in a rapidly changing
work world it's important to be a constant learner
to be able to change and evolve your skills.
Especially when you're facing automation
of certain types of work so
i want  you to think about a spectrum of work
to get automated on one part of the spectrum
is chess
Chess is based on rules is very clear
patterns repeat that is a great situation for computer.
computers are really good at patterns which is why they
made an exponential progress in chess
and  now
the chess app on your iphone can beat the best human chess player in the world
in a middle of spectrum maybe you think about
self driving cars.Self driving cars we have made
great progress there are rules of the road
there are regular repeating patterns but theres significant
challenges that remain and our far end
of the spectrum we have something like say
cancer research where IBM watson
had alot of hype but actually
was under perform that hype in a such away
that i talk to AI researcher some of them worried
that they would damage the reputation of AI
in health research going forward as one on chologist
i talk to put it the reason watson
destroyed at jeopardy
but failed in cancer research because we know the answer
to jeopardy so if you want to
have skills that continue to be valuable, you have to keep
learning things and you have to be some
of these more amorphous field almost
so i wanna share on one example how this has played out in the past
when ATM were created
the thought was that this would do away
with bank tellers for good right bank tellers did
repetitive transaction and see you would not need them anymore
but infact as more atm
came online there were more jobs for bank tellers what happend
was that each branch
needed few tellers so each of the bank became cheaper
and banks open more branches so there were more tellers
but the job of tellers changed completely
it was no longer someone who could do repetitive transaction
rather they had to learn
marketing skills and customers service and have this much
wider array of broad skills because those
broader skills and integrating different types of information
are what different for computer the psychologist
Robbin Hogart categorize
domain of learning as
going from the kind to the wicked
kind learning environment where areas of patterns repeated
there is wealth of previous data
there were clear rules
and feed back was apparent and those kind of areas like chess
computers really thrive on the end of the spectrum
are wicked environment where
not only information is clear rules dont necessarily repeat
people arent waiting for each other to take turns
feed back maybe delayed
if you get it all it maybe inaccurate human behaviour is
involved those are areas
wheres computer dont do as well
there are quiet alots of so called soft skills
how
to deal with human behaviour and how to adjust the things
that are changing in real time and interpret signals
that are very difficult to quantify thats an area
thats very very difficult for computers
but humans have a huge advantages
so those kinds of soft skills
are really important and will be for long time to come.
