฉฐ FBI์˜ ๋ฏธ๋ž˜์— ๋Œ€ํ•œ ๊นŠ์€ ์šฐ๋ ค๋ฅผ ํ‘œํ–ˆ์Šต๋‹ˆ๋‹ค. ์นด์‰ฌ ํŒŒํ…”์˜ ๋ฆฌ๋”์‹ญ ํ•˜์— FBI๋Š” ๊ทธ ์–ด๋А ๋•Œ๋ณด๋‹ค ์ •์น˜ํ™”๋˜๊ณ  ๋ถ„์—ด๋˜์—ˆ์œผ๋ฉฐ, ๊ทธ ์—ฌํŒŒ๋Š” ์•ž์œผ๋กœ๋„ ์˜ค๋žซ๋™์•ˆ ์ง€์†๋  ๊ฒƒ์œผ๋กœ ๋ณด์ž…๋‹ˆ๋‹ค.