The Problems With Machine Learning | More To Know!

Machine learning is a technological process by which not just robots but systems and even programs can be programmed to perform routine repetitive tasks and accurately predict future performance from past trends that have been fed in along with the logic. Machines are now teaching human students, performing weather forecasts, and even medical diagnoses.

There are machine learning algorithms that are continuously fed actual performance data and the ability of the machine to respond with greater and greater accuracy improves with more and more actual raw data being fed. The possibilities are endless.

What Are The Advantages & Disadvantages Of Machine Learning?

The process of machine learning is actually a forerunner of artificial intelligence. Machine learning is a stage where even the decision-making process is rapidly being automated.

Retail giants such as Amazon, Walmart, Flipkart, and the Indian Jio generate huge volumes of data on customer preferences, tastes, buying habits, spending power, and even sales trends on demographic and geographic parameters to train machines.

The machines that are getting better and better with increasing databases are accurately able to ensure area-wise inventories and even go further to advise increase and decrease of production of specific items.

Social media depends heavily upon machine learning. Have you noticed how an automatic friend suggestion comes on your Facebook account from a person who you may have called a few times? Phone records are being scanned and the machine is taught to identify whether a frequent caller is a Facebook friend or not, If not, the programmed logic sends a friend request.

Machine learning works in myriad ways. Facebook users will find more posts on a topic liked by people coming up frequently.

An advantage of using machine learning is its continuous improvement. Machine learning is actually getting better and better day by day. There are myriad uses that are evident in the internet of things. Home Appliances are connected to the internet and their start-up and installation are done online, from printers to microwave ovens to smart TVs. Even troubleshooting to rectify a fault is online.

The system gets better and better with more and more malfunctioning data being fed in till the system becomes an expert. This is the best example of continuous improvement.

Another advantage is using automation for most tasks for routine decision-making. This frees developers from routine tasks. What many customers may not realize is that many help chat boxes that open up in one product website are actually automated and a good example of machine learning at work. The interactive chatbot seems to answer queries from the increasing frequently asked questions (FAQs) with answers that are fed into the system. 

Another advantage is the wide range of applications. Machine learning is being used in diverse fields such as defense and education. Computer applications such as spam filtering and spelling checks and correction are done by machine learning.

There are disadvantages as well.

The first and foremost is the large amount of data acquisition that is needed for machine learning models to be able to predict with a reasonable amount of accuracy. There are bogus data as well and unless they are identified and filtered out, decision-making by the machines may be faulty. 

The next disadvantage is the loss of data privacy. There are frequent complaints about data mining and surveillance as people feel their privacy is being compromised. This is a part of the process and people feel they are being used as guinea pigs by way of surveys and online polls. When there is mass connectivity, it is up to us to determine how to keep our data confidential.

Another disadvantage is the high number of algorithms that need to be used to make a machine make a logical decision or a conclusion. This is like early programming hitches where a program had to be tried out a number of times before it is certified as workable and this takes a lot of time.

A major disadvantage is the Lack of practicality or human judgment intervention. Sometimes data trends can cause impractical decisions to be made. 

It is now a scene of the benefits outweighing the risks. Industries and companies are making huge profits out of machine learning to focus on actions with the highest productibility and profitability. 

Then there will always be the conspiracy theorists who will warn that the machines are taking over.

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