Datorprogrammerare
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Beräknad automatiseringsrisk
Hög risk (61-80%): Jobb i denna kategori står inför ett betydande hot från automatisering, eftersom många av deras uppgifter lätt kan automatiseras med nuvarande eller nära framtida tekniker.
Mer information om vad detta betyg är, och hur det beräknas finns tillgängligt här.
Användarundersökning
Våra besökare har röstat för att det är troligt att detta yrke kommer att automatiseras. Detta bedömning stöds ytterligare av den beräknade automationsrisknivån, som uppskattar 70% chans för automation.
Vad tror du är risken med automatisering?
Vad är sannolikheten att Datorprogrammerare kommer att ersättas av robotar eller artificiell intelligens inom de närmaste 20 åren?
Känsla
Följande graf inkluderas där det finns en betydande mängd röster för att ge meningsfull data. Dessa visuella representationer visar användaromröstningsresultat över tid och ger en viktig indikation på sentimenttrender.
Känsla över tid (kvartalsvis)
Känslor över tid (årligen)
Tillväxt
Antalet 'Computer Programmers' jobböppningar förväntas att minska med 9,6% fram till 2033
Total sysselsättning och uppskattade jobböppningar
Uppdaterade prognoser beräknas 09-2025.
Löner
I 2023 var den medianårliga lönen för 'Computer Programmers' 99 700 $, eller 47 $ per timme.
'Computer Programmers' betalades 107,4% högre än den nationella medianlönen, som låg på 48 060 $
Löner över tid
Volym
Från och med 2023 var det 120 370 personer anställda som 'Computer Programmers' inom USA.
Detta representerar cirka 0,08% av den anställda arbetskraften i hela landet
Sagt på ett annat sätt, runt 1 av 1 tusen personer är anställda som 'Computer Programmers'.
Arbetsbeskrivning
Skapa, ändra och testa koden och skripten som gör att datorprogram kan köras. Arbeta utifrån specifikationer som tagits fram av mjukvaru- och webbutvecklare eller andra individer. Kan utveckla och skriva datorprogram för att lagra, lokalisera och hämta specifika dokument, data och information.
SOC Code: 15-1251.00
Kommentarer
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So its pretty hard to train an ai that can be adapted to every it infrastrcuture. It also is a risk since it would mean giving ai access to 100% of the system, which is a concerning security risk.
One day there may be an ai that can do that, but even then it will require programmers that maintain the ai and check/test code that it wrote since someone will need to take responsbility for what the ai does. And since i cant even gurantee my own code to work at all times in different cases, I sure as hell wont take responbility for some ai code no matter how good the ai is
PR review is getting handled by AI now. Gemini, Copilot, and CodeRabbit are taking over.
Security has always been weak. They just force 2 factor and call it a day. Look at the NPM supply attacks because one guy took the bait on an email.
Please take into account the trajectory of progress rather than the current state of things.
But though AI (= LLMs) has gotten better in the sense of creating more complex outputs, it otherwise suffers from exactly the same problems as early versions: no compositionality, no continual learning, no consistency, and no self-correction.
If you ask it to fix a certain bug fix in a complex codebase, you have a high chance that it also starts to change something completely unrelated. It doesn't really grasp how precisely elements make up the complex whole; instead, it applies pattern-matching, by which it gets misled. You can waste days with AI on what would be a five-minute manual fix.
Also, junior devs' job isn't to churn out mediocre code for generic, long-solved tasks or create the 1000th to-do list app. Instead, they get onboarded and are supposed to familiarize themselves with your codebase to improve it. But you know that "PT" in ChatGPT stands for "pre-trained?" So AI doesn't learn anything new. AI is like suffering from anterograde amnesia.
Anyway, neither apps nor code are like a commodity where "more is better". In the end, the point is to create something new. Otherwise there is not much point: just use an already existing and tested library. And it's exactly the "new" part where AI sucks because it struggles to transcend its training data.
So no, AI is incapable of replacing junior devs.
It would have a lot of immediate positive effects if AI worked like you describe: it would insanely empower open-source projects (often lacking maintainers) to fix all their long lists of bugs or introduce new features. But this is not what we observe at all. Because AI is overhyped and underdelivers.
-> MNCs keep laying off juniors while recording profits. Why? Because they have trained their AIs to do the jobs of 100s of people. Where they needed 100 people, they only need 1 now.
-> OpenAI just hired ex-bankers to develop financial AIs that will eventually replace junior finance professionals in their company. Others are following suit.
-> Salesforce has openly admitted to cutting jobs because of AI. So have many other top companies.
Don't get me wrong, I think AI is way off from completely replacing digital labour. I almost agree with you on most of your points.
But it's getting there, and it's getting there quickly. It's only a matter of time until researchers develop a new system that supersedes transformer models. And judging by the Billions being burned every day on AI research, it's almost inevitable.
I think you'll find the "AI 2027" paper very interesting. Please do have a read. And thanks for your reply :)
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