Here are some of the common myths about artificial intelligence and the true realities behind them:

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  1 – Myth: Organizations need high budgets, data scientists, and machine learning experts to use AI

  Reality: Many AI tools are easily available to business users and do not require big budgets.

  While some AI applications do require heavy investments, most of the new applications that leverage AI technology are affordable and easily accessible to business users.

  AI is a technology that requires deep expertise and skills to understand, but the newly developed applications that incorporate the power of AI are user friendly with easy to understand interface and they can be used by business users who have little to no technical skills.

  The role of the technical staff is mainly to connect the AI modules and integrate them seamlessly with the existing systems. Some end to end AI tools even have one click integrations which don’t require the assistance of IT staff at all.

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  2 – Myth: AI algorithms can make make sense of any and every data

  Reality: The quality of data matters just as much as the AI algorithms

  Many people assume that they can feed any type of data to the AI solution and the powerful machine learning algorithm will just produce the right results automatically–which is far from the truth.

  There is no way AI can make sense of data that is already too broad or hasn’t been processed in a way that makes it easily understandable by the system.

  Machine learning algorithms learn the best way to process the data and arrive at an answer after continuous approximations and adjustments. Feeding bad data to the algorithm can lead to bad results, even if the algorithm is perfect.

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  3 – Myth: AI solutions are secure by design

  Reality: Security depends on the AI algorithm and its corresponding infrastructure design

  It’s easy to assume that AI systems can defend themselves in a much better way than traditional solutions. While it is possible for AI systems to detect hostile behavior and in some cases, take measures to defend itself, the very nature of AI can also be used against itself by hackers.

  The core of every AI system is mainly algorithms and not much data, which can make people assume that AI applications are secure by nature since there is nothing to steal. But hackers can actually feed AI systems the wrong data to manipulate its decision making.

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  4 – Myth: AI solutions can learn the same way as humans learn

  Reality: AI solutions are powerful but they still have a long way to go before they can achieve the complexity of the human brain

  Deep learning technology and neural networks in AI applications allows the system to emulate the way biological neurons learn and recognize patterns. This approach can be used to solve a number of challenges – from speech recognition to language translation and fraud detection.

  While these neural nets can solve many issues, they are still not capable of imitating the characteristics of human thinking-at least not yet.

  A human brain has 200 billion neurons and each neuron connects to as many as 10,000 other neurons through synapses.

  To put it in perspective, one human brain easily has more switches than all the computer systems, internet connections, and routers on earth. It isn’t really that surprising the AI cannot duplicate human brain yet.