Tasks for ML are relatively narrow and specific, so it's hard to see how that one task, or even a collection of tasks, could be identical to somebody's job. Jobs are ordinarily not restricted to performing one repetitive mental task over and over. However, ML could potentially make some jobs easier by speeding up some tasks, and allow them to be handled by fewer people.
Machine Translation will soon start taking a big bite out of generic professional translation work (we've already seen Google Translate replace the sort of translate-by-dictionary-lookup tasks often used by small businesses in the absence of better options), but will also serve as a productivity tool for more specialized (usually industry-specific) services.
I don't think this will cut into the translation work of longer prose (fiction or non-fiction) just yet, but we will see some pressure on some translators to up their game in terms of translating between cultural contexts, the sort of thing that makes these so amusing:
As far as I know, machine translations still come back as a jumble of phrases that you have to figure out like a puzzle. I am skeptical that machine translation will ever seriously approach professional translation. To effectively translate, you have to consider the idea being communicated and make sure that idea comes through, even if you have to creatively substitute different words and phrasing. A machine being able to understand what it's reading at multiple levels and anticipate possible misunderstandings seems hopelessly difficult.
Professional Tetris players and people who classify pictures of cats and dogs.
Machine learning is not a mature or robust field. Real world applications are brittle and extremely narrow in scope. The past few years has seen a burst funding and hype, as a result of deep learning advancements, but that will gradually wane as all the low hanging fruit is picked. Many applications that are promising (like self-drive cars and medical classification) will face major regulatory hurdles. It will take a much more radical (and, frankly, unexpected) breakthrough before most humans have to worry.
Stock trading, management, fast food menu pricing and inventory ordering, delivery route designers, and many more jobs.
Seems there are a large depth of jobs that can be replaced by automation across all industries at all levels. Not sure what the end goal is for those moving to automation (save money, speed up production, increase expansion, etc.) as there could be many good and negative.
Sometimes I do wonder whether there are areas in politics where decisions made by random number generators could lead to better outcomes. Obviously, they can't make informed decisions. However, they don't get swayed by all those biases humans are susceptible to.
List of jobs table is page 57.
[0] http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Futu...