1) AI makes really good code completion to make juniors way more productive. Senior devs benefit as well.
2) AI gets so good that it becomes increasingly hard to get a job as a junior--you just need senior devs to supervise the AI. This creates a talent pipeline shortage and screws over generations that want to become devs, but we find ways to deal with it.
3) Another major advance hits and AI becomes so good that the long promised "no code" future comes within reach. The line between BA and programmer blurs until everyone's basically a BA, telling the computer what kind of code it wants.
The thing though that many fail to recognize about technology is that while advances like this happen, sometimes technology seems to stall for DECADES. (E.g. the AI winter happened, but we're finally out of it.)
I could also see an alternative to #2 where it becomes increasingly hard to get a job as a senior dev when companies can just hire juniors to produce probably-good code and slightly more QA to ensure correctness.
You'd definitely still need some seniors in this scenario, but it feels possible that tooling like this might reduce their value-per-cost (and have the opposite effect on a larger pool of juniors).
As another comment said here, "if you can generate great python code but can't upgrade the EC2 instance when it runs out of memory, you haven't replaced developers; you've just freed up more of their time" (paraphrased).
No, programmers won't be replaced, we'll just add this to our toolbox. Every time our productivity increased we found new ways to spend it. There's no limit to our wants.
The famous 10 hour work week right? I am orders of magnitude more productive than my peers 50 years ago wrt programming scope and complexity, yet we work the same 40 hour week. I just produce more (sometimes buggy) code/products.
I live in a foreign country and study the language here. I frequently use machine translation to validate my my own translations, read menus with the Google Translate augmented reality camera, and chat with friends when I'm too busy to manually look up the words I don't understand in a dictionary. What I have learned is that machine translations are extremely helpful in a pinch, but often, a tiny adjustment in syntax, adding an adjective, or other minor edit like that will produce a sentence in English with entirely different meaning.
For context-specific questions it's even worse. The other day a stop owner that sells coffee beans insisted that we try out conversing with Google translate. I was trying to find the specific terms for natural, honey, and washed process. My Chinese is okay, but there's no way to know vocab like that unless you specifically look it up and learn it. Anyway, I felt pressured to go through with the Google translate charade even though I knew how the conversation would go. I said I wanted to know if this coffee was natural process. His reply was 'of course all of our coffees are natural with no added chemicals!' Turns out the word is 日曬, sun-exposed. AI is no replacement for learning the language.
State of the art image classification still classifies black people as gorillas [1].
I rue the day we end up with AI-generated operating systems that no one really understands how or why they do what they do, but when it gives you a weird result, you just jiggle a few things and let it try again. To me, that sounds like stage 4) in your list. We have black box devices that usually do what we want, but are completely opaque, may replicate glitchy or biased behaviors that it was trained on, and when it goes wrong it will be infuriating. But the 90% of the time that it works will be enough cost savings that it will become ubiquitous.
> For context-specific questions it's even worse. The other day a stop owner that sells coffee beans insisted that we try out conversing with Google translate. I was trying to find the specific terms for natural, honey, and washed process. My Chinese is okay, but there's no way to know vocab like that unless you specifically look it up and learn it. Anyway, I felt pressured to go through with the Google translate charade even though I knew how the conversation would go. I said I wanted to know if this coffee was natural process. His reply was 'of course all of our coffees are natural with no added chemicals!' Turns out the word is 日曬, sun-exposed. AI is no replacement for learning the language.
Does "natural process" have a Wikipedia page? I've found that for many concepts (especially multi-word ones), where the corresponding name in the other language isn't necessarily a literal translation of the word(s), the best way to find the actual correct term is to look it up on Wikipedia, then see if there is a link under "Other languages".
Looks like in this case it's only part of a Wikipedia page[0] but the Chinese edition is only a stub page. But your suggestion is absolutely spot-on. One of the things I love about Wikipedia is that it's human-curated for human evaluation, not a "knowledge engine" that produces wonky results.
I feel like you're neglecting to mention all the people who need to build and maintain this AI. Cookie cutter business logic will no longer need programmers but there will be more highly skilled jobs to keep building and improving the AI
But you need orders of magnitude fewer people to build and maintain the AIs then you do to manually create all the software running the world. And this is the unique peril of AI. The scale of capabilities of AI have the promise to grow faster than the creation of new classes jobs.
1) AI makes really good code completion to make juniors way more productive. Senior devs benefit as well.
2) AI gets so good that it becomes increasingly hard to get a job as a junior--you just need senior devs to supervise the AI. This creates a talent pipeline shortage and screws over generations that want to become devs, but we find ways to deal with it.
3) Another major advance hits and AI becomes so good that the long promised "no code" future comes within reach. The line between BA and programmer blurs until everyone's basically a BA, telling the computer what kind of code it wants.
The thing though that many fail to recognize about technology is that while advances like this happen, sometimes technology seems to stall for DECADES. (E.g. the AI winter happened, but we're finally out of it.)