I'm old enough to have seen a lot of these boom/hype/bust cycles. I'm convinced that this time is, in fact, different.
To temper this I believe most decent user-visible changes will take ~5 years (as most actually useful software does) but the changes will be huge:
* The author cites computer driven cars. I think this will take place mostly on long-haul highway trucking instead of in cities first. Even so, this could mean a massive swath of truckers without work in a short 5yr epoch.
* We've already seem the effects of heavy astro-turfing/disingenuous information/etc in the last US election. This certainly changed the "national psyche" and may have changed the election outcome. There is heavy ML research going into making the agglomeration of ads and content almost compulsively watchable. Our monkey brains can likely only handle a few simple dimensions and only boolean or maybe linear relations and they certainly get trapped in local maxima/minima. Even trivial ML techniques can bring this compulsion from say 50% effectiveness to 95%+ (by some reasonable measure). Imagine a web that is so completely tailored to the user such that search results, ads and content is completely tailored to you. Verbs, adjectives entire copy all written to get you to that next click. This is different.
* Bots that seem like real ppl will be rampant. Are those 100 followers/likes/retweets actual ppl? Even years ago reddit (to gain popularity) faked users. Certainly this has only accelerated and will continue to as commercial and state actors see value to moving public opinion with these virtual actors. (ironically maybe only bots will have read this far?)
* Financial Product innovation - Few ppl actually understand this market (even within the banks) however the deals are usually in the 100+ million range. The products take advantage of tax incentives, fx, swaps, interest rates, etc in an ever increasing complexity. These divisions are still some of the most profitable parts of banks. It's likely that on deals where profits are measured in tens of millions on a single deal (several are made per quarter, per major bank). It's likely that ML algos will be put to use here as well not only optimizing current products but in current prod elaborations. I beleive these products to be a major source of inflation. Whereas the official numbers are ~2% I believe the actual inflation (tm) felt by most is more in the 7%+ range.
* State Surveillance and Actions - I hear ppl saying that mass surveillance hasn't been effective in stopping "terrorism", as if it would be ok if it did. Well, it will be effective and it will get very, very good at it. Of course terrorism is not defined anywhere so ...
* Customer Support - this, like transportation, is a major employer of unqualified workers. I believe in 10 years there will be maybe 1% of the current workforce in CSR work. The technology is here the software just has to be written.
It's not just the number of jobs displaced it's the velocity. If we look to the effective Predator-prey modeling:
AI will find it's way into specific areas in which the ROI is very significant, and though those will be hard to predict, I agree with the above.
It will make a huge impact in some areas.
Others, not so much.
It's funny that not a single person mentioned 'big data'.
Big data was all the rage for the last few years, and it would seem like an intuitively obvious fit, not? I don't think so.
I think it's a stretch to see how AI help's the gap design new clothes, or even optimizes sales approach. I suggest it will be things like customer service as Randy indicated.
To temper this I believe most decent user-visible changes will take ~5 years (as most actually useful software does) but the changes will be huge:
* The author cites computer driven cars. I think this will take place mostly on long-haul highway trucking instead of in cities first. Even so, this could mean a massive swath of truckers without work in a short 5yr epoch.
* We've already seem the effects of heavy astro-turfing/disingenuous information/etc in the last US election. This certainly changed the "national psyche" and may have changed the election outcome. There is heavy ML research going into making the agglomeration of ads and content almost compulsively watchable. Our monkey brains can likely only handle a few simple dimensions and only boolean or maybe linear relations and they certainly get trapped in local maxima/minima. Even trivial ML techniques can bring this compulsion from say 50% effectiveness to 95%+ (by some reasonable measure). Imagine a web that is so completely tailored to the user such that search results, ads and content is completely tailored to you. Verbs, adjectives entire copy all written to get you to that next click. This is different.
* Bots that seem like real ppl will be rampant. Are those 100 followers/likes/retweets actual ppl? Even years ago reddit (to gain popularity) faked users. Certainly this has only accelerated and will continue to as commercial and state actors see value to moving public opinion with these virtual actors. (ironically maybe only bots will have read this far?)
* Financial Product innovation - Few ppl actually understand this market (even within the banks) however the deals are usually in the 100+ million range. The products take advantage of tax incentives, fx, swaps, interest rates, etc in an ever increasing complexity. These divisions are still some of the most profitable parts of banks. It's likely that on deals where profits are measured in tens of millions on a single deal (several are made per quarter, per major bank). It's likely that ML algos will be put to use here as well not only optimizing current products but in current prod elaborations. I beleive these products to be a major source of inflation. Whereas the official numbers are ~2% I believe the actual inflation (tm) felt by most is more in the 7%+ range.
* State Surveillance and Actions - I hear ppl saying that mass surveillance hasn't been effective in stopping "terrorism", as if it would be ok if it did. Well, it will be effective and it will get very, very good at it. Of course terrorism is not defined anywhere so ...
* Customer Support - this, like transportation, is a major employer of unqualified workers. I believe in 10 years there will be maybe 1% of the current workforce in CSR work. The technology is here the software just has to be written.
It's not just the number of jobs displaced it's the velocity. If we look to the effective Predator-prey modeling:
https://en.wikipedia.org/wiki/Lotka%E2%80%93Volterra_equatio...
We see that the generally the solution takes 2 modes:
* stability - wolf/rabbit populations wax and wane together * crash - the wolves kill enough rabbits to make the remaining pop crash
Now I don't believe there will be a 'crash' but likely there will be a new normal (equilibrium) and getting there will not be pleasant.
Disclaimer: Yes, I do work in ML.