EXPERT SPEAK
A
rtificial intelligence is when
a machine mimics functions
that human do such as sensing
and learning, reason and infer, deciding
and acting. As a technology, artificial
intelligence can support use cases such
as chatbots, detecting fraud, cognitive
document automation and others. So
where is the hard line between what is
artificial intelligence and what it is not?
Techniques which use brute-force or
rule-checking and do not mimic human
thinking are not artificial intelligence.
As an example, fraud detection
applications can be built by configuring
all possible frauds that have occurred in
the past and checking against this list.
This is not artificial intelligence as you are
not letting machines think, but instead
just using check rules. Since fraudsters
always find a new way of making fraud,
you will not be able to detect emerging
Pranay Dave, Director Data Science
WESEMEA, ThinkBig Analytics, Teradata.
and new kind of fraud incidents. At
present, artificial intelligence is used to
automate specific tasks done by human.
Those industries where highly specific
human tasks can be automated will soon
be impacted by future developments in
artificial intelligence.
Key industries which will be
impacted are in information technology,
telecommunications, consumer services,
financial services, manufacturing and
production. Industries where there is a
lot less human activity, such as education,
media and entertainment, sports,
construction and property will be less
impacted in the short term, but impacted
later on in the medium and long term.
While advancements in artificial
intelligence will replace some specific tasks
done by humans, it will also create new
opportunities of redefining job roles. One
such role is the Chief Artificial Intelligence
Officer. This is a senior executive
responsible for artificial intelligence
strategy and implementation in an
enterprise. But compared to the Chief
Data Officer, this role will also include
the human challenge of redefining job
descriptions in conjunction with human
resources, as advancements in artificial
intelligence progress into the enterprise.
Another role is the Citizen Data-
Scientist. Gartner defines a citizen data
scientist as a person who creates or
generates models that uses advanced
diagnostic analytics but whose primary
job function is outside the field of statistics
and analytics. As there will be more
demand for artificial intelligence, the
demand-supply gap for data-scientists
Arrival of the
Chief AI Officer
Artificial intelligence will disrupt human intensive jobs within
an organisation as well as create new ones like Chief Artificial
Intelligence Officer and Citizen Data Scientist according to
Pranay Dave at Teradata.
will increase. This will move traditional
workloads of data-science work to the
citizen data scientist, while the expert data
scientist will increasingly be focused on
artificial intelligence.
Based on a recent survey made by
Teradata, almost all respondents 91%,
anticipate significant barriers to adoption.
The majority predict roadblocks due to
lack of IT infrastructure 40%, followed
by a lack of in-house talent 34%. Just
as many, 33%, claim that artificial
intelligence technology available today
is too unproven and nascent, while
30% yearn for more budget. However,
skepticism is lower in other areas;
only 19% are concerned that artificial
intelligence has a weak business case,
and only 20% worry about the impact of
artificial intelligence and automation on
jobs and employee morale.
Companies will overcome these barriers
with more executive-level awareness and
an enterprise-wide strategy for artificial
intelligence implementation and use. This
is ushering in a shift within the C-suite:
Today, artificial intelligence strategy is
typically under the scope of a CIO or
CTO, but, in the near future, the majority
of businesses surveyed plan to install a
dedicated Chief Artificial Intelligence
Officer to lead the effort.
Various government have already started
to work on artificial intelligence strategies
for countries and cities. Artificial intelligence
has many potential advantages for cities,
like the implementation of 100% driver-less
cars, no traffic congestions, smart building,
and so on. So, one possible future scenario
is, completely new cities will be created
which are designed based on an artificial
intelligence framework and strategy.
Artificial intelligence is fast-coming
into the enterprise. Businesses, which do
not have an artificial intelligence strategy
will soon see themselves disappearing.
We will also see artificial intelligence
being integrated into hardware, such
as robots and drones. This will enable
various new applications such as robot
salesperson or robot interviewers and
intelligent logistics. The transformation is
just beginning.
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