Errors of Your / Machine Learning

Any progress on the front of Machine Learning, i.e., the comparison with how/what humans learn from various teaching formats, and how machines are better at rote learning et al, and how does the perfection of machines learning facts, reflect on what is data processing, what is intelligence, and what is wisdom ..? Where the latter is the area in which of course re retreat ever more, but without the foundation of a life long of learning and experience ..?

[Intermission: Anyone out there still holding on to the ‘you only learn from experience, which is making errors and surviving’? What was so many years of school all about; you’re still no further with calculus than 1+1 equals something more than one — the max you can learn from ‘ experience’ … How did you ‘experience’ History, Science ..? Apparently, there’s quite a base of facts to learn, even (or more?? contra The Shallows) in times of Google. Or, you’ll be the doofus that can not (sic) learn to be intelligent nor wise, and will make any and all rookie mistakes in all situations everywhere, over and over again.
Seems like the base of learning, grows steadily — exponentially…]

Notwithstanding the road (path) to wisdom is through experience … which would ever less be available when machines start to take over the simple, the foundations (qua operationality of work-as-labour), and then the next stage, etc. (since none will be experienced enough to succeed pensionados that still have that subsequent level of understanding). Leaving the abstract thinkers ever more loose in the sky. Hey that’s what’s happening with accountancy, if the industry doesn’t move fast. And will happen everywhere.

But back to the main point: Has Watson-class learning (AlphaGo/Deepmind/Brain (sic), … no not Siri you m.r.n) learned us anything about learning, and/or have we changed learning since machines took over parts of rote learning? Have we changed our view on learing, intelligence, wisdom?

To the disappointed, apologies go; nothing here on how machine learning could lead to the unethics of Computer Says No… Too much of a mer à boire qua research — see here.

[Steep, to enlightenment; Girona]

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