Feb 17. If the buzz around Artificial Intelligence (AI) has left
you nervous that it would soon take away your job and the technology
works better than your brain, you are probably mistaken.
By Nishant Arora
is nothing artificial about intelligence and unlike industrial automation
that is actually taking away jobs globally, AI is only going to supplement
human intelligence across the spectrum — from banking to media.
Gartner, in its current state, AI consists of software tools aimed at solving
forms of AI might give the impression of being clever, it would be unrealistic
to think that current AI is similar or equivalent to human intelligence.
forms of Machine Learning (ML) — a category of AI — may have been inspired by
the human brain, but they are not equivalent,” says Alexander Linden,
Research Vice President at Gartner.
image-recognition technology, for example, is more accurate than most humans,
but is of no use when it comes to solving a Math problem.
rule with AI today is that it solves one task exceedingly well but if the
conditions of the task change only a bit, it fails,” Linden noted.
comes to bias, an ML model will always operate the way you’ve trained it, said
Olivier Klein, Head of Emerging Technologies, Asia-Pacific at Amazon Web
Services (AWS), which is retail giant Amazon’s Cloud arm.
train a model with a bias, you would end up with a biased model. You
continuously need to train and re-train your ML model and the most important
thing is that you need some form of feedback from the end-consumers,”
Klein told IANS.
absolutely not about replacing humans but enhancing the experiences,” he
technology is based on data, rules and other kinds of input from human experts
and similar to humans, AI is also intrinsically biased in one way or the other.
there is no way to completely banish bias, however, we have to try to reduce it
to a minimum,” Linden said.
business leaders are often confused about what AI can do for their
organisations and are challenged by several AI misconceptions.
Gartner, they must separate reality from myths to devise their future strategies.
organisation should consider the potential impact of AI on its strategy and
investigate how this technology can be applied to its business problems,”
that humans are really good at learning quickly with very little information.
models are the opposite. They require a lot of data inputs to be able to be
would argue that you show someone a bicycle a few times and you show them how
to ride a bicycle and the human being is able to ride that bicycle pretty
easily. To just train a robot to ride a bicycle takes millions of hours of
training,” explained Klein.
is: Machines are not here to take decisions on their own and certain human
emotions — empathy, for instance – can never be automated.
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