It's really depressing that a lot of machine learning tasks can now be performed without much programming knowledge and even less knowledge about machine learning...
But once you want to extend a problem into an unfamiliar domain or debug why an algorithm is not working, then I don't see how you can accomplish this without domain-specific and machine learning knowledge. Or have I been missing out on some amazing auto-debugging AI that I am unaware of?
Or because your own lively hood is dependent on machine learning?
Whatever the case may be and my response is that I don't care. I firmly believe that this is a GOOD thing.
As developers we should be striving for a) open sourcing machine learning so that everyone can contribute to the good it can do and b) that we democratise the result of those efforts so that everyone can benefit from it for their own projects.
When time goes forward these efforts will translate into an NPM of machine learning. What would have taken a small team and a year to do, now just takes installing a plugin and having an API at the developers disposal. This is definitely a future that I cannot wait to see and it's within reach.
Out of the 3, AN (Narrow) I, AG (General) I and AS (Super) I. Artificial Narrow Intelligence is going to grow in prevalence in the next 10 years and the effects will be very good. I don't think it will kill jobs, merely make people much more productive.
Why? Oh I know. You are a wild-eyed optimist who would have cheered unfettered globalization in late 90's because "the whole can benefit from it".
You know what - as developers, we should care about maintaining scarcity of developers around the world so that we can continue being in demand and continue having great salaries. I would rather be a part of AMA (cartel which limits supply of Doctors in the USA and erects legal/regulatory barriers for competitors, thereby ensuring high standard of life for Doctors) than being a manufacturing engineer whose job was lost (or threatened) first by globalization and now by automation.
You know who benefits from "democratization of results of our efforts" or when "everyone can contribute to the good machine learning" (or other software engineering in general)? VCs and mega-rich folks, whose capital now doesn't have to share productivity gains with labor because labor is abundantly available.
Yes, it still needs that expertise to run models well. But those without the expertise sound more confident and then ruin the market with the expectations they elicit.
I use heaps of tools I probably couldn't create myself, or at least don't have the gumption to try.