(This was written about 9 months ago. Its not out of date... yet)
People think that AI is going to DESTROY some jobs and CREATE some jobs. It may be too early to tell if this is true. Even so, here are some thoughts.
1) Who will win? Who will lose?
2) Historically in the long term society was better off after a tech change (e.g., we live longer now than we did in the farm-era). Will that happen here as well?
3) We have some sense of what kinds of jobs will be destroyed. But what kind will be created? Will they be interesting? See later in this blog for a job you might not have thought of.
4) Many jobs will change. If you are over X years old then think about how much technology has changed your job even before the AI revolution. (The value of X may vary depending on how high-tech you are.)
For an intelligent view of the questions above, see here.
For my view of one aspect of this, read on.
There is one job which has been either created or expanded by AI:
Annotator.
(See here for an ARTICLE about these jobs, from which I got most of the rest of this post. The word ARTICLE is in caps so when I refer to it later you'll know what I am referring to.)
The job consists of looking at pictures and labeling things.
Here is a direct quote from the manual:
LABEL real items that can be worn by real people.
Does Lady Gaga count as a real person? She sometimes wears dresses made of meat. Should that count? See here for a real article about her and see here for the Weird Al parody of Born that Way. Note that this is Weird AL, not Weird Artificial Intelligence. (See here for the Weird AI for Weird AL problem.)
They do this to create data for AI.
a) The jobs don't pay well though there are some exceptions.
b) The jobs are boring though there are some exceptions (and that may depend on the worker).
c) This job is needed because AI keeps running into edge cases. This may have happened with AI's attempts to solve my GROUP ONE-GROUP TWO prez-VP problem from a prior blog post here or my baseball-brother-pitchers post here.
c) KEY: People in AI used to think this is a temporary thing and these jobs will soon be automated. This might not be the case. There are SO MANY edge cases that AI encounters. The more we expect from AI the more edge cases there will be.
A quote from page 26 (of the ARTICLE pointed to above) which is informative if you can parse it. I think.
Put another way, ChatGPT seems so human because it was trained by an AI that was mimicking humans who were rating an AI that was mimicking humans who were pretending to be a better version of an AI that was trained on human writing.
As I've said before, what's going to happen is that the world is going to figure out that "advanced model" AI is way too computationally expensive for it to be useful for anything.
ReplyDeleteSmall model AI (models that can run on your cell phone or a desktop) will be plentiful and free and useful for some things. People like me, who want to read the Wiki page or the actual papers that discuss the things we search for will continue to have no use for LLM-based AI, but people who just want to know simple trivial things and don't care about the details or intellectual content (or that it's wrong 10% of the time) will be happy with small-model AI.
But computers are getting faster and AI will get cheaper, you scream. Well, no, they're not. The RTX5080 benchmarks at less than 1.5 times faster than the two generations older RTX3080. Back in the day, every two years, things were twice as fast (from 1985 to 2005). Nowadays, a generational improvement is 20% every two years, if you are lucky. And that will often come with a similar increase in power drawn, i.e. zero improvement in computation per watt.