There is historical precedent, and it seems almost impossible that they aren't:
Today, machines can process regular spoken language and not only recognize human faces, but also read their expressions. They can classify personality types, and have started being able to carry out conversations with appropriate emotional tenor.
Machines are getting better than humans at figuring out who to hire, who’s in a mood to pay a little more for that sweater, and who needs a coupon to nudge them toward a sale. In applications around the world, software is being used to predict whether people are lying, how they feel and whom they’ll vote for.
...Most of what we think of as expertise, knowledge and intuition is being deconstructed and recreated as an algorithmic competency, fueled by big data.
On the other hand, there may be little evidence that this is happening:
We have a very good way to measure the extent to which machines are taking our jobs. It's called "productivity growth." It means the extent to which we can produce more output with the same amount of human labor. If the machines are taking our jobs, productivity growth should be very fast.
It isn't. Productivity growth was very fast in the years from 1947-73. It grew at a pace of roughly 3.0 percent annually. This was a period of strong wage growth and low unemployment. It then fell to around 1.5 percent annually from 1973-1995. There was then a pick-up to close to 3.0 percent annually in the years from 1995 to 2005. (For some technical reasons, like a faster pace of depreciation in the more recent period, the 1947-73 productivity growth was much stronger.) Since 2005 productivity growth has fallen to an average rate of about 1.5 percent. In the last two years it has been under 1.0 percent.