>Being anti AI/anti LLM is solidly in the Luddite camp; there’s really no more debates to be had. Every serious inquiry shows productivity gains by using ai.
These two sentences appear to be at odds with one another.
These two sentences appear to be at odds with one another.
Even putting the sophistry aside your argument is incomplete because you never defined what "productivity" means in this context or how it can be quantified. I would never dispute that a pseudo-random bullshit generator can shit out javascript faster than any human, but that's not necessarily productive.
i wait
### An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation We evaluate TESTPILOT using OpenAI’s gpt3.5-turbo LLM on 25 npm packages with a total of 1,684 API functions. The generated tests achieve a median statement coverage of 70.2% and branch coverage of 52.8%. In contrast, the state-of-the feedback-directed JavaScript test generation technique, Nessie, achieves only 51.3% statement coverage and 25.6% branch coverage. - *Link:* [An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation (arXiv)](https://arxiv.org/abs/2302.06527)
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### Field Experiment – CodeFuse (12-week deployment) - Productivity (measured by the number of lines of code produced) increased by 55% for the group using the LLM. Approximately one third of this increase was directly attributable to code generated by the LLM. - *Link:* [CodeFuse: Generative AI for Code Productivity in the Workplace (BIS Working Paper 1208)](https://www.bis.org/publ/work1208.htm)
The LLM’s better have written more code, they’re a text generation machine!
In what world does this study prove that the LLM actually accomplished anything useful?
LOC does have a correlation with productivity, as much as devs hate to acknowledge it. I don’t care that you can provide counterexamples to this, or even if the AI on average takes more LOC to accomplish the same task - it still results in more productivity overall because it arrives at the result faster.
If you want to measure time to complete a complex task, then measure that. LOC is an intermediate measure. How much more productive is "55% more lines of code"?
I can write a bunch of garbage code really fast with a lot of bugs that doesn't work, or I can write a better program that works properly, slower. Under your framework, the former must be classified as 'better' - but why?
I read the study you reference and there is literally nothing in the study that talks about whether or not tasks were accomplished successfully.
It says: * Junior devs benefited more than senior devs, then presents a disingenuous argument as to why that's the senior devs' fault (more experienced employees are worse than less experienced employees, who knew?!) * 11% of the 55% increase in LOC was attributed directly to LLM output * Makes absolutely no attempt to measure whether or not the extra code was beneficial
This is a terrible way to do research!