I’m not sure what it would even mean to teach something substantive about ML/AI to someone who lacks the basic concepts of programming. Like, if someone with zero programming experience and median-high-school level math background asked me how to learn more about ML/AI, I would say “you lack the foundations to achieve any substantive understanding at all, go do a programming 101 course and some calculus at a bare minimum”.
For instance, I could imagine giving such a person a useful and accurate visual explanation of how modern ML works, but without some programming experience they’re going to go around e.g. imagining ghosts in the machine, because that’s a typical mistake people make when they have zero programming experience. And a typical ML expert trying to give an explain-like-I’m-5 overview wouldn’t even think to address a confusion that basic. I’d guess that there’s quite a few things like that, as is typical. Inferential distances are not short.
Perhaps as an example, I can offer some comparisons between myself and my co-workers.
None of us are programmers. None of us are ever going to become programmers. We have reached a point where it is vitally necessary that people who are not programmers reach a level of understanding that will allow them to sensibly make the decisions they are going to have to make about how to use machine learning models.
Compared to them, I am much more able to predict what LLMs will and won’t be good at. I can create user prompts. I know what system prompts are and where I can read the officially published/leaked ones. I have some understanding of what goes on during some of the stages of training. I understand that and at least some of the reasons why this computer program is different from other computer programs.
I have encountered the kind of responses I’m getting here before—people seem to underestimate how much there is that it is possible to know in between ‘nothing’ and ‘things you cannot possibly comprehend unless you are a programmer’. They also don’t seem to have a sense of urgency about how vital it is that people who are not programmers—let’s say, doctors—are enabled to learn enough about machine learning models to enable them to make sensible decisions about using them.
they’re going to go around e.g. imagining ghosts in the machine, because that’s a typical mistake people make when they have zero programming experience
Tangential point, but I’m skeptical this is actually a very common error.
I’m not sure what it would even mean to teach something substantive about ML/AI to someone who lacks the basic concepts of programming. Like, if someone with zero programming experience and median-high-school level math background asked me how to learn more about ML/AI, I would say “you lack the foundations to achieve any substantive understanding at all, go do a programming 101 course and some calculus at a bare minimum”.
For instance, I could imagine giving such a person a useful and accurate visual explanation of how modern ML works, but without some programming experience they’re going to go around e.g. imagining ghosts in the machine, because that’s a typical mistake people make when they have zero programming experience. And a typical ML expert trying to give an explain-like-I’m-5 overview wouldn’t even think to address a confusion that basic. I’d guess that there’s quite a few things like that, as is typical. Inferential distances are not short.
Perhaps as an example, I can offer some comparisons between myself and my co-workers.
None of us are programmers. None of us are ever going to become programmers. We have reached a point where it is vitally necessary that people who are not programmers reach a level of understanding that will allow them to sensibly make the decisions they are going to have to make about how to use machine learning models.
Compared to them, I am much more able to predict what LLMs will and won’t be good at. I can create user prompts. I know what system prompts are and where I can read the officially published/leaked ones. I have some understanding of what goes on during some of the stages of training. I understand that and at least some of the reasons why this computer program is different from other computer programs.
I have encountered the kind of responses I’m getting here before—people seem to underestimate how much there is that it is possible to know in between ‘nothing’ and ‘things you cannot possibly comprehend unless you are a programmer’. They also don’t seem to have a sense of urgency about how vital it is that people who are not programmers—let’s say, doctors—are enabled to learn enough about machine learning models to enable them to make sensible decisions about using them.
Tangential point, but I’m skeptical this is actually a very common error.