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Based on βHow the engineer behind Claude Cowork actually uses Claude | Felix Rieseberg (Anthropic)β from How I AI Watch the original video
Episode summary
Felix Rieseberg, an engineering lead at Anthropic, asserts that AIβs true value isnβt in automating simple cursor movements, but in handling βannoying things in the backgroundβ to liberate human creative energy. He highlights that the primary hurdle isnβt the toolsβ capabilities, but peopleβs failure to grasp that βalmost any problem can go into these tools.β Rieseberg likens the current AI landscape to a βpre-convergentβ era, much like early
Unlocking AIβs True Potential: How Anthropicβs Felix Rieseberg Builds a Life Powered by Claude
In the rapidly evolving landscape of artificial intelligence, a common pitfall is to view AI as merely a sophisticated tool for automating mundane tasks. Many see it as a glorified mouse cursor, designed to perform repetitive actions that free up a few minutes in a busy day. However, Felix Rieseberg, an engineering lead at Anthropicβthe company behind the powerful Claude AIβchampions a far more expansive vision. For Rieseberg, AI should be an invisible force, diligently handling βa bunch of annoying things in the background to free you up for your creative energy.β
This philosophy isnβt just theoretical; itβs the bedrock of how Rieseberg integrates Claude into every facet of his personal and professional life. His unique workflows and surprising applications reveal a profound truth about AI: the biggest barrier isnβt the toolsβ capabilities, but our own imagination. As Rieseberg puts it, βIt is literally people being able to understand that almost any problem can go into these tools.β
The Abstraction Advantage: From Physical Claws to Digital Promises
Riesebergβs approach to AI is defined by what he calls βstepping up in abstraction.β Instead of manually tackling a problem, he challenges Claude to solve it, then pushes further: βWhy do I need to tell Claude what kind of furniture I have? Just like you figure out what furniture I have.β This iterative process of delegating, observing, and then re-abstracting the task is key to unlocking AIβs deepest potential. The ultimate goal isnβt just to solve a problem once, but to ask, βHow will I never have to do this again?β
This mindset has led to some truly unexpected applications. Take for instance, Riesebergβs βClaude Cowork Hardware Buddy.β Picture a tiny robotic claw on a stick, equipped with Wi-Fi and Bluetooth. This isnβt just a quirky desk accessory; itβs a physical manifestation of Claudeβs capabilities. βI want my little claw to live on this thing,β Rieseberg explains, βand I wanted to cheer me on every single time I do a good job. And also every single time I need to approve something that Claude is doing, I wanted to be on this big button that is out here.β The astonishing part? Claude built all the necessary code for this hardware integration in one shot, βI needed to correct absolutely nothing.β Itβs a testament to AIβs power to bridge the digital and physical worlds, creating bespoke solutions that were once the exclusive domain of dedicated engineers.
The boundless imagination Rieseberg applies to AI is, perhaps, best exemplified by the next generation of users. His 9-year-old son, a βdaily active Claude user,β has independently delved into cybersecurity. βHeβs truly Clauding on one thing, the terminal other,β Rieseberg recounts. βHeβs like, βMom, do you know that your device ID is this?ββ This innocent fearlessness, the willingness to ask βwhat not to ask for,β highlights a generational divide. Many adults, accustomed to technologyβs limitations, are βliving in this mind prison for many years,β unaware of the vast possibilities AI now presents.
Claude Co-Work: Your Personal Problem Solver
Rieseberg relies heavily on Claude Co-work, a feature that provides Claude with its own virtual machine, essentially giving it a dedicated computer to develop software and solve problems. This capability has transformed his personal life, especially during significant transitions like moving.
When faced with a realtorβs floor plan that lacked any units, Rieseberg turned to Claude. He created a folder with all the relevant documentsβfloor plans, mortgage info, house recordsβand prompted Claude: βIn this folder you can find a floor plan. Can you figure out what the units for that floor plan are and maybe make me a new one with units?β Claude, leveraging a garage permit it found within the documents, not only determined the units but then, without explicit instruction, created an interactive 3D furniture planner. Rieseberg, a seasoned software engineer, admitted, βI have no idea how you turn like a 2D floor plan actually into a reliable 3D plan.β Claude, however, did, even peaking at the transcript and using contrast analysis to map out walls and their thickness. The result was a fully navigable 3D model where Rieseberg could move furniture around like a video game.
The utility didnβt stop there. To populate the planner with his actual belongings, Rieseberg took another leap in abstraction. Instead of manually entering furniture dimensions, he instructed Claude: βYou have access to my emails. You find all the furniture that I bought and then please like add it in here so that I can move around the furniture I actually have.β This ingenious use of email as a βsource of truth for personal inventoryβ is a game-changer, turning sprawling inboxes into structured databases. Imagine applying this to clothing, building a virtual closet from online purchase receipts, and then asking Claude for style advice or wardrobe gaps.
This βanti-to-do listβ philosophy extends to managing his commitments. Rieseberg, frequently making promises via Twitter DMs, found himself struggling to track them. His solution? He gave Claude access to his messages and tasked it with keeping a running tally of promises. Claude, without Riesebergβs oversight, created a SQL Lite database and a βmountain of text filesβ to manage this. Now, Claude occasionally reminds him: βHey, just so you know, two weeks ago you said you would do X. It is time to do X. Please go do X.β
Live Artifacts: Dynamic Data at Your Fingertips
A powerful extension of Claudeβs capabilities is βLive Artifacts.β These are dynamic file outputsβreports, dashboards, presentationsβthat automatically refresh with the latest data. Rieseberg illustrates this with the common founderβs dilemma: constantly updating pitch decks for different VCs. Instead of manual updates, an artifact can pull in live signup numbers or investor-specific data.
For a personal example, Rieseberg demonstrated a βpersonal daily dashboard.β Using Claudeβs connectors (integrations with services like Spotify, Gmail, Calendar, Notion), he prompted Claude to create a dashboard with reports and information relevant to his life, suggesting a βmodern editorial design, something calming.β The βmagic wordβ here is βlive artifact,β ensuring the output continuously pulls and reloads data.
The true power of this lies in Riesebergβs βabstractionβ principle once again. A simple morning report summarizing meetings is unimpressive; he can just check his calendar. The real value comes from asking Claude to βLook at all of my meetings I have for the day. Go figure out who Iβm meeting with. Catch me up on like the recent conversations weβve had. What were the themes there? What were the problems?β If itβs a coworker, Claude can delve into Slack history to understand their recent work and potential discussion points. This level of dynamic, contextual preparation transforms a basic summary into actionable intelligence.
Beyond practicality, Live Artifacts invite creative expression. Rieseberg playfully experimented with asking Claude to design the dashboard βlike it is software made in the early 2000s.β The result was an impeccable emulation, complete with era-appropriate copyβa testament to Claudeβs ability to interpret and execute nuanced aesthetic instructions. This opens up exciting possibilities for non-developers, imagining βsoftware written by Margaret Atwood,β where tools are shaped by the creative vision of artists and writers, not just engineers.
Beyond Capabilities: The Human Element
Riesebergβs insights extend to the very interaction model with AI. He offers a practical heuristic for choosing between Claudeβs models: the efficient Sonnet 4.6 or the more powerful Opus. For most well-defined tasks, Sonnet suffices. Opus comes into play when Rieseberg βself-identified as someone who doesnβt really know yet what theyβre asking for.β If the problem requires reinterpretation, deep conceptual understanding, or creative explorationβlike a client who doesnβt quite know what they wantβOpus is the choice.
A fascinating aspect of Riesebergβs interaction is his politeness. He consistently greets Claude with βDear Claudeβ and expresses appreciation. While acknowledging that βthe chips donβt care,β he finds it beneficial for his own βmental healthβ to maintain respectful communication. This echoes a broader sentiment among AI users: itβs not about Claudeβs humanity, but about preserving oneβs own.
Perhaps the most impactful βhumanβ insight is Riesebergβs observation that telling Claude βI know itβs possibleβ significantly boosts its confidence. When pushing the boundaries of what AI can do, acknowledging the possibility, even without knowing the how, seems to preempt Claudeβs potential βFelix, your idea is dumbβ objections and encourages it to explore solutions.
Ultimately, Rieseberg advocates for judging AI by its impact, not by the perfection of its underlying code. He doesnβt obsess over the lines of code in his furniture planner because βitβs just for me and my wife to like design our house. It will get thrown away in a month.β This liberation from traditional software developmentβs rigor allows for rapid experimentation and problem-solving, perfectly aligning with the βpreconvergentβ era of AI toolingβa time when weβre still figuring out if our βphone should be shaped like a taco or a glass pebble.β
In Felix Riesebergβs world, AI isnβt just a tool; itβs a partner in creativity, a personal assistant that handles the tedious, and a catalyst for reimagining how we interact with technology. By embracing abstraction, trusting the AI, and maintaining a mindset of limitless possibility, he demonstrates that the true power of Claudeβand AI in generalβlies not in its ability to follow commands, but in its capacity to free human ingenuity.
Based on βWhy weβre bad at being social | The Gray Areaβ from Vox Watch the original video
Episode summary
Cognitive scientist Nicholas Epley explores why humans, despite being profoundly social creatures, frequently choose to avoid social interaction, often to their own detriment. He argues that we consistently underestimate the positive outcomes of engaging with others, leading to a βtragedyβ of missed connections and unnecessary loneliness.
Epley recounts a personal βeureka momentβ on a train, observing commuters ignoring each other βlike lampshades.β He initiated a conversation with a woman in a βfabulous red hat,β expecting awkward
The Unseen Barriers to Connection: Why We Struggle to Be Social
In our quest for a good day, we often overlook a simple truth: happiness is a mosaic of meaningful moments. While we meticulously plan our careers, hobbies, and finances, vast βdead spacesβ in our daily lives often go unfilled β moments ripe for connection that we routinely let slip away. Nicholas Epley, a distinguished cognitive scientist at the University of Chicago and author, suggests that bridging these gaps with genuine human interaction is a powerful, yet surprisingly underestimated, path to well-being.
Dr. Epleyβs personal journey into this paradox began, aptly, on a train. Every morning, he commuted to the University of Chicago, observing the familiar tableau of urban solitude: a carload of South Side neighbors, many of whom had ridden together for years, sitting hip-to-hip, yet utterly ignoring each other. βWe were treating the person sitting next to us like a lampshade,β he recalls. This struck him as profoundly βweird,β especially as he was writing a chapter about humans being inherently social creatures, made happier and healthier by connection.
One morning, a woman sat next to him, professionally dressed, wearing a βfabulous red hat.β Instead of βdoom scrollingβ on his phone, Dr. Epley decided to conduct an experiment. The immediate internal resistance was immense: Sheβll think youβre a creep. If she wanted to talk, she would have. You have nothing in common. How do you even start? These familiar anxieties are the unseen prison bars that hold us back. Yet, as a scientist, βthe experiment must go on.β
Summoning his courage, he turned to her and blurted, βHi, Iβm Nick. I love your hat. I have one just like it.β He admits it wasnβt his finest opening, but it didnβt matter. She smiled, recognized his friendly intent, and they began to talk. They discussed their work, their families, and the 30 minutes of their commute evaporated. As he left, she stopped him. βThank you so much for talking with me this morning.β
What truly resonated with Dr. Epley wasnβt just that it was a nice conversation, but that it was surprisingly nice. The chasm between his pessimistic expectations and the warm reality was immense. This gap, he realized, represented a profound tragedy: if we are constantly choosing to avoid potentially meaningful and rewarding interactions, we are mistakenly holding back, missing opportunities to enrich our lives and the lives of others. This βerror that weβre making consistentlyβ could be quietly diminishing countless lives.
The Central Paradox: Why We Avoid What We Need
Dr. Epleyβs experience on the train encapsulates the central paradox of human social behavior: we are deeply social creatures, hardwired for connection, yet we repeatedly choose not to engage, even when it makes us less happy. Why?
βMost people have this expectation that if we engage with strangers, if we talk to strangers, it will make the experience worse,β Dr. Epley explains. Yet, his research consistently shows the opposite. The gap between our expectations and experiences reveals a fundamental underestimation of how positive these interactions will be. Sometimes this manifests as fear β the worry of awkwardness or rejection. Other times, itβs a subtle indifference β a belief that expressing gratitude or offering a compliment βjust wonβt make much of a difference.β Across the spectrum, the consistent finding is that reaching out on average turns out better than we anticipate.
Three Psychological Traps That Keep Us Apart
Where does this pervasive misunderstanding come from? Dr. Epley identifies three key psychological mechanisms:
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Self-Evaluation vs. Other-Evaluation: When we initiate a conversation, weβre often preoccupied with our own competency: βWhat will I say? Will I be able to carry this conversation?β We focus on how capable or effective we appear. However, the person weβre approaching is evaluating our warmth: βIs this person nice? Are they trustworthy? Are they a friend or a threat?β Social behaviors β expressing interest, offering help, giving a compliment β are inherently warm signals. Our self-focused anxiety about competency blinds us to the positive warmth we convey.
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Static Expectations vs. Dynamic Reality: Our lives, and indeed our social interactions, unfold like a movie, dynamically, reciprocally. βI say hi to you, you say hi back to me; I smile at you, you smile back at me,β Dr. Epley illustrates. This back-and-forth responsiveness is the glue of connection. Yet, our expectations are often simplified βsnapshots,β focusing on static elements like βwho am I talking to?β or βwhat will we talk about?β We fail to fully appreciate the reciprocal nature of human engagement, leading us to underestimate its positive potential.
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The Self-Fulfilling Prophecy of Pessimism: This is perhaps the cruelest social fact. Pessimism encourages avoidance. If we believe an interaction will be unpleasant, we wonβt initiate it, thus never receiving the βdataβ that might correct our mistaken belief. Optimism, conversely, is self-correcting: if we approach, we gather information that calibrates our beliefs with reality. Avoidance, however, creates a feedback loop where pessimistic beliefs remain unchallenged, preventing us from discovering potentially rewarding experiences. βYou might never find out youβre wrong,β Dr. Epley laments. This tragic cycle prevents us from living richer, more connected lives.
The Biological Imperative: Why Connection Is a Basic Need
Beyond psychological biases, our very biology screams for connection. We possess a neural reward system that encourages behaviors historically beneficial for survival. For most of human history, being alone was a death sentence. Thus, when we are isolated or feel disconnected, our brain registers it as a threat.
βWhat you get are spikes in cortisol,β Dr. Epley explains, referring to the stress hormone. Chronic cortisol compromises our immune system, making us more susceptible to illness, and negatively impacts cardiovascular functioning. This is why loneliness isnβt just an emotional state; itβs a significant risk factor for death, on par with smoking 15 cigarettes a day, and worse than not exercising or being overweight.
For too long, psychology, notably Maslowβs hierarchy of needs, treated belonging as a βluxury good.β Dr. Epley vehemently disagrees: βIt is as basic a need as eating and sleeping. And our brain and our physiological responses reflect that.β
The βHard Problemβ of Other Minds
Despite this biological imperative, social interaction remains uniquely challenging. Why is it harder to learn that weβll enjoy talking to a stranger than, say, that weβll enjoy exercising? βBecause thereβs another mind involved,β Dr. Epley states. βThatβs the challenge. Because itβs not that people misunderstand that they understand themselvesβ¦ The problem is you canβt be certain about other people.β The complexity of navigating another personβs brain exponentially increases the uncertainty.
We might enjoy a conversation with someone today, expecting a future interaction with that same person to be pleasant. But when confronted with a new stranger, or even the same person after a lapse of time, our memory of past positive experiences seems to fade. We default back to uncertainty, constantly re-evaluating the unpredictable nature of another mind.
Modern Life: A World of Choice, A Cost to Connection
While social anxiety has always existed (Stanley Milgram observed βnobody talks to each otherβ on the New York subway in the 1970s, long before smartphones), modern life amplifies the problem. Weβve built a βfrictionless worldβ where we can increasingly choose to live in isolation.
βYou can choose on any day of your life to live it completely alone if you want,β Dr. Epley points out. We can have breakfast delivered, groceries fetched, work from home, and find entertainment online, all without ever seeing another human being. This independence, while offering many benefits, comes at the steep cost of social connection, an βincreasing problem for us.β
This choice often manifests as a βsocial courage collapseβ β a split-second decision to engage or hold back. Psychologically, two independent systems in our brain are at play: one for approach, one for avoidance. At a distance, our approach motivation is high (βIβll talk to someone on my flightβ). But as we draw closer to the actual moment, our interpretation shifts, and βall the reasons to avoid it get stronger and stronger.β Confidence tanks, and we get βcold feet,β even for things we know are good for us. Our brain, tragically, confuses predictions with information: βthis will be awkwardβ becomes βthis is awkward,β making it a self-fulfilling prophecy.
The Power of Authentic Honesty
Our reluctance to connect also extends to our willingness to be truly honest. We often believe people want honesty, but when it comes to delivering potentially negative feedback, we shy away. Dr. Epley argues we underestimate how much people appreciate honesty, especially when delivered with warmth.
Honesty, he explains, has two elements: its content (positive or negative) and the warmth it conveys (friendly, helpful intent). We tend to focus on the negative content, fearing the recipientβs reaction, but overlook the profound warmth of genuine concern. For instance, if Dr. Epley were to tell an interviewer their questions were βgaseous,β it might sting initially, but if delivered with clear intent to help them improve, it could be appreciated later. βWho are the people who are truly honest with us? Itβs the people who really love us, the people who are really friends with us,β he observes.
His colleague, Emma Levine, conducted an experiment where participants spent a day being either completely honest, completely kind, or simply mindful. Participants predicted an βhonest dayβ would be worse and damage relationships compared to a βkind day.β Yet, the actual results showed that a day of complete honesty was just as good, left relationships feeling just as strong, and made participants feel more authentic.
This research offers nuance on βwhite lies.β If honesty is cruel or unhelpful, a white lie might be justified. But when honesty could be constructive β offering feedback that helps someone improve, or expressing a genuine feeling that could strengthen a relationship β withholding it is a missed opportunity.
Beyond Small Talk: Embracing Deeper Conversations
Many of us βhateβ small talk, finding it banal, phony, and inauthentic. We run the same social scripts, asking surface-level questions, and often retreat from cocktail parties to avoid it. But Dr. Epley suggests that this aversion is a shared sentiment, and an opportunity.
In experiments with MBA students, Dr. Epley pairs them up and instructs them to engage in βdeep talk,β using questions like: βIf I was going to become a good friend of yours, what would be most important for me to know about you?β or βCan you tell me about one of the last times you cried in front of another person?β
The initial reaction is palpable: βItβs like somebody just pulls all the air out of the room.β Students expect awkwardness, dislike, and little in common. Yet, after the conversation, they overwhelmingly report it went βbetter than they thought.β It was less awkward, they formed stronger bonds, liked the person more, and found more in common. The challenge then, Epley jokes, is βgetting them back.β
People crave deeper conversations than they typically have. The power to change a conversation from superficial to meaningful lies with us. By signaling an interest in genuine connection, we invite others to reciprocate, leading to richer, more satisfying interactions.
Breaking the Chains of Avoidance
Dr. Epley admits this research profoundly changed him, more than any other heβs undertaken. Despite often being perceived as extroverted, he identifies as an introvert. His work helped him recognize the βmistaken opportunitiesβ in his own life β the people he could have connected with, the help he could have offered or received, but didnβt.
Loneliness and excessive social anxiety are especially cruel because they feed on themselves. But Dr. Epley offers a hopeful message: the βprison bars that hold us back from other people sometimes are actually wet pasta noodles.β If we dare to test them, to push on them a little, we might find that our fears are exaggerated, and a world of richer, more meaningful connections awaits. The tragedy of avoidance doesnβt have to define our lives. We have the power to choose connection, and in doing so, unlock a deeper sense of happiness and belonging.
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ν΄λ‘λ μμ§λμ΄λ ν΄λ‘λλ₯Ό μ΄λ»κ² μΈκΉ? μ°½μλ ₯μ ν΄λ°©νλ AI νμ©μ λΉλ°
AIλ λ μ΄μ λ¨μν μλνλ₯Ό λμ΄ μΈκ°μ μ°½μλ ₯μ ν΄λ°©νκ³ , 볡μ‘ν λ¬Έμ ν΄κ²°μ μλ‘μ΄ μ§νμ μ΄κ³ μμ΅λλ€. μ€νΈλ‘ν½(Anthropic)μμ ν΄λ‘λ(Claude) μ ν κ°λ°μ μ΄λλ μμ§λμ΄λ§ 리λ ν λ¦μ€ 리μ€λ²κ·Έ(Felix Rieseberg)λ μ΄λ¬ν AIμ μ μ¬λ ₯μ κ°μ₯ κΉμ΄ μ΄ν΄νκ³ νμ©νλ μΈλ¬Ό μ€ ν λͺ μ λλ€. κ·Έλ ν΄λ‘λλ₯Ό λ¨μν λκ΅¬κ° μλ, λ§μΉ μ λ₯ν λλ£μ²λΌ νμ©νλ©° μΌμκ³Ό μ 무μ ν¨μ¨μ κ·Ήλνν©λλ€.
μ΄ κΈ°μ¬λ ν λ¦μ€ 리μ€λ²κ·Έμ λ νΉν ν΄λ‘λ νμ©λ²μ ν΅ν΄, μ°λ¦¬κ° AIλ₯Ό λ°λΌλ³΄λ κ΄μ κ³Ό νμ© λ°©μμ λν κΉμ ν΅μ°°μ μ 곡ν κ²μ λλ€. κ·Έλ λ¨λ 20λ¬λ¬λ‘ μμ λ§μ νλμ¨μ΄ ν΄λ‘λ λ²λλ₯Ό λ§λλ λ°©λ²λΆν°, μ΄λ©μΌμ νμ©ν κ°μΈ λΉμ, κ·Έλ¦¬κ³ μλ μ λ°μ΄νΈλλ λμ보λμΈ βλΌμ΄λΈ μν°ν©νΈ(Live Artifacts)βμ μ΄λ₯΄κΈ°κΉμ§, ν΄λ‘λκ° βκ±°μ λͺ¨λ λ¬Έμ βλ₯Ό ν΄κ²°ν μ μλ€λ κ²μ λͺΈμ 보μ¬μ€λλ€.
AI, λ§μ°μ€ 컀μ κ·Έ μ΄μ: μ°½μλ ₯μ μν λꡬ
ν λ¦μ€ 리μ€λ²κ·Έλ AIμ μ§μ ν κ°μΉκ° βλ¨μν λ§μ°μ€ 컀μλ₯Ό μμ§μ΄λ κ²βμ λμ΄μ λ€κ³ κ°μ‘°ν©λλ€. κ·Έμκ² AIλ βμ§μ¦ λλ μΌλ€μ λ°°κ²½μμ μ²λ¦¬νμ¬ λΉμ μ μ°½μμ μΈ μλμ§λ₯Ό ν΄λ°©μμΌμ£Όλβ λꡬμ λλ€. κ·Έκ° λͺ©κ²©νλ κ°μ₯ ν° κ²©μ°¨λ AI λꡬμ λ₯λ ₯ μμ²΄κ° μλλΌ, βκ±°μ λͺ¨λ λ¬Έμ λ₯Ό μ΄λ¬ν λꡬμ λ§‘κΈΈ μ μλ€λ κ²μ μ¬λλ€μ΄ μ΄ν΄νλ λ₯λ ₯βμ μλ€κ³ λ§ν©λλ€.
νμ¬ ν λ¦μ€λ ν΄λ‘λ μ½μν¬(Claude Co-work), ν΄λ‘λ μ½λ(Claude Code), ν΄λ‘λ ν¬ ν¬λ‘¬(Claude for Chrome), κ·Έλ¦¬κ³ macOS λ° Windowsμ© ν΄λ‘λ λ°μ€ν¬ν± μ ν리μΌμ΄μ λ± μ€νΈλ‘ν½μ μ£Όμ ν΄λ‘λ μ ν κ°λ°μ μ΄λλ μμ§λμ΄λ§ 리λμ λλ€. κ·Έλ νμ¬μ AI νκ²½μ λ§μΉ βν΄λν°μ΄ μ‘°μ½λ λͺ¨μμ΄μ΄μΌ ν κΉ, νμ½ λͺ¨μμ΄μ΄μΌ ν κΉ, 립μ€ν± λͺ¨μμ΄μ΄μΌ ν κΉβλ₯Ό κ³ λ―Όνλ μ΄κΈ° μ€λ§νΈν° μμ₯μ λΉμ ν©λλ€. λ€μν ννμ μ§μ μ μ΄ μ‘΄μ¬νλ μ΄ μμ μμ, μ¬μ©μλ€μ μμ μ νμμ λ§λ μ΅μ μ ν΄λ‘λ μ¬μ© λ°©μμ μ νν μ μμ΅λλ€. ν λ¦μ€λ μ΄λ¬ν μ νμ μμ κ° μ΄κΈ° λ¨κ³μμλ μ€μνμ§λ§, κΆκ·Ήμ μΌλ‘λ β무μμ νλ ν κ³³μμ λͺ¨λ κ²μ μ²λ¦¬ν μ μλβ ν΅ν©λ κ²½νμΌλ‘ λμκ° κ²μ΄λΌκ³ λ΄λ€λ΄ λλ€.
ν΄λ‘λ νμ©μ μ μ: λ¬Έμ ν΄κ²°μ μ°½μμ μ κ·Ό
ν λ¦μ€λ ν΄λ‘λλ₯Ό μ¬μ©νλ μ¬λλ€μ 보며, λͺ¨λΈμ κΈ°μ μ λ₯λ ₯보λ€λ βμμ μ ꡬ쑰ννκ³ μμ΄λμ΄λ₯Ό λ μ¬λ¦¬λ μ°½μμ±βμ λ κΉμ μΈμμ λ°λλ€κ³ λ§ν©λλ€. κ·Έμ ν΄λ‘λ νμ© μ¬λ‘λ€μ μ΄λ¬ν μ°½μμ μ κ·Όμ΄ μ΄λ»κ² μΌμκ³Ό μ 무μ ν¨μ¨μ νμ ν μ μλμ§ λ³΄μ¬μ€λλ€.
μ΄μ¬ κ³ν λμ°λ―Έ β 3D κ°κ΅¬ νλλ
μ΅κ·Ό μ΄μ¬λ₯Ό μ€λΉνλ©° ν λ¦μ€λ ν΄λ‘λ μ½μν¬λ₯Ό νμ©ν΄ λλΌμ΄ κ°μΈ λΉμλ₯Ό λ§λ€μμ΅λλ€. λΆλμ° νμ¬μμ λ°μ νλ©΄λμλ λ¨μ(μ: νΌνΈ, λ―Έν°)κ° νμλμ΄ μμ§ μμμ΅λλ€. κ·Έλ ν΄λ‘λμκ² μ΄ νλ©΄λλ₯Ό λΆμνμ¬ λ¨μλ₯Ό νμ νκ³ , λ¨μλ₯Ό ν¬ν¨ν μλ‘μ΄ νλ©΄λλ₯Ό λ§λ€μ΄ λ¬λΌκ³ μμ²νμ΅λλ€. μ¬κΈ°μ ν λ¦μ€λ μ€νΈμ€(Opus) λͺ¨λΈ λμ μλ€νΈ(Sonnet) λͺ¨λΈμ μ¬μ©νλλ°, μ΄λ μ΄ μμ μ΄ βλͺ¨λΈμ΄ μμ£Ό λλν νμκ° μλβ μ μ μλ(well-scoped) λ¬Έμ μκΈ° λλ¬Έμ λλ€.
μ€νΈμ€ vs. μλ€νΈ: λͺ¨λΈ μ νμ μ§ν ν λ¦μ€λ μ€νΈμ€μ μλ€νΈ μ€ μ΄λ€ λͺ¨λΈμ μ νν μ§ κ²°μ νλ μμ λ§μ κΈ°μ€μ κ°μ§κ³ μμ΅λλ€. λλΆλΆμ μΌμμ μΈ μμ μλ μλ€νΈ 46(Sonnet 46)μΌλ‘ μΆ©λΆνλ©°, κ·Έ νκ³μ λΆλͺνλ κ²½μ°λ λλ¬Όλ€κ³ ν©λλ€. κ·Έμ κ²°μ κΈ°μ€μ βλͺ¨λΈμ΄ μ€μ λ¬Έμ λ₯Ό μΌλ§λ μ ννκ² νμ νλμ§μ λν λμ κ΄μ©λβμ λλ€.
- μλ€νΈ(Sonnet): μ¬μ©μκ° βμμ£Ό λͺ ννκ² μ μλ λ¬Έμ βλ₯Ό κ°μ§κ³ μμ λ μ ν©ν©λλ€. μλ₯Ό λ€μ΄, βνλ©΄λμ λ¨μκ° νμνλ€βλ λͺ νν μμ²μ²λΌ, λͺ¨λΈμ΄ μ§λ¬Έμ μ¬ν΄μν νμ μμ΄ λ°λ‘ μ€νν μ μλ κ²½μ°μ λλ€.
- μ€νΈμ€(Opus): μ¬μ©μκ° βμμ§ μμ μ΄ λ¬΄μμ λ¬»κ³ μλμ§ μ λͺ¨λ₯Ό λβ μ¬μ©ν©λλ€. λ³νΈμ¬, νκ³μ¬, μμ¬, λλ ν¬λ¦¬μμ΄ν°λΈ μ λ¬Έκ°μ²λΌ, κ³ κ°μ΄ λμ§λ μ§λ¬Έμ μ΄λ©΄μ μλ μ§μ§ μλλ₯Ό νμ νκ³ μ¬ν΄μνλ λ₯λ ₯μ΄ νμν 볡μ‘νκ³ λͺ¨νΈν λ¬Έμ μ λ μ ν©ν©λλ€.
ν΄λ‘λλ νλ©΄λμ λ¨μλ₯Ό μΆκ°ν ν, ν λ¦μ€μκ² βμ΄μ λ¨μκ° μλ νλ©΄λκ° μμΌλ, μΈν λ¦¬μ΄ λμμΈ μμλ₯Ό λ§λ€μ΄ μ€κΉ? μΉ¨λλ μ΄λμ, μκΈ°λ°©μ μ΄λμ λλ©΄ μ’μκΉ?βλΌκ³ λ¬Όμμ΅λλ€. ν λ¦μ€λ μ΄ κ³Όμ μμ βμΈν°λν°λΈ νλλκ° νμν΄. κ°κ΅¬λ₯Ό λ§μλλ‘ μμ§μΌ μ μκ² ν΄μ€βλΌκ³ μμ²νμ΅λλ€.
λλκ²λ ν΄λ‘λλ νμ΄μ¬(Python)μ μ¬μ©νμ¬ μ΄ λͺ¨λ κ²μ ꡬννμ΅λλ€. ν΄λ‘λ μ½μν¬λ ν΄λ‘λμκ² μ체 κ°μ λ¨Έμ (Virtual Machine)μ μ 곡νμ¬, λ¬Έμ ν΄κ²°μ νμν μννΈμ¨μ΄λ₯Ό μ€μ€λ‘ κ°λ°ν μ μκ² ν©λλ€. ν΄λ‘λλ 2D νλ©΄λλ₯Ό 3D λͺ¨λΈλ‘ λΆμνκ³ λ³νν ν, μ¬μ©μκ° κ°κ΅¬λ₯Ό 3D 곡κ°μμ μμ λ‘κ² μμ§μΌ μ μλ μΈν°λν°λΈ νλλλ₯Ό λ§λ€μ΄λμ΅λλ€. ν λ¦μ€λ μμ μ΄ 2D νλ©΄λλ₯Ό 3Dλ‘ λ³ννλ λ°©λ²μ μ ν λͺ°λμμλ ν΄λ‘λκ° μ΄λ₯Ό μλ²½νκ² ν΄λλ€λ μ¬μ€μ κΉμ μΈμμ λ°μμ΅λλ€.
μ¬κΈ°μ ν΅μ¬μ **βλ§₯λ½(Context)β**μ μ€μμ±μ λλ€. ν λ¦μ€λ ν΄λ‘λμκ² μμ μ μ΄λ©μΌ μ κ·Ό κΆνμ λΆμ¬νμ¬, κ³Όκ±°μ ꡬ맀νλ κ°κ΅¬ λͺ©λ‘κ³Ό μΉμλ₯Ό μ΄λ©μΌμμ μλμΌλ‘ μ°Ύμ νλλμ μΆκ°νλλ‘ νμ΅λλ€. μ΄λ©μΌμ κ°μΈμ μΈ βμ§μ€μ μμ²(Source of Truth)βμΌλ‘ νμ©νμ¬, μλ§μ ꡬ맀 λ΄μ μμμ νμν μ 보λ₯Ό μΆμΆν΄λΈ κ²μ λλ€. μ΄λ μλμΌλ‘ κ°κ΅¬ λͺ©λ‘μ μμ±νκ³ μΉμλ₯Ό μ¬λ κ³Όκ±°μ λ²κ±°λ‘μμ μμ ν ν΄μνμ΅λλ€. ν λ¦μ€λ μ΄ μμ΄λμ΄λ₯Ό νμ₯νμ¬ μ΄λ©μΌμμ μ· κ΅¬λ§€ λ΄μμ μΆμΆν΄ βκ°μ μ·μ₯βμ λ§λ€κ³ , ν΄λ‘λλ‘λΆν° μ€νμΌ μ‘°μΈμ μ»λ κ²λ κ°λ₯ν κ²μ΄λΌκ³ μΈκΈνμ΅λλ€.
μ΄λ¬ν μ κ·Ό λ°©μμ **βμΆμν κ³μΈ΅(Abstraction Layer)μ λμ΄λ κ²β**μΌλ‘ μ΄μ΄μ§λλ€. ν λ¦μ€λ μλμΌλ‘ κ°κ΅¬ μ 보λ₯Ό μ λ ₯νλ€κ° βλ΄κ° μ μ΄κ±Έ νκ³ μμ§? ν΄λ‘λμκ² κ·Έλ₯ μ΄ κ°κ΅¬κ° μλ€κ³ λ§νλ©΄ λμμβλΌκ³ μκ°νκ³ , λ€μ ν λ² βλ΄κ° μ ν΄λ‘λμκ² κ°κ΅¬λ₯Ό μλ €μ€μΌ νμ§? ν΄λ‘λκ° μμμ μ°Ύκ² νλ©΄ λμμβλΌκ³ μκ°νμ΅λλ€. μ΄μ²λΌ βν΄λ‘λκ° μ΄λ»κ² μ΄ μΌμ ν μ μμκΉ?β, βμ΄λ»κ² νλ©΄ μ΄ μΌμ λ€μλ νμ§ μμ μ μμκΉ?βλ₯Ό κ³μν΄μ μ§λ¬Ένλ©° μμ μ μΆμν κ³μΈ΅μ λμ΄λ κ²μ΄ AI νμ©μ ν΅μ¬μ΄λΌκ³ κ·Έλ κ°μ‘°ν©λλ€.
μ½μ μΆμ κΈ° (Promise Tracker)
ν λ¦μ€λ νΈμν°λ₯Ό ν΅ν΄ μλ§μ μ¬λλ€κ³Ό μν΅νλ©° μ½μμ μ£Όκ³ λ°λ κ³Όμ μμ, μ΄ μ½μλ€μ μΆμ νλ λ° μ΄λ €μμ κ²ͺμμ΅λλ€. κ·Έλ μ΄ λ¬Έμ λ₯Ό ν΄λ‘λμκ² λ§‘κ²Όμ΅λλ€. βν΄λ‘λ, λ΄ λͺ¨λ λ©μμ§λ₯Ό μ½κ³ λ΄κ° ν λͺ¨λ μ½μμ μΆμ ν΄μ€. κ·Έλ¦¬κ³ λ§€λ² λ©μμ§λ₯Ό λ€μ μ½μ§ μκ³ λ μ΄κ±Έ ν μ μλ λ°©λ²μ μ°Ύμμ€.β
ν΄λ‘λλ μ΄ μμ²μ μλ²½νκ² μννμ΅λλ€. ν λ¦μ€λ ν΄λ‘λκ° SQLite λ°μ΄ν°λ² μ΄μ€μ μλ§μ ν μ€νΈ νμΌλ‘ μ½μμ κ΄λ¦¬νλ κ²μΌλ‘ μΆμ νμ§λ§, μ€μ λ΄λΆ ꡬν λ°©μμλ ν¬κ² μ κ²½ μ°μ§ μμ΅λλ€. μ€μν κ²μ ν΄λ‘λκ° κ°λ β2μ£Ό μ μ Xλ₯Ό νκΈ°λ‘ μ½μνμ ¨μ΅λλ€. μ΄μ Xλ₯Ό ν μκ°μ λλ€. Xλ₯Ό ν΄μ£ΌμΈμ.βλΌκ³ μκΈ°μμΌμ£Όλ βμν₯(impact)βμ λλ€. κ·Έλ ν΄λ‘λμ λ΄λΆ μλ λ°©μμ μ§λμΉκ² κ°μν기보λ€, μ΅μ’ κ²°κ³Όμ μν₯μ μ§μ€νλ κ²μ΄ μ€μνλ€κ³ λ§ν©λλ€. μ΄λ μ°λ¦¬κ° AIλ₯Ό βκ°λ βνλ λ°©μμμ βνλ ₯βνλ λ°©μμΌλ‘ μ νν΄μΌ ν¨μ μμ¬ν©λλ€.
λΌμ΄λΈ μν°ν©νΈ: μλ μ λ°μ΄νΈλλ κ°μΈ λ§μΆ€ν λμ보λ
ν΄λ‘λμ βμν°ν©νΈ(Artifact)βλ μ¬μ©μκ° μμ ν κ²°κ³Όλ¬Όμ νμΌ ννλ‘ μΆλ ₯νλ κ²μ μλ―Έν©λλ€. λ³΄κ³ μ, λμ보λ, νλ μ ν μ΄μ , ν λ¦μ€μ 3D κ°κ΅¬ νλλ λ±μ΄ μν°ν©νΈμ μμμ λλ€. μ¬κΈ°μ ν λ¨κ³ λ λμκ° κ²μ΄ λ°λ‘ **βλΌμ΄λΈ μν°ν©νΈ(Live Artifacts)β**μ λλ€. λΌμ΄λΈ μν°ν©νΈλ μ΅μ λ°μ΄ν°λ₯Ό κΈ°λ°μΌλ‘ μ€μ€λ‘ μλ‘κ³ μΉ¨λκ³ μ λ°μ΄νΈλλ μν°ν©νΈλ₯Ό λ§ν©λλ€.
ν λ¦μ€λ μ€ννΈμ μ°½μ κ°λ€μ΄ ν¬μμλ₯Ό μν΄ μμ κ°μ νΌμΉ λ±μ λ§λ€κ³ , λ§€μ£Ό λ°μ΄ν°λ₯Ό μ λ°μ΄νΈνλ λ²κ±°λ‘μμ μ£Όλͺ©νμ΅λλ€. λΌμ΄λΈ μν°ν©νΈλ μ΄λ¬ν ν΅μ¬ μμ΄λμ΄λ₯Ό μ μ§νλ©΄μλ, λμκ³Ό μ΅μ λ°μ΄ν°μ λ§μΆ° μλμΌλ‘ μ λ°μ΄νΈλλ μ루μ μ μ 곡ν©λλ€.
ν λ¦μ€λ βκ°μΈ μΌμΌ λμ보λβλ₯Ό μμλ‘ λ€μ΄ λΌμ΄λΈ μν°ν©νΈμ κ°λ ₯ν¨μ μμ°νμ΅λλ€. κ·Έλ ν΄λ‘λμκ² βλ΄ λ€μν λ°μ΄ν° μμ€(Spotify, Gmail, Calendar, Notion λ±)μμ κ΄λ ¨ μ 보λ₯Ό ν¬ν¨νλ κ°μΈ μΌμΌ λμ보λλ₯Ό λ§λ€μ΄μ€. νλμ μΈ νΈμ§ λμμΈμΌλ‘ μ°¨λΆνκ² λ§λ€μ΄μ€. κ·Έλ¦¬κ³ βλΌμ΄λΈ μν°ν©νΈβλ‘ λ§λ€μ΄μ€.βλΌκ³ μμ²νμ΅λλ€. μ¬κΈ°μ βλΌμ΄λΈ μν°ν©νΈβλ ν΄λ‘λμκ² μλ μ λ°μ΄νΈ κΈ°λ₯μ νμ±ννλλ‘ μ§μνλ βλ§λ²μ λ¨μ΄βμ κ°μ΅λλ€.
ν΄λ‘λλ μ¦μμμ νλμ μ΄κ³ μ°¨λΆν λμμΈμ κ°μΈ λμ보λλ₯Ό μμ±νμ΅λλ€. μ΄ λμ보λλ μλ¨μ μλ‘κ³ μΉ¨ λ²νΌμ ν΅ν΄ μΈμ λ μ§ μ΅μ λ°μ΄ν°λ₯Ό λΆλ¬μ¬ μ μμ΅λλ€. νΉν μ£Όλͺ©ν μ μ ν΄λ‘λκ° **β컀λ₯ν°(Connectors)β**λ₯Ό ν΅ν΄ λ€μν μΈλΆ μλΉμ€μ μ°λλλ€λ κ²μ λλ€. μ€ν¬ν°νμ΄, μ§λ©μΌ, μΊλ¦°λ, λ Έμ λ± λ€μν 컀λ₯ν°κ° μ 곡λλ©°, μ¬μ©μλ API ν€λ₯Ό λ³λλ‘ μ λ ₯ν νμ μμ΄ OAuth μΈμ¦μ ν΅ν΄ μμ½κ² μ°κ²°ν μ μμ΅λλ€. ν λ¦μ€λ μ΄λ₯Ό ν΅ν΄ λ¨μν μ€λμ νμ λͺ©λ‘μ 보μ¬μ£Όλ κ²μ λμ΄, κ° νμ μ°Έμμμμ μ΅κ·Ό λν, κ·Έλ€μ΄ μμ μ€μΈ λ΄μ©, λ Όμν μ μλ μ£Όμ λ±μ μ¬λ(Slack)μ΄λ λ€λ₯Έ μμ€μμ κ°μ Έμ νμ μ€λΉλ₯Ό κ·Ήλνν μ μλ€κ³ μ€λͺ ν©λλ€. μ΄λ μ 보λ₯Ό λ¨μν μμ½νλ κ²μ λμ΄, **βλ§₯λ½μ μ΄ν΄λ₯Ό ν΅ν μ¬μΈ΅μ μΈ μ€λΉβ**λ₯Ό κ°λ₯νκ² ν©λλ€.
ν΄λ‘λμμ λνλ²: AIλ₯Ό μμ§μ΄λ βλ―Ώμβκ³Ό βκ°λ₯μ±β
ν λ¦μ€μ μ§νμ ν΄λΌλ₯΄λ³΄λ ν΄λ‘λμ λννλ λ°©μμ λν΄μλ ν₯λ―Έλ‘μ΄ ν΅μ°°μ 곡μ ν©λλ€. ν λ¦μ€λ νμ ν΄λ‘λμκ² βμΉμ νλ ν΄λ‘λβ λλ βμλ μΉκ΅¬βμ κ°μ΄ μ μ€νκ² μΈμ¬νλ€κ³ ν©λλ€. μ΄λ ν΄λ‘λμ μΈκ°μ± λλ¬Έμ΄ μλλΌ, βλ μμ μ μ μ 건κ°μ μν΄ λͺ¨λ κ²κ³Όμ μν΅μμ μ μ€νκ³ μΉμ ν νλλ₯Ό μ μ§νλ κ²μ΄ μ’λ€βλ μ² ν λλ¬Έμ λλ€. ν΄λΌλ₯΄λ³΄ μμ βν΄λ‘λμ μΈκ°μ±μ΄ μλ λμ μΈκ°μ±μ μν κ²βμ΄λΌλ©° μ΄μ λμν©λλ€.
λ λμκ° ν λ¦μ€λ ν΄λ‘λμκ² **βμ΄κ²μ κ°λ₯νλ©°, λλ κ·Έκ²μ΄ κ°λ₯νλ€λ κ²μ μλ€β**λΌκ³ λ§νλ κ²μ΄ μ€μνλ€κ³ μ‘°μΈν©λλ€. μ΄λ ν΄λ‘λμκ² μμ κ°μ λΆμ΄λ£μ΄ μ£Όμ΄μ§ μμ μ λμ± μ κ·Ήμ μΌλ‘ μννκ² λ§λ€κ³ , βν λ¦μ€, λΉμ μ μμ΄λμ΄λ μ΄λ¦¬μμΌλ νμ§ λ§μμΌ ν©λλ€βμ κ°μ λΆνμν λνλ₯Ό μ¬μ μ μ°¨λ¨νλ ν¨κ³Όκ° μμ΅λλ€. κ·Έλ μμ μ΄ βμμ μ μΈ μλμμ μμ§λ§, μ΄μ¨λ κ³μν΄λ¬λΌβκ³ λ§νλ©° ν΄λ‘λμ μ°½μμ νμμ μ₯λ €νλ€κ³ λ§λΆμ λλ€.
μ΄λ¬ν AIμμ λν λ°©μμ μννΈμ¨μ΄ κ°λ°μκ° μλ μ¬λλ€μκ²λ κ°λ ₯ν λꡬ μ μμ λ¬Έμ μ΄μ΄μ€λλ€. ν λ¦μ€λ μ λͺ μκ° λ§κ°λ μ νΈμ°λ(Margaret Atwood)κ° ν΄λ‘λλ₯Ό μ¬μ©νλ€λ μμμ λ£κ³ βλ§κ°λ μ νΈμ°λκ° μ΄ μννΈμ¨μ΄λ₯Ό λ³΄κ³ μΆλ€βκ³ λ§νμ΅λλ€. μ΄λ μ λ¬Έ κ°λ°μκ° μλλλΌλ λꡬλ μμ μ λΉμ μ λ§λ λꡬλ₯Ό λ§λ€ μ μλ μλκ° μμμ μλ―Έν©λλ€.
κ²°λ‘ : AI μλ, λ¬Έμ ν΄κ²°μ μλ‘μ΄ μ§ν
ν λ¦μ€ 리μ€λ²κ·Έμ ν΄λ‘λ νμ© μ¬λ‘λ€μ AIκ° λ¨μν μμ°μ± λꡬλ₯Ό λμ΄, μΈκ°μ μ°½μμ±μ μ¦νμν€κ³ λ¬Έμ ν΄κ²° λ°©μμ κ·Όλ³Έμ μΌλ‘ λ³νμν¬ μ μμμ λͺ νν 보μ¬μ€λλ€. κ·Έκ° μ μνλ ν΅μ¬ λ©μμ§λ λͺ νν©λλ€. βAIμ κ°μ₯ ν° μ μ¬λ ₯μ λꡬμ λ₯λ ₯μ μλ κ²μ΄ μλλΌ, κ±°μ λͺ¨λ λ¬Έμ λ₯Ό AIμ λ§‘κΈΈ μ μλ€λ μ¬μ©μλ€μ μΈμκ³Ό μμλ ₯μ μλ€βλ κ²μ λλ€.
ν΄λ‘λλ₯Ό νμ©ν 3D κ°κ΅¬ νλλ, μ½μ μΆμ κΈ°, κ·Έλ¦¬κ³ λΌμ΄λΈ μν°ν©νΈ λμ보λμ κ°μ μ¬λ‘λ€μ AIκ° κ°μΈμ μΆκ³Ό μ 무μ μΌλ§λ κΉμμ΄ ν΅ν©λμ΄, λ²κ±°λ‘μ΄ μμ μ μλννκ³ λ μ€μν μΌμ μ§μ€ν μ μλλ‘ λλμ§λ₯Ό 보μ¬μ€λλ€. νΉν βμΆμν κ³μΈ΅μ λμ΄λ μ§λ¬Έβκ³Ό βAIμ λν λ―Ώμκ³Ό κ°λ₯μ±μ μ μνλ λνλ²βμ AIλ₯Ό λ¨μν λͺ λ Ή μνμκ° μλ, μ°½μμ μΈ νλ ₯μλ‘ νμ©νλ ν΅μ¬ μ΄μ κ° λ κ²μ λλ€.
μ°λ¦¬λ μ§κΈ AI μΈν°νμ΄μ€μ νμ© λ°©μμ΄ λμμμ΄ μ€νλκ³ μ§ννλ ν₯λ―Έλ‘μ΄ μλλ₯Ό μ΄κ³ μμ΅λλ€. ν λ¦μ€ 리μ€λ²κ·Έμ μ¬λ‘λ μ΄λ¬ν λ³νμ μ λμ μμ, AIμ ν¨κ» λ λμ λ―Έλλ₯Ό ꡬμΆνλ €λ λͺ¨λ μ΄λ€μκ² μκ°μ μ€λλ€. μ΄μ λΉμ μ μ°¨λ‘μ λλ€. ν΄λ‘λλ₯Ό ν΅ν΄ βκ±°μ λͺ¨λ λ¬Έμ βλ₯Ό ν΄κ²°νκ³ , λΉμ μ μ°½μλ ₯μ λ§μκ» νΌμ³λ³΄μΈμ.
βWhy weβre bad at being social | The Gray Areaβ β Vox κΈ°λ° κΈ°μ¬ μλ³Έ μμ 보기
μνΌμλ μμ½
μΈκ°μ λ³Έμ§μ μΌλ‘ μ¬νμ μ‘΄μ¬μμλ λΆκ΅¬νκ³ , λ―μ μ¬λκ³Όμ κ΅λ₯λ₯Ό νΌνλ©° μ€μ€λ‘ λΆνμ μ ννλ μμ€μ μΈ κ²½ν₯μ 보μΈλ€. μΈμ§κ³Όνμ λμ½λΌμ€ μν리(Nicholas Epley)λ μ΄ νμμ΄ μ°λ¦¬κ° μ¬νμ μνΈμμ©μ κΈμ μ μΈ κ²°κ³Όλ₯Ό κΎΈμ€ν κ³Όμνκ°νκΈ° λλ¬Έμ΄λΌκ³ μ£Όμ₯νλ€. κ·Έλ λ§€μΌ μμΉ¨ κΈ°μ°¨μμ μ¬λλ€μ΄ μλ‘λ₯Ό βλ¨ν κ°βμ²λΌ 무μνλ λͺ¨μ΅μ 보λ€κ°, μμ λ λͺ¨λ₯΄λ μ¬μ΄μ λ―μ μ¬μ±μκ² λ§μ κ±Έμλ κ²½νμ μλ‘ λ λ€. μ²μμλ μλλ°©μ΄ μμ μ μ΄μνκ² λ³΄κ±°λ λνκ° μ΄μν κ²μ΄λΌλ μ¨κ° λΆμ μ μΈ μμμ νμ§λ§, μ€μ λνλ βλλλλ‘ μ¦κ±°μ κ³ β μ¬μ± λν κ³ λ§μμ ννλ€. μν리λ μ΄λ¬ν βμμκ³Ό κ²½ν μ¬μ΄μ μμ²λ κ°κ·Ήβμ΄ μ°λ¦¬κ° μλ―Έ μκ³ λ³΄λ μλ κ΄κ³λ₯Ό λμΉκ² λ§λλ λΉκ·Ήμ΄λΌκ³ μ§μ νλ€.
μ΄λ¬ν κ³Όμνκ°λ ν¬κ² μΈ κ°μ§ μμΈμμ λΉλ‘―λλ€. 첫째, μ°λ¦¬λ λν λ₯λ ₯ λ± μμ μ βμλ(competency)βμ μ§μ€νλ λ°λ©΄, μλλ°©μ μ°λ¦¬μ βλ°λ»ν¨(warmth)β(μΉμ ν¨, μ λ’°μ±)μ νκ°νλ€λ μ μ΄λ€. μ¬νμ νλμ λ³Έμ§μ μΌλ‘ λ°λ»ν¨μ λ΄ν¬νκ³ μμ΄ μλλ°©μκ² κΈμ μ μΌλ‘ λΉμΉλ€. λμ§Έ, μ°λ¦¬μ κΈ°λλ μνΈμμ©μ μλμ μΈ βμνβ κ°μ λ³Έμ§μ ν¬μ°©νμ§ λͺ»νκ³ μ μ μΈ βμ¬μ§βμ²λΌ λ¨μνλμ΄, λνμ ν΅μ¬μΈ μνΈ λ°μμ±μ κ°κ³Όνλ€. μ μ§Έ, λΉκ΄μ£Όμλ ννΌλ₯Ό μ‘°μ₯νμ¬ μ€μ€λ‘λ₯Ό κ°ννλ€. λνκ° λΆμΎν κ²μ΄λΌκ³ μκ°νλ©΄ μλμ‘°μ°¨ νμ§ μμ, μμ μ λΉκ΄μ μΈ μμΈ‘μ΄ νλ Έμμ νμΈν κΈ°νλ₯Ό μμν μ»μ§ λͺ»νλ€. λ°λ©΄ λκ΄μ£Όμλ μλλ₯Ό ν΅ν΄ νμ€κ³Ό μΌμΉνλλ‘ μμ λ μ μλ€. λν, μ¬νμ μ°κ²°μ μΈκ°μ κΈ°λ³Έμ μΈ μꡬμ΄λ©°, κ³ λ¦½μ λμ μνμΌλ‘ μΈμλμ΄ μ€νΈλ μ€ νΈλ₯΄λͺ¬ μ½λ₯΄ν°μ(cortisol) μμΉλ₯Ό λμ΄κ³ λ©΄μ 체κ³μ μ¬νκ΄ κΈ°λ₯μ μ μν₯μ λ―ΈμΉλ€. μν μ‘°μ¬μ λ°λ₯΄λ©΄ μΈλ‘μμ ν루 15κ°λΉμ λ΄λ°°λ₯Ό νΌμ°λ κ²κ³Ό λ§λ¨Ήλ μ¬λ§ μν μμλ‘, μ΄λ λΆμ‘±μ΄λ 과체μ€λ³΄λ€λ μ¬κ°νλ€.
λ¬Όλ‘ λͺ¨λ μ¬νμ μνΈμμ©μ΄ νμ μ±κ³΅μ μΈ κ²μ μλλ©°, λλ‘λ νΌμλ§μ μκ°μ΄ νμν μλ μλ€. νμ§λ§ μν리λ μ°λ¦¬κ° κΈμ μ μΈ κ²°κ³Όκ° λμ¬ νλ₯ μ μλͺ» κ³μ°νκ³ μλ€κ³ κ°μ‘°νλ€. νλ μ¬νλ λ°°λ¬ μλΉμ€λ μ¬ν근무 λ±μΌλ‘ νμΈκ³Όμ μ μ΄ μμ΄λ μνν μ μλ μ νμ§κ° λμ΄λλ©΄μ, μ΄λ¬ν μ νμ κ³ λ¦½μ΄ μ¬νμ μ°κ²°μ λΉμ©μΌλ‘ μμ©νκ³ μλ€. λν, λ©λ¦¬μ λ³Ό λλ μ¬νμ νλμ΄ λ§€λ ₯μ μΌλ‘ λκ»΄μ§μ§λ§, μ€μ νλμ μκ°μ΄ λ€κ°μ¬μλ‘ ννΌ λκΈ°κ° κΈμ¦νλ©° μμ κ°μ κΈλ½νλ βμ¬νμ μ©κΈ°
ν볡μ λμΉλ μ΅κ΄: μ°λ¦¬λ μ μ¬νμ κ΅λ₯λ₯Ό μ£Όμ ν κΉ?
μ°λ¦¬λ λ³Έμ§μ μΌλ‘ μ¬νμ λλ¬Όμ΄λ©°, νμΈκ³Όμ μ°κ²°μ ν΅ν΄ ν볡과 건κ°μ μ»μ΅λλ€. νμ§λ§ μμ€μ μΌλ‘, μ°λ¦¬λ μ’ μ’ μ¬νμ κ΅λ₯λ₯Ό νΌνκ³ κ³ λ¦½μ μ ννλ κ²½ν₯μ΄ μμ΅λλ€. νΉν λ―μ μ¬λκ³Όμ λνλ μ΄μν¨κ³Ό λΆνΈν¨μ μ λ°ν κ²μ΄λΌλ μμ λλ¬Έμ λ§μ€μ΄κ² λμ£ . μ΄λ¬ν μΈκ°μ νλ λ€μ μ¨κ²¨μ§ μ¬λ¦¬μ λ©μ»€λμ¦μ 무μμ΄λ©°, μ°λ¦¬κ° λμΉκ³ μλ μμ€ν κΈ°νλ 무μμΌκΉμ?
λ―Έκ΅ μμΉ΄κ³ λνκ΅μ νλκ³Όν κ΅μμ΄μ λ² μ€νΈμ λ¬ μκ°μΈ λμ½λΌμ€ μ΄ν리(Nicholas Epley)λ κ·Έμ μ μμ μ°κ΅¬λ₯Ό ν΅ν΄ μ΄ μ§λ¬Έμ λν κΉμ΄ μλ ν΅μ°°μ μ μν©λλ€. νμ€(Vox) μ±λμ βλ κ·Έλ μ΄ μμ΄λ¦¬μ΄(The Gray Area)β μΈν°λ·°μμ κ·Έλ μ°λ¦¬κ° μ¬νμ κ΅λ₯μ μν° μ΄μ μ κ·Έλ‘ μΈν΄ λ°μνλ λΉκ·Ήμ κ²°κ³Όλ₯Ό μ€λͺ νλ©°, μμΈλ‘ κ°λ¨ν λ°©λ²μΌλ‘ μ°λ¦¬μ μΆμ λ νμλ‘κ² λ§λ€ μ μλ€κ³ μμ€νμ΅λλ€.
λ―μ μ΄μμ λν, μμλ³΄λ€ ν¨μ¬ μ’λ€
μ΄ν리 κ΅μλ μμΉ΄κ³ ν΅κ·ΌκΈΈμμ κ²ͺμλ κ°μΈμ μΈ κ²½νμ ν΅ν΄ κ·Έμ μ°κ΅¬κ° μμλμλ€κ³ λ§ν©λλ€. λ§€μΌ μμΉ¨ λ§μ μ§νμ² μμ μλ λμ κ°μ μΉΈμ ν μ΄μλ€μ΄ μλ‘λ₯Ό ν¬λͺ μΈκ° μ·¨κΈνλ©° μμμλ λͺ¨μ΅μ 보면μ, κ·Έλ μ°λ¦¬κ° βλ€λ₯Έ μ¬λμ μμ λ¨νμ²λΌ λνκ³ μλ€βλ κ°ν μΈμμ λ°μμ΅λλ€. μΈκ°μ νμΈμ λ§μκ³Ό μ°κ²°λλλ‘ κ³ λλ‘ μ€κ³λ μ¬νμ μ‘΄μ¬μμλ λΆκ΅¬νκ³ , μ€μ λ‘λ κ³ λ¦½μ μ ννλ μ΄ μμ€μ μΈ μν©μ λν΄ κ³Όνμλ‘μ μλ¬Έμ νκ² λ κ²μ΄μ£ .
μ΄λ λ μμΉ¨, μ΄ν리 κ΅μλ λ©μ§ λΉ¨κ° λͺ¨μλ₯Ό μ΄ 15μ΄ μ λ μ°μμ νμΈ μ¬μ± μμ μκ² λ©λλ€. κ·Έλ ν΄λν°λ§ λ©νλ 보며 μκ°μ 보λ΄λ(doom scrolling) λμ , κ·Έλ μκ² λ§μ κ±Έμ΄λ³΄κΈ°λ‘ κ²°μ¬νμ΅λλ€. νμ§λ§ λ¨Έλ¦Ώμμμλ μ¨κ° λΆμκ³Ό ννΌμ μ΄μ λ€μ΄ μμμ Έ λμμ΅λλ€. βκ΄΄μ§λ‘ λ³΄μΌ κ±°μΌβ, βλ§νκ³ μΆμλ€λ©΄ λ¨Όμ λ§μ κ±Έμκ² μ§β, βλνν 곡ν΅μ λ μλλ° μ΄λ»κ² μμνμ§?β κ°μ μκ°λ€μ΄μμ£ .
κ·ΈλΌμλ λΆκ΅¬νκ³ κ·Έλ μ©κΈ°λ₯Ό λ΄μ΄ κ·Έλ μκ² λ§μ κ±Έμμ΅λλ€. βμλ νμΈμ, λμ λλ€. λͺ¨μκ° μ λ§ λ©μ§λ€μ. μ λ λΉμ·ν λͺ¨μκ° μμ΄μ.β λ€μ μ΄μν μμμ΄μμ§λ§, κ·Έμ μΉκ·Όν μλλ₯Ό μμμ°¨λ¦° κ·Έλ λ λ―Έμλ₯Ό μ§μΌλ©° λνλ₯Ό λ°μμ£Όμμ΅λλ€. λ μ¬λμ 30λΆ λμ μμ μ μΌκ³Ό κ°μ‘±μ λν΄ μ΄μΌκΈ°νκ³ , λνλ λλλλ‘ μ¦κ±°μ μ΅λλ€. ν€μ΄μ§ λ κ·Έλ λ κ·Έμκ² βμ€λ μμΉ¨μ λν λλ μ£Όμ μ μ λ§ κ°μ¬ν΄μβλΌκ³ λ§νμ΅λλ€.
μ΄ν리 κ΅μλ μ΄ κ²½νμ΄ βμμλ³΄λ€ ν¨μ¬ μ’μλ€βλ μ μμ ν° μΆ©κ²©μ λ°μλ€κ³ νμν©λλ€. μ€μ€λ‘λ₯Ό κ³ λ¦½μν€λΌλ λ΄λ©΄μ κΈ°λμΉμ μ€μ κ²½ν μ¬μ΄μ κ±°λ¦¬κ° μμ²λ¬λ κ²μ λλ€. κ·Έλ λ§μ½ μ°λ¦¬κ° μΆμ λ€λ₯Έ μμμμλ μλ―Έ μκ³ λ³΄λ μλ μνΈμμ©μ λΆνμνκ² νΌνκ³ μλ€λ©΄, μ΄λ μ°λ¦¬μ μΆμ λ€μν λ°©μμΌλ‘ λ³νμν¬ μ μλ βμ€μβλΌκ³ κΉ¨λ¬μμ΅λλ€.
μ¬νμ κ΅λ₯λ₯Ό νΌνλ μΈ κ°μ§ μ¬λ¦¬μ μ₯λ²½
μ΄ν리 κ΅μλ μ°λ¦¬κ° μ¬νμ κ΅λ₯λ₯Ό νΌνλ μ΄μ λ₯Ό μΈ κ°μ§ μ¬λ¦¬μ μμΈμΌλ‘ μ€λͺ ν©λλ€.
1. μκΈ° νκ°μ νμΈ νκ°μ λΆμΌμΉ
μ°λ¦¬λ νμΈκ³Όμ μνΈμμ©μμ μ£Όλ‘ μμ μ βλ₯λ ₯(competency)βμ νκ°ν©λλ€. βλ¬΄μ¨ λ§μ ν΄μΌ ν κΉ?β, βλνλ₯Ό μ μ΄λμ΄κ° μ μμκΉ?β κ°μ κ±±μ μ΄μ£ . νμ§λ§ νμΈμ μ°λ¦¬λ₯Ό βλ°λ»ν¨(warmth)βμ΄λΌλ λ€λ₯Έ κΈ°μ€μΌλ‘ νκ°ν©λλ€. βμ΄ μ¬λμ΄ μΉμ νκ°?β, βλ―Ώμ λ§νκ°?β, βμΉκ΅¬μΈκ°, μλλ©΄ μ‘°μ¬ν΄μΌ ν μ¬λμΈκ°?β λ±μ μ΄νΌλ κ²μ λλ€.
μ¬νμ νλμ λ³Έμ§μ μΌλ‘ λ°λ»ν¨μ μ λ¬ν©λλ€. λκ΅°κ°μκ² κ΄μ¬μ νννκ³ , μΉκ·Όνκ² λ€κ°κ°κ³ , κ°μ¬ν¨μ μ νκ³ , μΉμ°¬νκ±°λ λμμ μμ²νλ λͺ¨λ νμλ μ°λ¦¬μ λ°λ»ν μλλ₯Ό 보μ¬μ€λλ€. νμ§λ§ μ°λ¦¬λ μμ μ λ₯λ ₯μ λν κ±±μ λλ¬Έμ μ΄λ¬ν λ°λ»ν¨μ μ λ¬ ν¨κ³Όλ₯Ό κ³Όμνκ°νμ¬ μνΈμμ©μ μ£Όμ νκ² λ©λλ€.
2. μνΈμμ©μ μλμ±μ κ°κ³Όνλ κΈ°λμΉ
μ°λ¦¬λ μ¬νμ μνΈμμ©μ κ²½νμ΄ μ΄λ»κ² νΌμ³μ§μ§μ λν κΈ°λλ₯Ό βμ€λ μ·(snapshot)βμ²λΌ λ¨μνκ³ μ μ μΈ λ°©μμΌλ‘ νμ±ν©λλ€. κ·Έλ¬λ νμ€μ μνΈμμ©μ βμν(movie)βμ²λΌ μλμ μ΄κ³ μνΈμ (reciprocal)μ λλ€. λ΄κ° λ¨Όμ μΈμ¬λ₯Ό 건λ€λ©΄ μλλ°©λ μΈμ¬λ₯Ό νκ³ , λ΄κ° λ―Έμ μ§μΌλ©΄ μλλ°©λ λ―Έμ μ§μ΅λλ€. μλ―Έ μλ μ΄μΌκΈ°λ₯Ό λ¨Όμ κΊΌλ΄λ©΄, μλλ°©λ λ§μμ μ΄μ΄μ£Όλ κ²½ν₯μ΄ μμ΅λλ€.
μ΄λ¬ν λ°μμ μ΄κ³ μνΈμ μΈ νΉμ§λ€μ΄ μ°λ¦¬λ₯Ό μλ‘ μ°κ²°ν©λλ€. νμ§λ§ μ°λ¦¬λ 볡μ‘νκ³ μλμ μΈ μνΈμμ©μ λ³Έμ§, νΉν μνΈμ±μ μΆ©λΆν μ΄ν΄νμ§ λͺ»νκΈ° λλ¬Έμ, λνκ° μΌλ§λ μ μ§νλ μ§ κ³Όμνκ°νκ² λ©λλ€.
3. μκΈ° μΆ©μ‘±μ λΉκ΄μ£Όμ (Self-Fulfilling Pessimism)
λ§μ§λ§μΌλ‘, λ§μμ λΉκ΄μ£Όμκ° μΉνΈλ©΄ κ·Έκ²μ βμκΈ° μΆ©μ‘±μ μμΈ(self-fulfilling prophecy)βμ΄ λ κ°λ₯μ±μ΄ ν½λλ€. λ§μ½ λκ΅°κ°μ λννλ κ²μ΄ λΆμΎν κ²μ΄λΌκ³ μκ°νλ©΄, μ°λ¦¬λ κ·Έ λνλ₯Ό μλμ‘°μ°¨ νμ§ μμ κ²μ λλ€. κ·Έλ κ² λλ©΄ μ°λ¦¬κ° νλ Έμ μλ μλ€λ μ¬μ€μ μμν μ μ μκ² λ©λλ€.
λ°λλ‘ λκ΄μ£Όμλ μ κ·Όμ μ λνκ³ , μ κ·Όμ νμ€κ³Ό μ°λ¦¬μ λ―Ώμμ μ‘°μ νλ λ° νμν λ°μ΄ν°λ₯Ό μ 곡ν©λλ€. νμ§λ§ λΉκ΄μ£Όμλ μ°λ¦¬κ° κ·Έ λ°μ΄ν°λ₯Ό μ»λ κ²μ λ§κ³ , κ²°κ΅ κ³Όλνκ² λΉκ΄μ μΈ λ―Ώμμ κ³ μ°©νμν΅λλ€. μ΄ν리 κ΅μλ μ΄λ₯Ό βλΉκ·Ήμ βμ΄λΌκ³ ννν©λλ€. λΆνμν μν ννΌκ° 보λ μλ κ²½νμ κΈ°νλ₯Ό λ°ννλ κ²μ΄κΈ° λλ¬Έμ λλ€. κ·Έλ μ°λ¦¬κ° λ€λ₯Έ μ¬λκ³Όμ μ°κ²°μ λ§κ³ μλ€κ³ μκ°νλ βκ°μ₯μ μ°½μ΄βμ΄ μ¬μ€μ βμ μ νμ€ν λ©΄λ°βμ²λΌ μ½ν μ μμΌλ©°, μ‘°κΈλ§ λ°μ΄λ³΄λ©΄ κ·Έ μ¬μ€μ μκ² λ κ²μ΄λΌκ³ λ§ν©λλ€.
κ³ λ¦½μ΄ κ°μ Έμ€λ μμμΉ λͺ»ν λκ°
μ¬νμ μ°κ²°μ λΆμ¬λ λ¨μν λΆνΈν¨μ λμ΄ μ°λ¦¬μ 건κ°κ³Ό μμ‘΄μ μ¬κ°ν μνμ΄ λ©λλ€. μ΄ν리 κ΅μλ μΈκ° μμ¬ λλΆλΆμ κΈ°κ° λμ νΌμ κ³ λ¦½λλ κ²μ κ³§ μ£½μμ μλ―Ένλ€κ³ κ°μ‘°ν©λλ€. λ°λΌμ μ°λ¦¬κ° νΌμ μκ±°λ λ€λ₯Έ μ¬λκ³Ό λ¨μ λμλ€κ³ λλ λ, μ°λ¦¬μ λμ μ 체λ μ΄λ₯Ό μνμΌλ‘ μΈμν©λλ€.
μ΄λ¬ν μν μΈμμ μ€νΈλ μ€ νΈλ₯΄λͺ¬μΈ μ½λ₯΄ν°μ(cortisol) μμΉλ₯Ό κΈμ¦μν€κ³ , λ§μ±μ μΈ μ½λ₯΄ν°μ μ¦κ°λ λ©΄μ 체κ³λ₯Ό μ½νμμΌ κ°κΈ°, νλ ΄, μ¬μ§μ΄ μ½λ‘λ19μ κ°μ μ§λ³μ λ μ·¨μ½νκ² λ§λλλ€. μ₯κΈ°μ μΌλ‘λ μ¬νκ΄ κΈ°λ₯μλ μ μν₯μ λ―ΈμΉ©λλ€. λλκ²λ μν μ°κ΅¬μ λ°λ₯΄λ©΄, μΈλ‘μμ ν루 15κ°λΉμ λ΄λ°°λ₯Ό νΌμ°λ κ²κ³Ό λ§λ¨Ήλ μμ€μΌλ‘ μ‘°κΈ° μ¬λ§μ μ£Όμ μν μμμ΄λ©°, μ΄λ λΆμ‘±μ΄λ 과체μ€λ³΄λ€λ λ μΉλͺ μ μΌ μ μλ€κ³ ν©λλ€.
μ€λ«λμ μ¬λ¦¬νκ³λ μ¬νμ μ°κ²°μ μ€μμ±μ κΈ°λ³Έμ μΈ μΈκ°μ μκ΅¬λ‘ μΆ©λΆν μΈμνμ§ λͺ»νμ΅λλ€. μμ΄λΈλ¬ν λ§€μ¬λ‘(Abraham Maslow)μ μꡬ λ¨κ³ μ΄λ‘ μμ βμμκ°(belonging)βμ μ€κ° λ¨κ³μ μμΉνμ¬ λ§μΉ μ¬μΉνμ²λΌ μ¬κ²¨μ‘μ§λ§, μ΄ν리 κ΅μλ μμ¬μ μλ©΄μ²λΌ κΈ°λ³Έμ μΈ μμ‘΄ μꡬλΌκ³ κ°μ‘°ν©λλ€. μ°λ¦¬μ λμ μ리μ λ°μμ΄ μ΄λ₯Ό λͺ νν 보μ¬μ€λλ€.
βμ¬νμ μ©κΈ°βλ₯Ό κ°λ‘λ§λ μκ°μ λ§μ€μ
μ°λ¦¬κ° μ¬νμ κ΅λ₯λ₯Ό μλν μ§ λ§μ§ κ²°μ νλ μκ°μ βμ νβμ λ¬Έμ μ λλ€. μ΄ν리 κ΅μλ μ΄λ₯Ό βμ κ·Ό-ννΌ κ°λ±(approach-avoidance conflict)βμ΄λΌκ³ μ€λͺ ν©λλ€. μ°λ¦¬μ λμλ λ€κ°κ°λλ‘ κ²©λ €νλ μμ€ν κ³Ό ννΌνλλ‘ κ²©λ €νλ μμ€ν μ΄ λ 립μ μΌλ‘ μλν©λλ€.
ν₯λ―Έλ‘κ²λ, μ΄λ€ μ¬κ±΄μ΄ λ©λ¦¬ μμ λλ μ κ·Ό λκΈ°κ° λ§€μ° λμ΅λλ€. μλ₯Ό λ€μ΄, βμ€λ λΉνκΈ°μμ μ μ¬λκ³Ό μ΄μΌκΈ°ν΄μ ν₯λ―Έλ‘μ΄ μ΄μΌκΈ°λ₯Ό λ€μ΄μΌμ§βλΌκ³ μκ°ν λλ λ§€μ° κΈμ μ μ λλ€. νμ§λ§ μ€μ λ‘ κ·Έ μκ°μ΄ λ€κ°μ λ―μ μ¬λμ΄ λ°λ‘ μμ μμ μκ±°λ, μ΄λ €μ΄ λνλ₯Ό μμν΄μΌ ν λκ° λλ©΄, ννΌ λκΈ°κ° κΈμ¦ν©λλ€. λͺ¨λ ννΌμ μ΄μ λ€μ΄ μ¦κ°μ μΌλ‘ κ°λ ₯ν΄μ§λ©΄μ μμ κ°μ λ°λ₯μΌλ‘ λ¨μ΄μ§κ³ , κ²°κ΅ μ°λ¦¬λ βλ°μ΄ μλ €μ(get cold feet)β λ¬Όλ¬μκ² λ©λλ€.
μ΄λ¬ν νμμ λκ° βμμΈ‘βμ βμ 보βλ‘ μ°©κ°νλ λ°μ λΉλ‘―λ©λλ€. βμ΄μν κ±°μΌβλΌλ μμΈ‘μ βμ΄μνλ€βλ νμ€λ‘ λ°μλ€μ΄λ κ²μ΄μ£ . μ΄ν리 κ΅μλ μ°λ¦¬κ° μΆμμ 무μμ ν μ§ κ²°μ ν λ, νμ€μ΄ μλ βμ°λ¦¬κ° μ΄λ»κ² κ²½νν κ²μ΄λΌκ³ μκ°νλμ§βκ° κ°μ₯ μ€μνλ€κ³ λ§ν©λλ€. μ΄ μμΈ‘μ΄ νμ€μ λ§λ€κ³ , μ°λ¦¬κ° μλνμ§ μμΌλ©΄ μλͺ»λ μμΈ‘μ κ²°μ½ μμ ν μ μκ² λ©λλ€.
μ μ§ν¨κ³Ό κΉμ΄ μλ λνμ ν
μ€ν΄λ°λ μ μ§ν¨
μ°λ¦¬λ νν μ μ§ν¨μ΄ μλλ°©μκ² μμ²λ₯Ό μ£Όκ±°λ κ΄κ³λ₯Ό ν΄μΉ κ²μ΄λΌκ³ μκ°ν©λλ€. νΉν λΆμ μ μΈ νΌλλ°±μ μ€ λ λμ± κ·Έλ μ£ . νμ§λ§ μ΄ν리 κ΅μλ μ°λ¦¬κ° μ μ§ν¨μ βλ΄μ©βμλ§ μ§μ€νκ³ , μ μ§ν¨μ΄ μ λ¬νλ βλ°λ»ν¨βμ΄λΌλ λ³Έμ§μ μΈ μ°¨μμ κ°κ³Όνλ€κ³ μ§μ ν©λλ€.
λμμ μ£Όλ €λ μλλ₯Ό λ΄μ μ μ§ν¨μ μμλ³΄λ€ ν¨μ¬ κΈμ μ μΌλ‘ λ°μλ€μ¬μ§ μ μμ΅λλ€. μλ₯Ό λ€μ΄, λ°°μ°μκ° ν΄μ€ μμμ΄ λ³λ‘μμ λ βμ λ§ λ§μμμ΄βλΌκ³ βνμ κ±°μ§λ§(white lie)βμ νλ λμ , βμ΄κ²λ§ κ³ μΉλ©΄ ν¨μ¬ λ§μμ κ±°μΌβλΌκ³ 건μ€μ μΈ νΌλλ°±μ μ£Όλ κ²μ κ΄κ³λ₯Ό κ°μ νκ³ μλλ°©μ΄ λ λμμ§λλ‘ λλ λ°λ»ν νμκ° λ μ μμ΅λλ€. λ¬Όλ‘ μκ°μ μΌλ‘λ μμ‘΄μ¬μ΄ μν μ μμ§λ§, μ₯κΈ°μ μΌλ‘λ μλλ°©μ΄ μμ μ μ§μ μΌλ‘ μλΌκ³ λμμ£Όλ € νλ€λ κ²μ λλΌκ² λμ΄ κ΄κ³κ° λμ± κΉμ΄μ§ μ μμ΅λλ€.
μ΄ν리 κ΅μμ λλ£ μ λ§ λ λΉ(Emma Levine) κ΅μμ μ°κ΅¬μ λ°λ₯΄λ©΄, ν루λ₯Ό βμμ ν μ μ§νκ²β λ³΄λΈ μ¬λλ€μ βμμ ν μΉμ νκ²β λ³΄λΈ μ¬λλ€κ³Ό λ§μ°¬κ°μ§λ‘ κ·Έλ μ μ’κ² νκ°νκ³ , κ΄κ³κ° λ κ°ν΄μ‘λ€κ³ λκΌμ΅λλ€. μ€νλ € μμ§ν¨μ ν΅ν΄ μμ μ λν΄ λ μ’κ² λλΌλ κ²½ν₯λ μμμ΅λλ€. λ€λ§, μ μ§ν¨μ΄ μλλ°©μκ² μ ν λμμ΄ λμ§ μκ³ λ¨μ§ μμΈνκ² λκ»΄μ§ λλ§ βνμ κ±°μ§λ§βμ΄ μ λΉνλ μ μλ€κ³ λ λΉ κ΅μλ λ§λΆμμ΅λλ€.
μ€λͺ° ν ν¬λ₯Ό λμ΄μ λ₯ ν ν¬
λ§μ μ¬λλ€μ΄ βμ€λͺ° ν ν¬(small talk)βλ₯Ό μ«μ΄ν©λλ€. μ§λΆνκ³ νΌμμ μ΄λ©° κ°μμ μ΄λΌκ³ λλΌκΈ° λλ¬Έμ΄μ£ . μ΄ν리 κ΅μ μμ μ΄λ¬ν κ°μ μ 곡κ°νλ©°, μ€λͺ° ν ν¬κ° μλ βκΉμ΄ μλ λν(deep talk)βμ μ€μμ±μ κ°μ‘°ν©λλ€.
κ·Έλ MBA νμλ€μ λμμΌλ‘ ν μ€νμμ, λ―μ μ¬λκ³Ό ν¨κ» βλ§μ½ λ΄κ° λΉμ μ μ’μ μΉκ΅¬κ° λλ€λ©΄, λΉμ μ λν΄ κ°μ₯ μ€μνκ² μμμΌ ν κ²μ 무μμΈκ°μ?β, βλΉμ μ μΈμμμ κ°μ₯ κ°μ¬νλ κ²μ 무μμ΄λ©°, κ·Έμ λν΄ λ§ν΄μ€ μ μλμ?β, βλ€λ₯Έ μ¬λ μμμ λ§μ§λ§μΌλ‘ μΈμλ λμ λν΄ λ§ν΄μ€ μ μλμ?βμ κ°μ κΉμ΄ μλ μ§λ¬Έλ€μ λλλλ‘ νμ΅λλ€.
μ²μμλ νμλ€μ΄ λ§€μ° μ΄μνκ³ λΆνΈν΄νλ©° λνκ° μ λμ§ μμ κ²μ΄λΌκ³ μμνμ§λ§, μ€μ λνκ° λλ νμλ μλμ μΌλ‘ λλΆλΆμ νμλ€μ΄ μμλ³΄λ€ ν¨μ¬ λ μ΄μνκ³ , μλλ°©κ³Ό λ κ°ν μ λκ°μ νμ±νμΌλ©°, λνκ° μ¦κ±°μ λ€κ³ λ³΄κ³ νμ΅λλ€. μ΄ν리 κ΅μλ μ΄ μ€νμ ν΅ν΄ βλ€λ₯Έ μ¬λλ€λ μ°λ¦¬μ²λΌ μ€λͺ° ν ν¬λ₯Ό μ«μ΄νκ³ , λ μλ―Έ μλ λνλ₯Ό μνλ€βλ μ¬μ€μ κΉ¨λ¬μλ€κ³ λ§ν©λλ€.
μ°λ¦¬κ° μΌμμμ λλλ λνλ μΆ©λΆν κΉμ§ λͺ»νμ§λ§, λλΆλΆμ μ¬λλ€μ μ€μ λ‘λ λ κΉμ΄ μλ λνλ₯Ό μν©λλ€. λνμ λ°©ν₯μ λ°κΏ νμ μ°λ¦¬μκ² μμ΅λλ€. μλλ°©μκ² λ§μμ μ΄κ³ κ΄μ¬μ νννλ©΄, μλλ°©λ λ§μμ μ΄κ³ λμμ¬ κ²μ΄λ©°, μ΄λ ν¨μ¬ λ νμλ‘μ΄ λνλ‘ μ΄μ΄μ§ μ μμ΅λλ€.
νλ μ¬νμ βμ νμ κ³ λ¦½βμ μν
μ¬νμ κ΅λ₯λ₯Ό νΌνλ κ²½ν₯μ κ³Όκ±°μλ μ‘΄μ¬νμ΅λλ€. 1970λ λ λ΄μ μ§νμ² μμ μ€ν 리 λ°κ·Έλ¨(Stanley Milgram) κ΅μκ° κ΄μ°°νλ―, μμ΄ν°μ΄ μλ μμ μλ μ¬λλ€μ μλ‘ λ§μ κ±Έμ§ μκ³ μ λ¬Έμ΄λ μ± λ§ λ³΄λ©° κ°μμ μΈκ³μ λͺ°μ νμ΅λλ€. νμ§λ§ νλ μ¬νμμλ κ·Έ μμμ΄ λμ± μ¬νλμμ΅λλ€.
μ΄ν리 κ΅μλ κ³Όκ±°μλ μ¬νμ μνΈμμ©μ΄ μμ‘΄μ μν νμμ μΈ μμμλ λ°λ©΄, νλμλ βμ νβμ μ¬μ§κ° ν¨μ¬ λ§μμ‘λ€κ³ μ§μ ν©λλ€. μ°λ¦¬λ μνλ€λ©΄ ν루 μ’ μΌ μ무λ λ§λμ§ μκ³ νΌμ μ΄ μ μμ΅λλ€. μμΉ¨ μμ¬λ λ°°λ¬μν€κ³ , μ₯μ μ¨λΌμΈμΌλ‘ λ³΄κ³ , μ¬ν근무λ₯Ό νλ©°, λ°€μλ TVλ‘ μν°ν μΈλ¨ΌνΈλ₯Ό μ¦κΈΈ μ μμ΅λλ€. κΈ°μ λ°μ μ΄ κ°μ Έμ¨ βλ§μ°° μλ μΈμ(frictionless world)βμ μ°λ¦¬μκ² λ 립μ±μ΄λΌλ ν° μ΄μ μ μ£Όμμ§λ§, λμμ μ¬νμ μ°κ²°μ΄λΌλ μ€μν κ°μΉλ₯Ό ν¬μμν€κ³ μμ΅λλ€.
μμ μ©κΈ°κ° κ°μ Έμ¬ ν° λ³ν
μ΄ν리 κ΅μλ μμ μ μ°κ΅¬κ° κ·Έ μ΄λ€ κ²λ³΄λ€λ κ°μΈμ μΌλ‘ ν° λ³νλ₯Ό κ°μ Έμλ€κ³ κ³ λ°±ν©λλ€. μμ μ βλ΄ν₯μ μΈ μ¬λ(introvert)βμ΄λΌκ³ μκ°νμ§λ§, μ°κ΅¬λ₯Ό ν΅ν΄ μ¬νμ κ΅λ₯μ λν μ€ν΄λ₯Ό λ²κ³ μ κ·Ήμ μΌλ‘ λ€κ°κ°λ©΄μ μΆμ΄ ν¨μ¬ νμλ‘μμ‘λ€λ κ²μ λλ€.
μ°λ¦¬κ° λ―μ μ΄μμ λνλ₯Ό μ£Όμ νκ³ , μμ§ν νΌλλ°±μ λ§μ€μ΄λ©°, νΌμμ μΈ μ€λͺ° ν ν¬μ 머무λ κ²μ λλΆλΆ μλͺ»λ κΈ°λμ λΉκ΄μ£Όμ λλ¬Έμ λλ€. μ°λ¦¬μ λλ μ΄μν κ²μ΄λΌλ βμμΈ‘βμ βμ 보βλ‘ μ°©κ°νμ¬ νμ€μ μ곑νκ³ , κ²°κ΅ μ°λ¦¬λ₯Ό λΆνμν κ³ λ¦½μΌλ‘ μ΄λμ΄κ°λλ€.
νμ§λ§ μ΄ν리 κ΅μλ μ°λ¦¬κ° μ¬νμ μνΈμμ©μ μ±κ³΅ νλ₯ μ κ³Όμνκ°νκ³ μμ λΏμ΄λΌκ³ λ§ν©λλ€. μμ βμνβμ ν΅ν΄ μ°λ¦¬μ μμΈ‘μ΄ νλ Έμμ κΉ¨λ«λλ€λ©΄, μΈμμ ν¨μ¬ λ μ΄λ¦¬κ³ νμλ‘μμ§ κ²μ λλ€. μ€λ ν루, λ―μ μ΄μκ² λ―Έμ μ§μΌλ©° λ¨Όμ μΈμ¬λ₯Ό 건λ€κ±°λ, μ‘°κΈ λ κΉμ΄ μλ μ§λ¬Έμ λμ Έλ³΄λ μμ μ©κΈ°κ° μ΄μ©λ©΄ λΉμ μ μΆμ μμλ³΄λ€ ν¨μ¬ λ ν볡νκ³ μλ―Έ μκ² λ§λ€ μ μμ΅λλ€.