A few years ago, Artificial Intelligence was not considered a topic of serious discussion outside colleges and universities. But today everyone around us talks about AI and even uses it to solve real-world problems and generate brilliant machines and new businesses. It is considered a new trend and every software and wearable app development company are trying to make the most of it.The growing acceptance of artificial intelligence has created significant hype adding not only great ideas but also in several situations a lot of false promises. We take a look at the most common AI myth below:
#Myth 1: AI works like the human brain
This is one of the biggest misconceptions people have about Artificial Intelligence. It is inspired by human brains but it is not equivalent to it. AI is a branch of computer engineering which is designed to build smart machines that are capable of solving problems. Yes, there are some forms of AI that seem clever, but it would be unrealistic for us to think that present AI is alike to human intelligence.
For instance, Image recognition technology is more accurate than most humans, but it is of no use when we try to solve a math problem with it. The reality with today’s AI is that it can crack one task exceptionally well, but if the circumstances of the task change only a bit, it fails.
#Myth 2: AI can be 100% objective
When it comes to AI technology, data is king. We are aware that every single AI technology is based on data, rules, and other types of input from human professionals. But humans can never be rational, they are intrinsically biased in one way or another, and so is AI. Human decision-making in this area, like in others, can be imperfect, fashioned by societal and individual preconceptions that are often unconscious.
To solve this problem, you can use diversity in the teams who are working with AI. You can also let team members review each other’s work. This can protect from various judgemental biases such as selection and confirmation bias.
#Myth 3: Intelligent machines learn on their own
People usually have a misconception in their minds that machines can learn on their own. But in reality, experienced and skilled human data scientists first frame the problem, then prepare the data, regulate appropriate datasets, eliminate potential bias in the training data, and, most significantly, constantly update the software to enable the integration of new knowledge and data into the next learning cycle.
#Myth 4: AI will replace all jobs
The impression that AI will completely take over the job market is one more myth with little to no foundation. AI permits businesses to make more accurate and informed decisions through predictions, classifications, and clustering. It is evident that technology has the control to transform the workplace and mechanize time-consuming and mundane tasks, but it’s unlikely to think that AI will completely replace humans
But it will limit the work of people, for instance, the use of imaging AI in healthcare. A chest X-ray application based on AI can detect diseases much faster than radiologists. But these capabilities don’t eliminate human participation in those tasks but will change job profiles and won’t completely make human intelligence redundant.
#Myth 5: Everyone is ‘using AI’
According to a survey done by MMC (London-based venture capital firm) on a total of 2,830 AI start-ups in 13 EU countries, it was found that 40% of start-ups that are classifying themselves as ‘European AI companies don’t use artificial intelligence and are merely cashing in on the hype.
It was found that the majority of firms work with machine learning software, which is one of the subordinate fields of AI that combines mathematical techniques to let a system or machine to practice deriving information from the underlying database. ML techniques consist of both supervised and unsupervised learning.
#Myth 6: My business does not require AI
If your current strategy is “no AI” than you should revisit your organization’s need to consider the potential impact of AI and investigate how this technology can be useful to solve the organization’s business problems. If you continue to avoid the implementation of AI in your business that it can turn into a competitive disadvantage for your business.
Every business should research AI and understand its applications for the business and then make a rational decision about whether to adopt AI technology or not.
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