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.
First, there 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.
According to Gartner, in its current state, AI consists of software tools aimed at solving problems.
While some 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.
"Some 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.
The image-recognition technology, for example, is more accurate than most humans, but is of no use when it comes to solving a Math problem.
"The 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.
When it 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.
"If you 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.
"ML is absolutely not about replacing humans but enhancing the experiences," he added.
Every AI 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.
"Today, there is no way to completely banish bias, however, we have to try to reduce it to a minimum," Linden said.
IT and business leaders are often confused about what AI can do for their organisations and are challenged by several AI misconceptions.
According to Gartner, they must separate reality from myths to devise their future strategies.
"Every organisation should consider the potential impact of AI on its strategy and investigate how this technology can be applied to its business problems," said Gartner.
Klein said that humans are really good at learning quickly with very little information.
"ML models are the opposite. They require a lot of data inputs to be able to be trained.
"I 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.
The truth is: Machines are not here to take decisions on their own and certain human emotions -- empathy, for instance - can never be automated.
(Nishant Arora can be contacted at firstname.lastname@example.org)
(This story has not been edited by Business Standard staff and is auto-generated from a syndicated feed.)