Ask HN: How to Deal with ChatGPT Anxiety? | Hacker News Reader

Ask HN: How to Deal with ChatGPT Anxiety?

39 pointsscaredgpt65 comments

Since the release of ChatGPT I can't help it but be pessimistic about what the future holds for the field of software engineering. As a Junior developer I'm so thankful for the constant learning I'm experiencing at work and despite the low impact I have on issues/code base I'm always making sure that I take it one day at a time. I keep hearing friends and people online saying that the calculator didn't replace mathematicians and that Excel didn't replace accountants, but I can't help it to be anxious and think of ChatGPT replacing me and is making my imposter syndrome worse. I wanted to ask HN and see what they think of my fears, am I unreasonable? I know that I should not fear such tool but make sure I learn it and have it help me become more productive. Any tips or recommendations on how to deal with such anxiety/fear. Thank you in advance.

P.S: using throw away account, my main one has my email and website :/

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I just watched the "Making of Jurassic Park" documentary. They originally wanted to do most of the effects without computers. But one of the computer guys convinced them to try it, and it worked really well. They actually had to scrap a bunch of practical models they had built because the computer stuff was so good.

One of the guys in the documentary says "we were afraid they wouldn't need special effects people anymore. The director would just go on the computer and hit D for dinosaur and R for rain, and we'd be out of a job".

But it turned out that even with computers, they had to do a whole bunch of practical effects to get the rest of the footage. So when a computer generated dinosaur breaks through a fence, they had to make the fence break in just the right way so they could film it, and that took practical effects.

A lot of things have changed in the film industry and a lot of the old effects have gone away due to computers, but I don't think these big doom and gloom predictions people make are likely to come to pass.

I was listening to my favorite Martin Luther King Jr speech, The Three Evils of Society, and he's talking about concerns people have about job loss due to automation back in the 1960's. And computers did come and automate away all kinds of stuff, but people still found work in other areas.

My point is people have been worried about automation for a very long time. And it is interesting to think about, but I think a lot of the hyperbolic claims that it's going to destroy all these jobs overnight are a bit overblown.

A lot of the practical effects guys were in fact made redundant and replaced by CGI guys.

So, the industry as such survived, but not all the jobs did.

Oh absolutely. I just think the change was more gradual than the kind of overnight doom and gloom predictions we get from new technology a lot of the time. And you end up in situations where the previous practical effects workers might move to adjacent fields due to their industry experience, rather than just lose work entirely. Things will absolutely change, but that doesn't mean whole industries get obliterated overnight. What I am trying to say is some predictions are overly pessimistic about future job prospects, and that in reality a lot of predicted technological change is overblown. I suspect we will still have programming jobs in 20 years, and I would be surprised if we had fewer than we do today.

It’s nice to know it didn’t happen over night as GPT enthusiasts posit.

Yup the game will just change, fear is only a lack of imagination in this instance

In my tinkering with ChatGPT, I feel like I could rely on it approximately as I would rely on Stack Overflow. It may well offer me some good help on specific blocks of code -- largely serving as supplementary documentation -- but I wouldn't expect to be able to just ask it for an application and turn around and sell whatever it types out.

I mean, sure, like, I can imagine it could write some small applications, but only simple things that have been done over and over and that it can rehash based on its (admittedly massive) input data. Like maybe it could write a basic blogging application. But I doubt it could write a flight management application, much less adequately verify that it functions correctly and keep it up to date with the latest FAA regulations and navigation databases.

(On that note, since I do in fact work in aerospace ... considering how hard it is to certify any automated tools to use in avionics software development, I don't even want to think about how hard it would be to certify ChatGPT to churn out trustworthy avionics code!)

>(On that note, since I do in fact work in aerospace ... considering how hard it is to certify any automated tools to use in avionics software development, I don't even want to think about how hard it would be to certify ChatGPT to churn out trustworthy avionics code!)

I'm in the automotive industry and couldn't imagine it being used there either. I think companies who build tools like ChatGPT would be happy to leave it that way.

Understand how it works under the hood, and then don’t buy into the hype. ChatGPT is impressive for many reasons, but it basically consumes a bunch of data and spits out the most probable answer to a question based on that data.

It is kind of like linear regression on mega steroids, and you know with non-linear functions. Lots of really interesting ideas/applications but it is not an AI.

“it basically consumes a bunch of data and spits out the most probable answer to a question based on that data.”

Sounds like many people I know.

Sounds like the brain works like this. It would be a great hubris that any of us are different.

I’m not sure if the rest of the responses here are reflexive self-soothing, or just caught on the “ChatGPT” product itself, but unequivocally, your anxiety is warranted.

Code generation is moving extremely fast. This tech didn’t freeze in time at Codex or Copilot or ChatGPT. It’s one of the most exciting and difficult domains in AI and the smartest people are all set on solving it.

I’m sorry you’re feeling distress. You’re in good company. A lot of the world is going to have to deal with these problems very soon.

I just disagree, no one with any level of software accumen think AI generated code can write anything beyond a high school student copy and pasting.

The vast majority of software engineers are hired to work on is deeply complex in ways humans barely understand. It isn't small little JavaScript loops, it's huge multilayered executables with an incredible number of interdependences. It takes 6 months for people to just start to understand the internals of the software stack at most major companies. And that is working on it everyday, nothing is getting near passing the "Turing Test".

I don’t know what your argument is exactly, but it seems to be something like, “Software engineering is really hard so computers can’t do it.”

A variation of that argument props up most common AI skepticism. I don’t think there’s anything out right now that would convince you, but from what I know, everything you pointed out will be solved within the next few years.

Do you think systems like this will be able to do things like:

- Create a new programming language like Go or Rust?

- Create new infrastructure patterns like containers and kubernetes?

- Build tools like MapReduce/Arrow/Airflow or TF/JAX? Blockchain?

- Understand a new tool or framework it was not trained on?

- Decide when and how to refactor a code base because the mapping to the underlying problem has reached its limits?

- Write or modify compilers for emerging platforms like RiscV or WASM?

- Help to resolve a 1:1000 50x returned by my server?

Do today's ML models come close to the "why" these problems have?

I read the argument as "the hard part of software engineering is understanding the codebase and the world well enough to turn a description of a desired change in how a system should act into a diff that actually changes the system behavior in the intended way (and only in the intended way), not taking clear requirements and turning them into fresh code".

Of course humans aren't exactly great at that part either. But I do think I'd bet against, within the next 4 years, an AI tool being able to take tickets in the form

1. Expected behavior

2. Observed behavior

3. Steps to reproduce

and produce a changelist that legibly fixes the problem, and does not break anything else, at a level better than a typical junior software developer. I think the ability to do that is probably AGI complete.

I think you’re right that code models are a vital research path toward AGI.

The steps you elucidated are all expressible in natural language, and we see models like Codex Edit making headway there. One of the most fascinating parts of this is that once access to the known baselines are provided to high-level engineers, they then go on to do much more than what the models alone can do.

The main hinderance to enterprise was compliance but the move toward Azure, etc, will dissolve those barriers this year.

Well I'm certainly looking forward to AI doing the fundamental research needed to model the behavior and work with certain hardware components, or writing clock cycle exact embedded code for complex applications, or debugging a timing problem in an async system... /s

Let's get real, nothing except simple crud apps are getting replaced, if any, anytime soon.

An AI being able to create arbitrary computer programs and work productively in an arbitrary codebase sounds basically like an AGI or something approximating it. Not sure if that's what you're implying is a few years away. I do think it's inevitable, but the time horizon still doesn't seem clear to me at all

same as GP here. your argument does not make any sense to me.

> Code generation is moving extremely fast

Correction, it was moving fast a few years ago, it isn't moving fast right now. I can understand being a little worried a few years ago, but today? They are clearly stuck, we know the capabilities of current models and they aren't threatening anyone, if it was easy to improve then they would have made huge strides from a couple of years ago but they haven't.

That’s objectively wrong.

Codex, AlphaCode, both surpassed by CodeRL on the challenging APPS benchmark last year. Meta working on InCoder. Microsoft working on UniXCoder…

Future research directions are pretty clear from where we stand. That includes iterative methods, reinforcement learning, text diffusion, etc. No one is stuck.

Codex just barely surpassed it on easy questions but did worse on harder ones. AlphaCode is significantly better on harder questions, but significantly worse on easy questions. That isn't extremely fast development, they are mostly moving sideways, trying to improve one part of the metric hurts the others.

https://paperswithcode.com/sota/code-generation-on-apps

Development in these areas was very fast in the 3 years between transformer networks were invented and roughly GPT 3 was done. But in the 3 years since GPT-3 not much has changed, we see a lot of "we applied a large network to a new problem and found X" since then, but that isn't new performance, its just a new result with the same thing we had around back then.

unixcoder… they had to name it like that, right?

I had a teacher in undergrad (over 20 years ago) who said UML and code generation are getting so advanced, 5 years out, you likely won't be coding anymore.

In the early 00s, there was tremendous outsourcing going on. Some people said Western programmer salaries will collapse.

So your anxiety is nothing new. I think of ChatGPT-like tech to be like grammar checker. It will make your job easier.

Also, it is interesting to consider how chip design works these days. My understanding (as a software person) is that there are more people doing test-verification harnesses/QA of sorts than designing the basic blocks. This model may be how things go in software.

Exactly this. Even previous to that, we were told Lisp and Rapid Prototyping would end programming languages like C. And yet C is still here, although it looks quite different and has branched out a whole lot. And Lisp is still here, but has nowhere near the legs even if it is so much nicer to work with. Programming line-by-line is still the de facto way to go even though Rapid Prototyping folks said it would not be.

It’s an issue of: are you here to take from the world or contribute to it? If a robot is able to do what you’re currently doing just as well, then great, you can work on higher level stuff and we can all contribute more to society.

It’s always been the same fear with all tech revolutions: people thinking there won’t be any work left to do, afraid they won’t find a way to sustain themselves. When work is replaced, there is always new one to do, and it usually simply represents an upscaling of global GDP. It’s a good thing. We are facing massive global challenges and could use greater efficiency and expression of our collective intelligence to address them.

As long as you stay willing to learn, you will always discover ways to contribute to society and be relevant. But if you’re attached to “I learned X and I hope it gives me bread for the rest of my life,” you probably chose the wrong century :-)

One anecdote. I just use ChatGPT to help with a relatively complex project. But that depended on a number of relatively simple scripts around automating some AWS functional in Python using boto3 - the AWS SDK.

It really did help keep me in the flow. While I was designing the entire system and documenting it, I would just give ChatGPT the requirements in a few sentences and it spit out correct code.

Honestly it did take the place of what I would have formerly thrown at an intern/junior dev.

Will it “replace” the need for junior devs? I am going to say the unpopular opinion - yes.

But coding has always been the least important part of my job. Knowing what to code and solving XYProblems is where the money and differentiator are.

If so, how can a junior dev level up while making money?

Honestly, that’s the age old challenge - how to break the can’t get a job <-> don’t have experience cycle.

I’ve never been a “junior developer”. By the time I graduated from college back in antiquity in 1996, I had already been a hobbyist for a decade and my first job was designing and developing a relatively complicated data entry system in C. So my first and second jobs were already mid level developer type work.

That’s not bragging. It hurt me in the long run. I stayed at my second job too long and became an “expert beginner” and had to start over and learn best practices from others 12 years later.

But now, isn’t the general advice “grind leetcode and work for a FAANG” (tm) r/cscareerquestions.

GPT-3 is legitimately the closest thing I've ever seen in my lifetime to what people 30 years ago saw when they first witnessed NCSA Mosaic, and I'm amazed to see people in tech downplaying its significance the way they are. Many of these same people were in awe of the iPhone, which while a legitimate technological breakthrough, IMO will not prove nearly as disruptive as this tech. And probably many of these same naysayers foolishly bought into the hype around crypto. But here you have something that is going to be massively disruptive, and not necessarily in a good way, and instead of sounding the alarm, you have "crying wojak mask"-tier comments reassuring each other that everything will be fine.

GPT is going to put millions of writers, artists, and programming/IT professionals out of work, full-stop. It will also make Sam Altman and other tech billionaires even richer than they already are, and worsen already extreme wealth inequality. It's obvious enough at this point that I can't believe other people don't see it. Just look at how rapidly the technology is being adopted, even by normies.

I'm not going to give the OP life or career advice, but for my part, I am actively trying to invest substantial amounts of my money into the firms I think will win the AI revolution, at least to protect myself form the downside.

I also think people should consider a "starve the beast" strategy, at least on principle. Is it really wise to be publishing art under a CC license, or code under an OSI-approved license, knowing that it will just be fed into one of these LLMs for profit (of which you will have no share), and against which you may have to compete for a job in the future? Heck, it seems like even copyrighted content (if published on the internet) isn't necessarily safe, if the Getty watermarks in DALL-E outputs are anything to go by.

Might be biased from the software domain I work in (embedded/networking), but chatgpt-like software development seems far more likely to be an aid or informational rather than authoritative (read: auto-generating entire programs).

For simple programs where the requirements are trivial, sure. But for any software with a bit of complexity, that is integrated with other software of similar complexity, I don’t see how this becomes a job destroyer. In most software roles I’ve worked, big and small, the actual development is largely factoring and balancing a ton of requirements (security, performance, business needs/timelines, customer asks, hardware constraints, operations, on and on). You’d probably have to write a hell of a chatgpt prompt to explain the entirety of what you need to replace the human factors of evaluating all of that :-)

Edit: I like the comment below about the movie industry. The evolution of technology has pushed the boundary of whats possible, but still have a lot of the same needs in terms of people.

I use a number of GPT-based products on a day-to-day basis and find them incredibly useful, so unfortunately I can't assuage your concerns by downplaying current and future language model technology.

The great news is that many of these products are free or relatively inexpensive, so you can start gaining experience with them today.

The best way to future-proof your career in the event that language models become widely applied is to make it one of your core competencies. :)

If you start practicing today, you'll quickly be at the front of the curve. And try to practice deliberately, for example gaining experience with:

- how to give it all the necessary information and nothing superfluous,

- how to effectively articulate the desired deliverable and its requirements,

- how to guide it through iterating on the solution and when to stop (often I do the first 10% of the work, then the model does the next 60% of the heavy lifting, and then I finish off the last 30% to fix its mistakes and tailor the result)

> number of GPT-based products on a day-to-day basis and find them incredibly useful

mind sharing what those might be?

There are all kinds of similar stories in history. The synth didn't replace the guitar, even if there isn't much guitar in radio pop music these days. Guitar abounds outside of pop, and isn't entirely diminished from pop either way. Tablets and dumb terminals with network-based operating systems didn't replace the local application, even after we've reached for the Clouds. MIDI didn't replace human orchestras. Aibo and Tamagotchi didn't replace live pets. Etc. Etc.

Toys are toys. Tools are tools. And ChatGPT is a toy quickly becoming a tool that also won't replace people.

It is made to look like it knows and understands. It has mainstream packaging that everyone and their dog can use and postulate on.

However, it doesn’t understand anything of its underlying subject matter.

It simply (!) has accumulated a wealth of information that it chooses the best answer for. Of course, that is very impressive but a thinking machine it is not.

My anxiety is not on the AI but the ability to game human kind and normalization of content. You think everything is quite similar now? Let’s see how it can determine what is new, real authentic human content versus bot rehashing?

“It simply (!) has accumulated a wealth of information that it chooses the best answer for. Of course, that is very impressive but a thinking machine it is not.”

I’m very confused. I don’t think I’m different than this.

If I ask you a question that requires you to have a set of dependencies to solve you would need to understand the meaningful outcome of them as they were inputs into the next issue. You understand the ‘thing’ not just the associated words to reply. ChatGPT has zero knowledge of the world other than language.

Behind your thinking is a lot of heuristics built up from decades of experience, along with the ability to use logic in addition to the information you've picked up. ChatGPT still sucks with anything requiring logical inference.

As do I.

But you know you do, chatGPT doesn’t

AI doesn't improve along a smooth curve. Generally speaking there are leaps that coincide with epiphanies followed by large periods of slow incremental improvement.

I wouldn't be too worried about another quantum leap for atleast another few years and I highly doubt that will be enough for AI to generate code.

In the long term it's definitely something to keep in mind and be aware that you should be moving up the stack in terms of critical thinking so you aren't left as a code monkey 20 years from now where AI will definitely be eating your lunch.

No need to worry. If and when the time comes that you are replaced by AI, you will have enough sense, courage and loved ones to navigate out of it. You won't be alone, thousand just like you will have the same problem. Trust your future self. That's my advice.

In the meantime if you think another skill or business might come in useful, do it. But do it calmly if possible. Anxiety will never help you do something better or more. Ever. If calm is not possible for you, then that is a skill I suggest you start cultivating.

> If calm is not possible for you, then that is a skill I suggest you start cultivating.

It took me years to figure this out and it was hard. But life has been better since I've chilled out.

As I'm sure you must know, ChatGPT isn't always entirely accurate. People won't use it for things if they know it still has a scope of error. While it may provide great insights or tips on a certain topic, it is just surfing the internet and collating this data.

I don't think it'll rid you of your jobs, I think it'll just open up new types of jobs for everyone.

ChatGPT is Wikipedia all over again. It'll give you some really good material to work with, but if you plagiarize it blindly you're gonna get called out for the inaccuracies. It does not analyze its output, so if it has ever seen something that says 1+1=3, or a pattern that suggests it is even possible, it'll happily tell you that this is the case.

Always check your work, even if something that sounds compelling online gave it to you for free!

Yes. But ChatGPT gets me closer to correctly working code that meets my requirements than a random Google search.

For the longest though it got the answer wrong “what is 123 times 456”. But it did turn a Python+boto3 40 line script into a correctly working Node+JS/AWS SDK script for me.

Yup, that matches my experience.

When you realize how conversational ChatGPT is, you adjust the way you use it in order to get good code from it. It doesn't take long to know instinctively what things it gets wrong. When it happens, I also give feedback because I'd love for this to work more fully when it is no longer beta.

I got it to translate a C encryption algo into Lisp, and ended up learning from its descriptions how C doesn't have (atom), but it useful here because <yadda yadda>. When I asked it how C would do (atom) it gave me a sample that would work in the original C code I gave it, but then stated that while it should work in that case, it probably wouldn't in others because <same yadda yadda as earlier>.

That sold me on it being a good coding partner.

> As I'm sure you must know, ChatGPT isn't always entirely accurate. People won't use it for things if they know it still has a scope of error.

And how is that any different than your average junior dev?

AI code generation will make your skills more valuable, not less. Your work will change, as it moves to architectural design and code vetting, but will still be dependent on your knowledge of and experience in software engineering.

The increase in the productivity of people developing software will lead to far more software being generated, not fewer software developers.

There will always be a need for the boss to have someone else make sure the work is done correctly. And like any contractor knows. What the boss / client says they wants isn’t always what they really want. Also until humans aren’t using the software we need it to be usable. A lot of the code I’ve seen generated is bland and engineering build at best.

I really question how impressive it would be for generating new, unknown programs. ML is based on prior knowledge, and if it hasn’t been invented before, it would get lost real quick.

I saw a chatGPT redux reducer was for a todo app. That probably has 50 examples online. The VM running inside chatGPT also has a rich set of examples to use online from people teaching Linux cli interface.

You see this with GitHub’s autopilot. Very impressive stuff for trivial things, but it breaks down quick with any complexity.

Nobody really gets paid to write trivial programs like that since whomever could just copy it.

A few years ago everyone was saying that low code tools and "citizen development" will destroy the industry. The reality was that they just allowed more small players to increase their efficiency / productivity. We're still here today.

As an additional moat, any non-trivial business has a lot of context and tacit knowledge that will not be within the corpus of "knowledge" that AI models have and there will be many non-technical hurdles (regulatory, political etc) before any of that business context can be fed into the model, if ever. Remember these models only have access to public information at this point in time.

Think about what these LLMs can do better than people. They can answer questions (or generate code) about a huge range of topics, fast and plausibly. But, if I asked you any of these questions, you could find an answer by Googling, and you as a human would be able to say a lot more about whether it was true or correct in a useful way. ChatGPT is an accelerated version of that person who can BS their way through any conversation or job interview, but who ultimately is focused on appearing smart, not being smart. Future models may scare me more.

I am glad people are talking about this. I have been feeling like this for the past couple of weeks. It's a difficult thing as I really enjoy coding but it feels like that part of the job will be changing in the future.

I think it's all about being adaptable, being here on HN and thinking about these things will put you ahead of others who simply don't see the change coming. Unfortunately we can't put the AI genie back in the bottle and we just have to be ready to adapt.

Software productivity, though hard to objectively measure, probably gone up quite a few magnitudes.

People used to program by flipping switches or punching holes in punch cards. We made assembly languages, higher level languages, optimizing compilers, libraries of commonly used code, and so on.

There is presumably some tipping point where we become so productive that fewer people are needed. It hasn't happened yet, and there's no good way to know if and when it will happen.

I'm zero percent concerned about a computer being able to synthesize and build at a certain higher level.

I've 100% accepted that AI will displace tons of jobs and lead to the near dissolution of meaning and discourse "online" (as if as anything else will exist). And Im just trying to be happy day to day until that and its secondary effects come to pass or until one of other countless seemingly incoming disasters happens.

Before Excel, there were entire teams of people manually maintaining a paper spreadsheet. What the popularity of Excel did long term was increase the demand for worksheets. When something like spreadsheets or concrete becomes cheaper, sometimes demand spikes instead of conforming to past trends. I feel the same for modern AI generated work and the continued need for humans to refine the output

ChatGPT has a habit of making up references and spewing bullshit, it's not ready for prime time.

Someone has to ride herd on this AI stuff and make sure it stays sane. It'll take a while for everyone to figure that out, but we'll get there.

And that’s completely irrelevant to the question. It’s not hard to prove whether ChatGPT gave you the write code - you just paste it in your IDE and verify the results.

Yes I had ChatGPT once make up a function when I asked it to write a Python script that listed all of the accounts in an AWS Organization.

It completely made up a function on the organizations class called “get_accounts_by_tag()”.

It took one minute to realize it was a bullshit when I got an error and after I told it that answer wasn’t correct, it gave me a working script using a set of boto3 calls and AWS functionality I had never heard of. But it was correct.

Personally I plan to see where it goes and hope that society doesn't collapse as a result of everyone being put out of work due to widespread adoption of AI.

I'm getting too old to fight in the robot uprising when it comes.

correctness and verification are not close to being solved. it's feasible that AI will increase individual developer productivity and narrow the field. it's also possible, and probably more likely, that increased productivity and capability will just increase the complexity of software; that may be good (more interesting problems and broader real-world applications) or bad (overengineered monstrosities).

Don't worry. If you are good at your job, you will be fine. Software engineering is so much more than just boilerplate coding.

> ChatGPT replacing me

If you could look into the future and know you’re right about this, what would you do today?

After writing part of the comment below, I threw this at GPT-3 to finish it off. It did okay-ish :D (the prompt ends at "REWRITTEN COMMENT:")