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How would they know if the code produced by ChatGPT had a side effect that effected their research? Isn't it risky to not fully understand the behavior of your

How would they know if the code produced by ChatGPT had a side effect that effected their research? Isn't it risky to not fully understand the behavior of your experiment?

kian 3y ago
I think in this case that problem even exists in their own code that they don't fully understand.
_giorgio_ 3y ago
Breaking down code in cells and asking chatGPT for help is quite easy and mostly foolproof, if you have enough will to learn things.
- dpflan 3y ago
  Indeed, build up the complexity from smaller, verifiable code components.
Balgair 3y ago
I get what you're saying, but the reality is that most researchers aren't any more code literate than the average person. Which is to say, they know just enough to make things worse. Hopefully those errors are removed before publication, but in my experience, they are not. Especially when it comes to coding. Also, a larger point is that this was fundamental research. A very hard thing. You're supposed to be getting it wrong most of the time. Then when you think you've got it right, you try to publish. Then you hope the reviewers actually read anything you wrote and catch all the errors [0]. But a lot of the time, errors sneak through and really only get discovered after a few years/decades. That's fine in the end, as science is a 'strongest-link' system where we really only care about the big and correct discoveries. 'Weak-link' systems are the opposite, they are governed by the small little falsehoods and errors. [0] Very unlikely, reviews almost always only review to see if the paper is of a high enough quality for the journal to include. I want to be clear on this point: Reviewers do not re-do experiments and typically do not go back through your math, let alone the code you used. Now, each field is different and has different standards, and those vary wildly. But generally, reviewers aren't there to make sure the science is right.
- kiba 3y ago
  It sounds like that researchers should just learn to properly code.
  - sdenton4 3y ago
    If the set theorists knew how to farm, then we wouldn't need the NSF to give them money.
    - kiba 3y ago
      Given that it is relevant to their research, they should consider learning how to code. Otherwise you'll be at the mercy of whatever autogenerated code that you happen to be using, since you literally don't have the skill to check if it's actually working. The other alternative is to work with a programmer.
      - melagonster 3y ago
        this is new technologies, and there are no scientists have salary higher than programmers
        Balgair 3y ago
        I want to echo this point. Our 'salary' was ~$24k/year. So, just enough to stay alive and for a beer on Fridays. If my co-researcher had the coding abilities he needed, he would have left. And, apologies if I wasn't clear enough here, we were grad students.
  - Balgair 3y ago
    Yeah, we were in a neuro lab. So your patch-clamping, pipette drawing, and tetrode dropping skills were a bit more prized. My co-researcher had never taken calculus, let alone any coding. Trying to get him up to speed with all the various skills he'd missed out on would have taken another 4 years of full time 'remedial' education. Of course, there was no time for that, let alone budget. I totally agree with you though. And that's why I really think that AI would have helped out a lot. It's not perfect in any way, but your velocity through all the pitfalls of learning is a lot faster with the AI helping out.

How would they know if the code produced by ChatGPT had a side effect that effected their research? Isn't it risky to not fully understand the behavior of your experiment?

kian 3y ago

I think in this case that problem even exists in their own code that they don't fully understand.

_giorgio_ 3y ago

Breaking down code in cells and asking chatGPT for help is quite easy and mostly foolproof, if you have enough will to learn things.

dpflan 3y ago
Indeed, build up the complexity from smaller, verifiable code components.

Balgair 3y ago

I get what you're saying, but the reality is that most researchers aren't any more code literate than the average person. Which is to say, they know just enough to make things worse. Hopefully those errors are removed before publication, but in my experience, they are not. Especially when it comes to coding. Also, a larger point is that this was fundamental research. A very hard thing. You're supposed to be getting it wrong most of the time. Then when you think you've got it right, you try to publish. Then you hope the reviewers actually read anything you wrote and catch all the errors [0]. But a lot of the time, errors sneak through and really only get discovered after a few years/decades. That's fine in the end, as science is a 'strongest-link' system where we really only care about the big and correct discoveries. 'Weak-link' systems are the opposite, they are governed by the small little falsehoods and errors. [0] Very unlikely, reviews almost always only review to see if the paper is of a high enough quality for the journal to include. I want to be clear on this point: Reviewers do not re-do experiments and typically do not go back through your math, let alone the code you used. Now, each field is different and has different standards, and those vary wildly. But generally, reviewers aren't there to make sure the science is right.

kiba 3y ago
It sounds like that researchers should just learn to properly code.
- sdenton4 3y ago
  If the set theorists knew how to farm, then we wouldn't need the NSF to give them money.
  - kiba 3y ago
    Given that it is relevant to their research, they should consider learning how to code. Otherwise you'll be at the mercy of whatever autogenerated code that you happen to be using, since you literally don't have the skill to check if it's actually working. The other alternative is to work with a programmer.
    - melagonster 3y ago
      this is new technologies, and there are no scientists have salary higher than programmers
      - Balgair 3y ago
        I want to echo this point. Our 'salary' was ~$24k/year. So, just enough to stay alive and for a beer on Fridays. If my co-researcher had the coding abilities he needed, he would have left. And, apologies if I wasn't clear enough here, we were grad students.
- Balgair 3y ago
  Yeah, we were in a neuro lab. So your patch-clamping, pipette drawing, and tetrode dropping skills were a bit more prized. My co-researcher had never taken calculus, let alone any coding. Trying to get him up to speed with all the various skills he'd missed out on would have taken another 4 years of full time 'remedial' education. Of course, there was no time for that, let alone budget. I totally agree with you though. And that's why I really think that AI would have helped out a lot. It's not perfect in any way, but your velocity through all the pitfalls of learning is a lot faster with the AI helping out.