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I don't really think that thinking of LLMs and related technologies as "Artificial Humans" is the right way to think about how they're going to be integrated in

I don't really think that thinking of LLMs and related technologies as "Artificial Humans" is the right way to think about how they're going to be integrated into workflows. What is going to happen is that people are going to be adopt these tools to solve particular tasks that are annoying or tedious for developers to do, in a way similar to the way tools like Ansible and Chef replaced the task of logging into ssh servers manually to install stuff, and aws replaced 'sending a guy out to the data center to setup a server' for many companies. And it's going to be done piecemeal, not all-at-once. Someone will figure out a way to get an AI to do _one_ thing faster and cheaper than a human and sell _that_. Maybe it's automatic test generation, maybe it's automatically remediating alerts, maybe it's code reviews. The scope of work of what a software developer does will be reduced until it's reduced to two categories: 1) Those tasks that it is still currently only possible for a human to do. 2) Those tasks which are easier and cheaper for a human to do. You don't even really need to think about LLMs as AIs or conscious or whether they pass the turing test or not, it's just like every other form of automation we've already developed. There are vast swathes of work that software developers and IT people did a few decades ago that almost nobody does any more because of various forms of automation. None of that has reduced the overall amount of jobs for software developers because there isn't a limited amount of software development to do. If you make software development less expensive and easier than people will apply it to more tasks, and software developers will become _more_ valuable and not _less_.

visarga 3y ago
> 1) Those tasks that it is still currently only possible for a human to do. 2) Those tasks which are easier and cheaper for a human to do. I agree, but "1" must include all tasks where a mistake could lead to liabilities for the company, which is probably most tasks. LLMs can't be held responsible for their fuckups, they can't be punished, they have no body. It's like the genie from the bottle, it will grant your three wishes, but they might turn out in a surprising way and it can't be held accountable. The same will apply for example for using LLMs in medicine. We can't afford to risk it on AI, a human must certify the diagnosis and treatment. In conclusion we can say LLMs can't handle accountability, not even in principle. That's a big issue in many jobs. The OP mentioned this as well: > even when AI coders can be rented out like EC2 instances, it will be beneficial to have an inhouse team of Software Developers to oversee their work Oversight is basically manual-mode AI alignment. We won't automate that, the more advanced an AI, the more effort we need to put in overseeing its work.
- estebank 3y ago
  "A COMPUTER CAN NEVER BE HELD ACCOUNTABLE THEREFORE A COMPUTER MUST NEVER MAKE A MANAGEMENT DECISION" — IBM slide from 1979.
  - visarga 3y ago
    hahaha funny Let me tell you a story - a company was using AI for invoice processing, and it misread a comma for a dot, so they sent a payment 1000x larger than expected, all automated of course because they were very modern. The result? they went bankrupt. "Bankrupted by AI error" might become a thing
    - chromanoid 3y ago
      Of course. It is like when a company goes bankrupt because they didn't establish good fire protection in their factory. Using AI automation has its risks that have to be mitigated appropriately.
    - erikpukinskis 3y ago
      That’s why you buy a cyber insurance policy.
  - esafak 3y ago
    Some might consider that a plus in the same way that "you can't get fired for choosing IBM" -- it's a way to outsource blame.
    - jazzyjackson 3y ago
      ted nelson calls it "cybercrud", blaming the machine as if it has the final say on the matter, "the system won't let me..."
  - deleted 3y ago
    [deleted]
- politician 3y ago
gtirloni 3y ago
I think this is the sanest comment I've seen about LLMs.
cogman10 3y ago
Exactly my take. I'd further state that LLMs appear to do ok with generating limited amounts of new code. Telling them "Here's a class, generate a bunch of unit tests" works. However, telling them "Generate me a todo application" will give mixed results at best. Further, it seems like updating and changing code is simply right out of their wheelhouse. That's where I think devs will be primarily valuable. Someone needs to understand the written code for when the feature request eventually bubbles through "Now also be able to do x". I don't think you'll be able to point an LLM at a code repository and instruct it "Update this project so that it can do feature X"
joenot443 3y ago
This is really well put and level-headed, I particularly like the comparison to AWS and in-field ops work.
karmakaze 3y ago
It's also paints a narrow picture of how results are described. I suspect that there will be a lot more by example like this, and iteration on the output, except that... where the inputs/outputs are multi-modal. Everything is going to be close enough, not fully spec'ed out. Full-self-driving is only the beginning of everything.
octopusRex 3y ago
I remember spending a lot of time writing comments for the exceptions when automation flagged code with a false positive. A lot of time.

visarga 3y ago

> 1) Those tasks that it is still currently only possible for a human to do. 2) Those tasks which are easier and cheaper for a human to do. I agree, but "1" must include all tasks where a mistake could lead to liabilities for the company, which is probably most tasks. LLMs can't be held responsible for their fuckups, they can't be punished, they have no body. It's like the genie from the bottle, it will grant your three wishes, but they might turn out in a surprising way and it can't be held accountable. The same will apply for example for using LLMs in medicine. We can't afford to risk it on AI, a human must certify the diagnosis and treatment. In conclusion we can say LLMs can't handle accountability, not even in principle. That's a big issue in many jobs. The OP mentioned this as well: > even when AI coders can be rented out like EC2 instances, it will be beneficial to have an inhouse team of Software Developers to oversee their work Oversight is basically manual-mode AI alignment. We won't automate that, the more advanced an AI, the more effort we need to put in overseeing its work.

estebank 3y ago
"A COMPUTER CAN NEVER BE HELD ACCOUNTABLE THEREFORE A COMPUTER MUST NEVER MAKE A MANAGEMENT DECISION" — IBM slide from 1979.
- visarga 3y ago
  hahaha funny Let me tell you a story - a company was using AI for invoice processing, and it misread a comma for a dot, so they sent a payment 1000x larger than expected, all automated of course because they were very modern. The result? they went bankrupt. "Bankrupted by AI error" might become a thing
  - chromanoid 3y ago
    Of course. It is like when a company goes bankrupt because they didn't establish good fire protection in their factory. Using AI automation has its risks that have to be mitigated appropriately.
  - erikpukinskis 3y ago
    That’s why you buy a cyber insurance policy.
- esafak 3y ago
  Some might consider that a plus in the same way that "you can't get fired for choosing IBM" -- it's a way to outsource blame.
  - jazzyjackson 3y ago
    ted nelson calls it "cybercrud", blaming the machine as if it has the final say on the matter, "the system won't let me..."
- deleted 3y ago
  [deleted]
politician 3y ago

gtirloni 3y ago

I think this is the sanest comment I've seen about LLMs.

cogman10 3y ago

Exactly my take. I'd further state that LLMs appear to do ok with generating limited amounts of new code. Telling them "Here's a class, generate a bunch of unit tests" works. However, telling them "Generate me a todo application" will give mixed results at best. Further, it seems like updating and changing code is simply right out of their wheelhouse. That's where I think devs will be primarily valuable. Someone needs to understand the written code for when the feature request eventually bubbles through "Now also be able to do x". I don't think you'll be able to point an LLM at a code repository and instruct it "Update this project so that it can do feature X"

joenot443 3y ago

This is really well put and level-headed, I particularly like the comparison to AWS and in-field ops work.

karmakaze 3y ago

It's also paints a narrow picture of how results are described. I suspect that there will be a lot more by example like this, and iteration on the output, except that... where the inputs/outputs are multi-modal. Everything is going to be close enough, not fully spec'ed out. Full-self-driving is only the beginning of everything.

octopusRex 3y ago

I remember spending a lot of time writing comments for the exceptions when automation flagged code with a false positive. A lot of time.