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+How to tell if AI threatens YOUR job
+
+No, really, this post may give you a way to answer that
+
+An icon of a clock Publish Date
+    March 14, 2023
+An icon of a human figure Authors
+    Justin Searls
+
+As a young lad, I developed a habit of responding to the enthusiasm of others
+with fear, skepticism, and judgment.
+
+While it never made me very fun at parties, my hypercritical reflex has been
+rewarded with the sweet satisfaction of being able to say “I told you so” more
+often than not. Everyone brings a default disposition to the table, and for me
+that includes a deep suspicion of hope and optimism as irrational exuberance.
+
+But there’s one trend people are excited about that—try as I might—I’m having a
+hard time passing off as mere hype: generative AI.
+
+The more excited someone is by the prospect of AI making their job easier, the
+more they should be worried.
+
+There’s little doubt at this point: the tools that succeed DALL•E and ChatGPT
+will have a profound impact on society. If it feels obvious that self-driving
+cars will put millions of truckers out of work, it should be clear even more
+white collar jobs will be rendered unnecessary by this new class of AI tools.
+
+While Level 4 autonomous vehicles may still be years away, production-ready AI
+is here today. It’s already being used to do significant amounts of paid work,
+often with employers being none the wiser.
+
+If truckers deserve years of warnings that their jobs are at risk, we owe it to
+ourselves and others to think through the types of problems that generative AI
+is best equipped to solve, which sorts of jobs are at greatest risk, and what
+workers can start doing now to prepare for the profound disruption that’s
+coming for the information economy.
+
+So let’s do that.
+
+Now it’s time to major bump Web 2.0
+
+Computer-generated content wouldn’t pose the looming threat it does without the
+last 20 years of user-generated content blanketing the Internet to fertilize
+it.
+
+As user-generated content came to dominate the Internet with the advent of Web
+2.0 in the 2000s, we heard a lot about the Wisdom of the Crowd. The theory was
+simple: if anyone could publish content to a platform, then users could rank
+that content’s quality (whether via viewership metrics or explicit upvotes),
+and eventually the efforts of the (unpaid!) general public would outperform the
+productivity of (quite expensive!) professional authors and publishers. The
+winners, under Web 2.0, would no longer be the best content creators, but the
+platforms that successfully achieve network effect and come to mediate
+everyone’s experience with respect to a particular category of content.
+
+This theory quickly proved correct. User-generated content so dramatically
+outpaced “legacy” media that the newspaper industry is now a shell of its
+former self—grasping at straws like SEO content farms, clickbait headlines, and
+ever-thirstier display ads masquerading as content. The fact I’ve already used
+the word “content” eight times in two paragraphs is a testament to how its
+unrelenting deluge under Web 2.0 has flattened our relationship with
+information. “Content” has become a fungible resource to be consumed by our
+eyeballs and earholes, which transforms it into a value-added product called
+“engagement,” and which the platform owners in turn package and resell to
+advertisers as a service called “impressions.”
+
+And for a beautiful moment in time, this system created a lot of value for
+shareholders.
+
+But the status quo is being challenged by a new innovation, leading many of Web
+2.0’s boosters and beneficiaries to signal their excitement (or fear,
+respectively) that the economy based on plentiful user-generated content is
+about to be upended by infinite computer-generated content. If we’re witnessing
+the first act of Web 3.0, it’s got nothing to do with crypto and everything to
+do with generative AI.
+
+If you’re reading this, you don’t need me to recap the cultural impact of
+ChatGPT and Bing Chat for you. Suffice to say, if Google—the runaway winner of
+the Web 2.0 economy—is legit shook, there’s probably fire to go with all this
+smoke. Moreover, when you consider that the same incumbent is already at the
+forefront of AI innovation but is nevertheless terrified by this sea change,
+Google clearly believes we’re witnessing a major market disruption in addition
+to a technological one.
+
+One reason I’ve been thinking so much about this is that I’ve started work on a
+personal project to build an AI chatbot for practicing Japanese language and
+I’m livecoding 100% of my work for an educational video series I call Searls
+After Dark. Might be why I’ve got AI on the mind lately!
+
+But you’re not a tech giant. You’re wondering what this means for you and your
+weekend. And I think we’re beginning to identify the contours of an answer to
+that question.
+
+ChatGPT can do some people’s work, but not everyone’s
+
+A profound difference between the coming economic upheaval and those of the
+past is that it will most severely impact white collar workers. Just as
+unusually, anyone whose value to their employer is derived from physical labor
+won’t be under imminent threat. Everyone else is left to ask: will generative
+AI replace my job? Do I need to be worried?
+
+Suppose we approached AI as a new form of outsourcing. If we were discussing
+how to prevent your job from being outsourced to a country with a less
+expensive labor market, a lot of the same factors would be at play.
+
+Having spent months programming with GitHub Copilot, weeks talking to ChatGPT,
+and days searching via Bing Chat as an alternative to Google, the best
+description I’ve heard of AI’s capabilities is “fluent bullshit.” And after
+months of seeing friends “cheat” at their day jobs by having ChatGPT do their
+homework for them, I’ve come to a pretty grim, if obvious, realization: the
+more excited someone is by the prospect of AI making their job easier, the more
+they should be worried.
+
+Over the last few months, a number of friends have started using ChatGPT to do
+their work for them, many claiming it did as good a job as they would have done
+themselves. Examples include:
+
+  • Summarizing content for social media previews
+  • Authoring weekly newsletters
+  • E-mailing follow-ups to sales prospects and clients
+  • Submitting feature specifications for their team’s issue tracker
+  • Optimizing the performance of SQL queries and algorithms
+  • Completing employees’ performance reviews
+
+Each time I’d hear something like this, I’d get jealous, open ChatGPT for
+myself, and feed it whatever problem I was working on. It never worked.
+Sometimes it’d give up and claim the thing I was trying to do was too obscure.
+Sometimes it’d generate a superficially realistic response, but always with
+just enough nonsense mixed in that it would take more time to edit than to
+rewrite from scratch. But most often, I’d end up wasting time stuck in this
+never-ending loop:
+
+ 1. Ask ChatGPT to do something
+ 2. It responds with an obviously-wrong answer
+ 3. Explain to ChatGPT why its response is wrong
+ 4. It politely apologizes (“You are correct, X in fact does not equal Y. I
+    apologize.”) before immediately generating an equally-incorrect answer
+ 5. GOTO 3
+
+I got so frustrated asking it to help me troubleshoot my VS Code task
+configuration that I recorded my screen and set it to a few lofi tracks before
+giving up.
+
+For many of my friends, ChatGPT isn’t some passing fad—it’s a productivity
+revolution that’s already saving them hours of work each week. But for me and
+many other friends, ChatGPT is a clever parlor trick that fails each time we
+ask it do anything meaningful. What gives?
+
+Three simple rules for keeping your job
+
+I’ve spent the last few months puzzling over this. Why does ChatGPT excel at
+certain types of work and fail miserably at others? Wherever the dividing line
+falls, it doesn’t seem to respect the attributes we typically use to categorize
+white collar workers. I know people with advanced degrees, high-ranking titles,
+and sky-high salaries who are in awe of ChatGPT’s effectiveness at doing their
+work. But I can identify just as many roles that sit near the bottom of the org
+chart, don’t require special credentials, and don’t pay particularly well for
+which ChatGPT isn’t even remotely useful.
+
+Here’s where I landed. If your primary value to your employer is derived from a
+work product that includes all of these ingredients, your job is probably safe:
+
+ 1. Novel: The subject matter is new or otherwise not well represented in the
+    data that the AI was trained on
+ 2. Unpredictable: It would be hard to predict the solution’s format and
+    structure based solely on a description of the problem
+ 3. Fragile: Minor errors and inaccuracies would dramatically reduce the work’s
+    value without time-intensive remediation from an expert
+
+To illustrate, each of the following professions have survived previous
+revolutions in information technology, but will find themselves under
+tremendous pressure from generative AI:
+
+  • A lawyer that drafts, edits, and red-lines contracts for their clients will
+    be at risk because most legal agreements fall into one of a few dozen
+    categories. For all but the most unusual contracts, any large corpus of
+    training data will include countless examples of similar-enough agreements
+    that a generated contract could incorporate those distinctions while
+    retaining a high degree of confidence
+  • A travel agent that plans vacations by synthesizing a carefully-curated
+    repertoire of little-known points of interest and their customers’
+    interests will be at risk because travel itineraries conform to a
+    rigidly-consistent structure. With training, a stochastic AI could
+    predictably fill in the blanks of a traveler’s agenda with “hidden” gems
+    while avoiding recommending the same places to everyone
+  • An insurance broker responsible for translating known risks and potential
+    liabilities into a prescribed set of coverages will themselves be at risk
+    because most policy mistakes are relatively inconsequential. Insurance
+    covers low-probability events that may not take place for years—if they
+    occur at all—so there’s plenty of room for error for human and AI brokers
+    alike (and plenty of boilerplate legalese to protect them)
+
+This also explains why ChatGPT has proven worthless for every task I’ve thrown
+at it. As an experienced application developer, let’s consider whether that’s
+because my work meets the three criteria identified above:
+
+ 1. Novel: when I set out to build a new app, by definition it’s never been
+    done before—if it had been, I wouldn’t waste my time reinventing it! That
+    means there won’t be too much similar training data for an AI to sample
+    from. Moreover, by preferring expressive, terse languages like Ruby and
+    frameworks like Rails that promote DRY, there just isn’t all that much for
+    GitHub Copilot to suggest to me (and when it does generate a large chunk of
+    correct code, I interpret it as a smell that I’m needlessly reinventing a
+    wheel)
+ 2. Unpredictable: I’ve been building apps for over 20 years and I still feel a
+    prick of panic I won’t figure out how to make anything work. Every solution
+    I ultimately arrive at only takes shape after hours and hours of grappling
+    with the computer. Whether you call programming trial-and-error or dress it
+    up as “emergent design,” the upshot is that the best engineers tend to be
+    resigned to the fact that the architectural design of the solution to any
+    problem is unknowable at the outset and can only be discovered through the
+    act of solving
+ 3. Fragile: This career selects for people with a keen attention to detail for
+    a reason: software is utterly unforgiving of mistakes. One errant character
+    is enough to break a program millions of lines long. Subtle bugs can have
+    costly consequences if deployed, like security breaches and data loss. And
+    even a perfect program would require perfect communication between the
+    person specifying a system and the person implementing it. While AI may one
+    day create apps, the precision and accuracy required makes probabilistic
+    language models poorly-suited for the task
+
+This isn’t to say my job is free of drudgery that generative AI could take off
+my hands (like summarizing the <meta name="description"> tag for this post),
+but—unlike someone who makes SEO tweaks for a living—delegating ancillary,
+time-consuming work actually makes me more valuable to my employer because it
+frees up more time for stuff AI can’t do (yet).
+
+So if you’re a programmer like me, you’re probably safe!
+
+Job’s done. Post over.
+
+Post not over: How can I save my job?
+
+So what can someone do if their primary role doesn’t produce work that checks
+the three boxes of novelty, unpredictability, and fragility?
+
+Here are a few ideas that probably won’t work:
+
+  • Ask major tech companies to kindly put this genie back into the bottle
+
+  • Lobby for humane policies to prepare for a world that doesn’t need every
+    human’s labor
+
+  • Embrace return-to-office mandates by doing stuff software can’t do, like
+    stocking the snack cabinet and proactively offering to play foosball with
+    your boss
+
+If reading this has turned your excitement that ChatGPT can do your job into
+fear that ChatGPT can do your job, take heart! There are things you can do
+today to prepare.
+
+Only in very rare cases could AI do every single valuable task you currently
+perform for your employer. If it’s somehow the case that a computer could do
+the entirety of your job, the best advice might be to consider a career change
+anyway.
+
+Suppose we approached AI as a new form of outsourcing. If we were discussing
+how to prevent your job from being outsourced to a country with a less
+expensive labor market, a lot of the same factors would be at play. As a
+result, if you were my friend (just kidding! You are my friend, I swear!) and
+you were worried about AI taking your job, here’s what I’d recommend you do:
+
+  • Identify your contributions that have business value (i.e. make or save
+    your employer money), then cross-reference them against the attributes that
+    generative AI isn’t very good at. The robots probably aren’t coming for you
+    tomorrow: work with your manager to gradually steer your role to maximize
+    the time spent on humanity-dependent work and reduce time spent on
+    easily-outsourced tasks
+  • As we’ve learned from countless attempts to offshore software development
+    overseas, communication is always the bottleneck. Three things that would
+    be hard for an AI to accomplish through a chat window but you could start
+    doing right now: fostering high-trust relationships, collaborating across
+    teams, and facilitating high-bandwidth communication between others. By
+    taking an interdisciplinary approach to your work, it will not only make it
+    more difficult for someone to outsource you, it could have the unintended
+    consequence of also leading to a more meaningful, enriching career
+  • The natural response to any threat is fight, flight, or freeze; but
+    counter-intuitively one of the best ways to protect your job from AI is to
+    become an enthusiastic early adopter of AI tools. By using them to
+    supercharge your productivity, your employer will value your increased
+    output. Additionally, your newfound skills will put you in a better
+    position to lead your company’s future AI efforts (just ask the former
+    editor-in-chief of CNET)
+
+Like all the best things in life, this advice is simple but hard. The reason I
+wrote this post now (instead of waiting until GPT-9.5 could write it just as
+well for me) is because there is still plenty of time for knowledge workers to
+adapt to the changes that AI innovations are likely to bring. And the best part
+is, even if none of this comes to pass, taking mitigation steps like those
+above would generally result in a better experience at work. It’s a win-win!
+
+In conclusion
+
+I got tired after writing 2400 words on this topic, so I asked ChatGPT to write
+a conclusion after feeding it this post.
+
+Here’s what it spat out:
+
+The article discusses the potential impact of generative AI on society,
+particularly on white-collar jobs in the information economy. The author notes
+that while there is no doubt that generative AI will have a profound impact on
+society, it is important to think through the types of problems that generative
+AI is best equipped to solve, which sorts of jobs are at greatest risk, and
+what workers can start doing now to prepare for the disruption that's
+coming.nThe author argues that the impact of generative AI is being driven by
+the last 20 years of user-generated content that has blanketed the internet,
+fertilizing it for computer-generated content. User-generated content dominated
+the internet with the advent of Web 2.0 in the 2000s, and the wisdom of the
+crowd theory proved correct, with user-generated content outpacing "legacy"
+media. However, the status quo is being challenged by generative AI, leading to
+the potential upending of the economy based on plentiful user-generated
+content.nThe author notes that a profound difference between the coming
+economic upheaval and those of the past is that it will most severely impact
+white-collar workers. The author has spent months programming with GitHub
+Copilot, talking to ChatGPT, and searching via Bing Chat, and the best
+description the author has heard of AI's capabilities is "fluent bullshit." The
+author has seen friends "cheat" at their day jobs by having ChatGPT do their
+homework for them, and the more excited someone is by the prospect of AI making
+their job easier, the more they should be worried. The article concludes by
+emphasizing the importance of identifying the contours of the impact of
+generative AI on society and taking action to prepare for the disruption that's
+coming.
+
+Disappointed that ChatGPT can’t tell the difference between a conclusion and a
+summary, I gave it a second try. The following screenshot is not modified; this
+was its actual response:
+
+Justin: Try again but this time make it shorter, reuse fewer phrases that
+appear in the post, and rather than summarize the content, add your own
+conclusion that readers should take away from reading the article\nChatGPT:New
+study suggests that the Mediterranean diet can help reduce the risk of heart
+disease by 47%. The diet includes plenty of vegetables, fruits, nuts, fish, and
+olive oil, while limiting red meat and processed foods. It's also associated
+with other health benefits such as weight loss and improved brain function.
+Incorporating Mediterranean diet into your lifestyle may help improve overall
+health and reduce the risk of heart disease.
+
+So, in conclusion: eat more olives. 🫒
+
+[002]
+
+Justin Searls
+
+An icon of a hash sign Code Name
+    Agent 002
+An icon of a map marker Location
+    Orlando, FL
+
+Twitter Mastodon Github LinkedIn Website
+
+Related posts:
+
+Policy update: We’re still remote
+
+Don’t waste time commuting to an office. Test Double will continue to be a 100%
+remote software development company that values autonomy and flexibility.
+
+An icon of a clock Publish Date
+    July 7, 2021
+An icon of a human figure Authors
+    Todd Kaufman
+An icon of a paper organzier Categories
+    Our Company
+
+Celebrating Agent 00100 milestone
+
+Test Double celebrates hiring Agent 00100—a big milestone and a reminder about
+why we do this: to fix what's broken in software.
+
+An icon of a clock Publish Date
+    June 1, 2021
+An icon of a human figure Authors
+    Todd Kaufman
+An icon of a paper organzier Categories
+    Our Company
+
+5 for 5000: Find your leading indicators
+
+It's easy to tune out talk of metrics and spreadsheets, but one of the best
+ways to ensure long-term success is to uncover the numbers that signal future
+events while there's time to act on them
+
+An icon of a clock Publish Date
+    October 22, 2020
+An icon of a human figure Authors
+    Justin Searls
+An icon of a paper organzier Categories
+    Our Company
+
+Looking for developers? Work with people who care about what you care about.
+
+We level up teams striving to ship great code.
+
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