What are the Common Myths about Machine Learning?

Machine Learning (ML), one of the hottest technology in the IT industry providing another interesting opportunity for techies to developed AI-based models like automated machines and business applications making human work easier and more robotic in various fields.

Nowadays, machine learning seems everywhere and lots of people around us talking about this, but many of them not fully aware of it. Smartphones are automatically tagging photos, voice-activated virtual assistants working everywhere, Chatbots, and self-driving cars all are backed with machine learning technology.

Before you know anything more about ML you need to make clear the machine learning myths what exactly machine learning is and what it is not, that you may have been perceived from the information hovering around you. The definition says – Machine learning is a discipline to train computers or make them learn themselves with the training dataset and work accordingly without explicit programming.

Read More: 5 in-demand Professions with Growth of AI.

Top Five Myths About Machine Learning

Myth#1: Machine learning works without human intervention

No doubt ML is the process of self-learning and performs accordingly but without customizing programming how it is possible to create programming or controlling codes for such technologies. All the algorithms used in machine learning solutions are created by humans. Hence, the involvements of humans are a mandate for ML. Though, after employing machine learning, limits or removes humans from various stages but complete human intervention cannot be ruled out.

Myth#2: Machine learning completely removes human bias

Yes, it is true, that machine learning helps to remove the biased based decisions that are usually taken by humans. However, it is also not true that bias is completely removed working with ML. ML can’t be completely unbiased because at the stage of the initial development of data categorization a suitable algorithms data sets are analyzed and the programming platform is also decided by the humans. Though, machine learning removes bias to a very large extend compare to humans but can’t remove completely.

Myth#3: Machine learning performs the task on real-time basis

This is also a common myth that Machine learning always performs tasks on a real-time basis. Only the systems that are built for learning can perform on a real-time basis. At a very high level, ML-based technologies are developed to run a series of the algorithm against data and build useful models for organizations and systems to use based on the results of that analysis. Such models are meant to be used in real-time for most of the part while learning and analysis that built those models are not used for real-time basis task performance.


Myth#4: Machine learning can be applied to perform any task

This is another myth among the people interested in this emerging technology. Though, at present times machine learning can be only applied to a task where a large number of input data sets exists or can be potentially captured by the algorithms. Machine learning cannot be applied to every task where sufficient data sets are not available. As per the well-known publications, “the problem could be bigger when you search at areas where data is difficult to get your hands on. However, now many companies are trying to overcome this bottleneck of the requirement of large amounts of data collection and analysis for machine learning algorithms and trying to develop with fewer training data set to develop feasible models.

Read More: What is the Difference Between Artificial Intelligence and Machine Learning?

Myth#5: Only highly skilled data scientists can use machine learning

This is one of the biggest myths about machine learning that only highly skilled professionals or data scientists can use this technology. Though it is true that owing to the complex science of machine learning and further constant evolving it is quite difficult to understand, hence till now only major technology companies and enterprises are taking the advantage of this technology.

However, now many companies are focusing to work on this technology and trying to utilize machine learning in daily business actions to make it more accessible to everyone. Big tech giants like Google, Facebook, Apple, Amazon, and Microsoft are working seriously on this technology and they have already developed machine learning-powered applications and business models making it available for everyone through open source projects and APIs.

Bottom-line

In addition to the above myths, there are many more fables that are very difficult to clear off from everyone’s minds. However, with further progress in different industries and more practical use in our real life, all these myths would be clear in near future. As nowadays many companies are using machine learning to build solutions to protect their business from fraud, while few of them are not using this as efficiently as they should; because this could be considered more of a marketing buzzword. Machine learning as a service is just like other technology, as long as a realistic and favorable approach is taken it would be a powerful tool, and approaching this technology can produce value for money for the businesses across the industries globally.