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I think the zero sum, "use AI everywhere" vs "don't use it at all" are both to be avoided. The wise path is somewhere in the middle. On avoiding it, if your c

by jmfldn 4y ago

I think the zero sum, "use AI everywhere" vs "don't use it at all" are both to be avoided. The wise path is somewhere in the middle. On avoiding it, if your competitors are getting massive productivity gains from AI tools, your hand-crafted, artisanal code is going to be expensive and your customers will vote with their wallets.

rf15 4y ago
Exactly. I am absolutely no fan of the new AI products, and the only question you have to answer for yourself is: can you leverage this technology for what you are trying to do? For me the answer was "yes", and I now enjoy having copilot around to dynamically type boilerplate I'd need much longer to type and fill out myself.
- goldfeld 4y ago
  Why would you be absolutely no fan of a sure technological improvement? Is it because of the personal threat to professionals? Not commenting personally on you here, but I am very surprised at programmers' lack of nose for opportunities and how, after realizing GPT could do coding even before replacing retail and industry jobs, coders are completely on the defense. Is it a threat to job availability and security? Yes, but programmers have long been to other professionals (doctors even?) what AI is now to them (I was a coder too). Well, tough luck, the world changes and fast, better to try to create and carve out a new job or business idea for yourself than stand on denial of something that, good or bad, could either make or break humanity, but humanity has no say on the inexorable progress of ideas. This actually is science right here, don't tech people embrace science, or only when the collateral damage is elsewhere and not on them?
  - rf15 4y ago
    The technology's hype precedes it whenever you try to engage with it. On the surface, it looks a lot like the bitcoin hype, and if you remember IBM Watson you might get the idea that nothing much will come of it. So for me, I will keep using it, but I have nothing but disdain for the people worrying about AI overtaking the world, claiming this will revolutionise everything/etc.. Especially since this technology is almost good enough to tempt lay people to believe the statistically related words to your query would mean anything. In fact, iirc this has already happened and e.g. caused a suicide.
  - zelphirkalt 4y ago
    I think many are not actually against usage of these kinds of ML models in general, but against what is done using them right now: Code laundering, violation of licenses, intransparency, training on personal data, no responsible person to talk to, no way of having data removed, that one does not want in the model or the model to train from, and more. Any of these can lead to dystopia. When we use computer vision to identify benign or malignant tumors, we might cost someone a job, but at least what that model was trained on can be known and we are not leaking personal data in the model and probably there is no violation of licenses or similar to the data that was used to train the model. The model is very limited in output. The consequences are kind of simple to monitor or predict, because the model can only be used in its specialized area of use. With the new crop of ML models the situation is different. Lawmakers were asleep while these things became popular and there is no knowing, how it will all pan out, because the output is of a more general nature, that can touch any subject, any area of expertise. No one knows what they have been trained on and whether there is anything in that training data, that should not have been used, and there is no simple way (that I know of) to operate out any such data after training the model.
gavinhoward 4y ago
Maybe, but that's a bet I'm willing to take. Here's the rub: if my competitors are going to realize "massive productivity gains," where are those gains actually coming from? Are they coming from the time it takes to type? No, because typing is a small portion of the time we spend as programmers. Are the gains coming from the time spent on design and architecture? Maybe, but that means my software will have better architecture, and I will have better velocity in the long run. (I have real-world experience with this, by the way; it takes me, on average, less than an hour to fix bugs in my bc nowadays. Architecture matters for long-term velocity.) Are the gains coming from the time squashing bugs? No, this is where AI would decrease productivity because you have to carefully review outputs to ensure there are not any bugs. In essence, the productivity gains will only happen the less that my competitors actually review and clean up the code from these tools. The less they do that, the lower the quality. The lower the quality, the slower their long-term velocity will be. "A little bit of slope makes up for a lot of y-intercept." [1] [1]: https://gist.github.com/gtallen1187/e83ed02eac6cc8d7e185 https://gist.github.com/gtallen1187/e83ed02eac6cc8d7e185
- jmfldn 4y ago
  Honestly I wish you well in this approach, I just worry that ignoring this completely may be too costly. I'm just advocating a very cautious middle path. For now, these tools are just code helpers to me (and right now I barely use them for that), but the moment I sense a genuine advantage to using them in my job, and I don't think it undermines my engineering, I think I'll have to engage further. Undermining for me means, reducing software quality, reliability, my own understanding. To the extent that I can work faster though, and even improve on those metrics, so much the better. The semi-near future to me (5-10 years?) , breathless hype-aside, looks like one where quite a lot of coding is automated with machines able to range over whole codebases and build higher level models of the software, and then getting into architectural system-design suggestions. I also see them linking up with company docs to build up a model of the whole domain. This doesn't need AGI, it's just an extension of what we have now, and I can't see it being anything other than a game changer. Forget ChatGPT, imagine your own private LLM, trained on your code and business, with all the weird glitches these prototypes have currently largely gone. You, the expert architect, are still needed, but you've now added a superpower to your tool chain.
BeefWellington 4y ago
> I think the zero sum, "use AI everywhere" vs "don't use it at all" are both to be avoided. The wise path is somewhere in the middle. I suspect this is one of those tech Pandora's box moments where it's largely irrelevant what actual tech people think about this; executives will be swayed to the "use AI everywhere" side of things purely as a cost-cutting measure. Any productivity gained via the use of AI will be leveraged not to improve overall productivity (in the medium to long term) but instead leveraged against employees to to shed salaries.

by jmfldn 4y ago

rf15 4y ago

Exactly. I am absolutely no fan of the new AI products, and the only question you have to answer for yourself is: can you leverage this technology for what you are trying to do? For me the answer was "yes", and I now enjoy having copilot around to dynamically type boilerplate I'd need much longer to type and fill out myself.

goldfeld 4y ago
Why would you be absolutely no fan of a sure technological improvement? Is it because of the personal threat to professionals? Not commenting personally on you here, but I am very surprised at programmers' lack of nose for opportunities and how, after realizing GPT could do coding even before replacing retail and industry jobs, coders are completely on the defense. Is it a threat to job availability and security? Yes, but programmers have long been to other professionals (doctors even?) what AI is now to them (I was a coder too). Well, tough luck, the world changes and fast, better to try to create and carve out a new job or business idea for yourself than stand on denial of something that, good or bad, could either make or break humanity, but humanity has no say on the inexorable progress of ideas. This actually is science right here, don't tech people embrace science, or only when the collateral damage is elsewhere and not on them?
- rf15 4y ago
  The technology's hype precedes it whenever you try to engage with it. On the surface, it looks a lot like the bitcoin hype, and if you remember IBM Watson you might get the idea that nothing much will come of it. So for me, I will keep using it, but I have nothing but disdain for the people worrying about AI overtaking the world, claiming this will revolutionise everything/etc.. Especially since this technology is almost good enough to tempt lay people to believe the statistically related words to your query would mean anything. In fact, iirc this has already happened and e.g. caused a suicide.
- zelphirkalt 4y ago
  I think many are not actually against usage of these kinds of ML models in general, but against what is done using them right now: Code laundering, violation of licenses, intransparency, training on personal data, no responsible person to talk to, no way of having data removed, that one does not want in the model or the model to train from, and more. Any of these can lead to dystopia. When we use computer vision to identify benign or malignant tumors, we might cost someone a job, but at least what that model was trained on can be known and we are not leaking personal data in the model and probably there is no violation of licenses or similar to the data that was used to train the model. The model is very limited in output. The consequences are kind of simple to monitor or predict, because the model can only be used in its specialized area of use. With the new crop of ML models the situation is different. Lawmakers were asleep while these things became popular and there is no knowing, how it will all pan out, because the output is of a more general nature, that can touch any subject, any area of expertise. No one knows what they have been trained on and whether there is anything in that training data, that should not have been used, and there is no simple way (that I know of) to operate out any such data after training the model.

gavinhoward 4y ago

Maybe, but that's a bet I'm willing to take. Here's the rub: if my competitors are going to realize "massive productivity gains," where are those gains actually coming from? Are they coming from the time it takes to type? No, because typing is a small portion of the time we spend as programmers. Are the gains coming from the time spent on design and architecture? Maybe, but that means my software will have better architecture, and I will have better velocity in the long run. (I have real-world experience with this, by the way; it takes me, on average, less than an hour to fix bugs in my bc nowadays. Architecture matters for long-term velocity.) Are the gains coming from the time squashing bugs? No, this is where AI would decrease productivity because you have to carefully review outputs to ensure there are not any bugs. In essence, the productivity gains will only happen the less that my competitors actually review and clean up the code from these tools. The less they do that, the lower the quality. The lower the quality, the slower their long-term velocity will be. "A little bit of slope makes up for a lot of y-intercept." [1] [1]: https://gist.github.com/gtallen1187/e83ed02eac6cc8d7e185 https://gist.github.com/gtallen1187/e83ed02eac6cc8d7e185

jmfldn 4y ago
Honestly I wish you well in this approach, I just worry that ignoring this completely may be too costly. I'm just advocating a very cautious middle path. For now, these tools are just code helpers to me (and right now I barely use them for that), but the moment I sense a genuine advantage to using them in my job, and I don't think it undermines my engineering, I think I'll have to engage further. Undermining for me means, reducing software quality, reliability, my own understanding. To the extent that I can work faster though, and even improve on those metrics, so much the better. The semi-near future to me (5-10 years?) , breathless hype-aside, looks like one where quite a lot of coding is automated with machines able to range over whole codebases and build higher level models of the software, and then getting into architectural system-design suggestions. I also see them linking up with company docs to build up a model of the whole domain. This doesn't need AGI, it's just an extension of what we have now, and I can't see it being anything other than a game changer. Forget ChatGPT, imagine your own private LLM, trained on your code and business, with all the weird glitches these prototypes have currently largely gone. You, the expert architect, are still needed, but you've now added a superpower to your tool chain.

BeefWellington 4y ago

> I think the zero sum, "use AI everywhere" vs "don't use it at all" are both to be avoided. The wise path is somewhere in the middle. I suspect this is one of those tech Pandora's box moments where it's largely irrelevant what actual tech people think about this; executives will be swayed to the "use AI everywhere" side of things purely as a cost-cutting measure. Any productivity gained via the use of AI will be leveraged not to improve overall productivity (in the medium to long term) but instead leveraged against employees to to shed salaries.