Home' HR Monthly : November 2018 Contents November 2018 HRM magazine 19
8 WAYS MACHINE
LEARNING IMPACTS HR
Shortlist outstanding applicants by
reading through resumes.
Improve recruitment by identifying
desirable characteristics, including
Provide employees with a digital
coaching companion, similar to Siri.
Deliver better customer service through
Identify areas of weakness an employee
may have and tailor training accordingly.
Provide employees with smart calendars
to streamline their workday.
Improve analytics across the entire
Provide a deeper insight into employee
Identify meaningful measures of workforce
performance and learn how to develop a
sustainable measurement and reporting
process, in this AHRI course that can be
what the distinction is, and it will create
algorithms so it can make the distinction for
itself in the future.”
The result will have up to 98 per cent
accuracy. If that doesn't sound great, van den
Hengel says that humans only achieve about a
95 per cent success rate from the same test.
“Most of the things a human can do in
less than a second, machine learning is more
accurate at,” he says.
Neural networks are the underpinning
technology for machine learning. They help
deal with large sets of data and are very much
inspired by the human brain.
“They are interconnected layers of
algorithms, called neurons, which feed data into
each other, with the output of the preceding
layer being the input of the subsequent layer,”
says Nick Heath in a September 2018 article for
One of the biggest benefits of a neural
network over a traditional computer is its ability
to do many things at once.
“ With traditional computers, processing is
sequential. One task, then the nex t, then the
next, and so on,” says Eric Roberts, professor
emeritus of computer science at Stanford
University, on his university’s website.
With traditional computers, it may appear
that many things are happening at once, but this
is only an appearance.
Another fundamental difference between
traditional computers and artificial neural
networks is the way in which they function.
“While computers function logically with a
set of rules and calculations, artificial neu ral
networks can function via images, pictures and
concepts,” says Roberts.
“Traditional computers have to learn by
rules, while artificial neural networks learn by
example, by doing something and then learning
You're already involved
Even if you classify yourself as a doomsayer who
fears the rise of machines, chances are you have
already been participating in your own demise.
Ever tried to log into a website and had Google's
infu riating reCAPTCHA act as gatekeeper?
Well, instead of the machine knowing all the
answers, you've actually been an unwitting
participant in training it.
You've been at it since 2009 and have helped
Google Books digitise its entire archive, helped
train Google Street View to read house numbers
and shop signage, and you're also playing a part
in d riverless cars one day being able to read
“Reading house numbers was a real
challenge for Google,” says van den Hengel,
“because house numbers are surprisingly
difficult due to each one having a different font
and different colour.”
Machine learning is already playing a part in
our day-to -day lives, but how can it impact HR?
One key area, says van den Hengel, is efficiently
Machine learning can be used to identify
key traits that you r most successful employees
all possess. It can then use that information to
shortlist the most ideal candidates.
“The current process is that you put together
a team that has all the skills you need,” says
van den Hengel, “but the real opportunity is
the ability to put together a team that has the
personality types that you need to work together
Coaching is another area where machine
learning will have an impact, predicts van den
Hengel. Say you're an employee at a bank and a
customer asks you a difficult question.
In times gone by your options would be
to wing it, wait until someone more senior is
available to help out, or get back to the customer
at a later date.
But machine learning will allow you to
engage with a digital coach for advice on the
spot. Think Siri or Alexa, but for employees.
“There's a whole lot of legal questions in
banking, and people who work there struggle
with the unbelievable complexity of the system,”
says van den Hengel.
“So machine learning coaching resources
can not only help them answer the technical
question, but also figu re out what the
The same opportunity exists for customers.
Chatbots have exploded onto the scene in recent
years, and machine learning will only help them
improve their customer service.
So should HR run for the hills, or should it
face the machines head on? Van den Hengel
says that while some people will likely see their
jobs reassigned due to future machine learning
efficiency gains, there's an opportunity for most
professionals to add more value and provide
“There will be winners and losers. But as far
as I'm concerned, the winners will be the ones
who can figu re out how to get better outcomes
using machine learning.” •••
18/10/18 3:21 pm
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