The Rythmos Blog

Machine Learning: Established or Emerging Technology?

Posted by Rythmos on Oct 1, 2019 9:00:00 AM

In today's fast-moving world, artificial intelligence, or AI, is becoming more and more commonplace. We are shifting to letting machines do more of our work, and we are already reaping the benefits from this quickly growing technology. Machine learning, a subset of artificial intelligence, is on the rise as well, but we in the general public don't know as much about it. Here are some key points you should know to increase your awareness of machine learning.

Blog- MachineLearning-Sept2-1

What is Machine Learning?

Since machine learning is a relatively new technology, many people bundle it in with the overarching concept of AI. In truth, machine learning is simply a subset of AI. Not all AI is machine learning, but all machine learning is AI.  Taking it a step forward, machine learning has created its own subsets, such as deep learning.

The main feature that sets machine learning apart from other subsets of AI is its ability to learn on its own. It doesn't require human intervention for some changes, making it more dynamic than other branches of AI. When presented with additional data, machine learning can make changes and adjustments by itself.

Basically, machine learning is an optimization algorithm. This technology aims to minimize errors or maximize success based upon its objective. An early example of machine learning was in 1962 when Arthur Samuel created a computer program that defeated the Connecticut State Checkers champion.

How Can It Help?

We have already seen the benefits of machine learning technology in popular outlets like Netflix and Spotify. With both of these services, users input information about what they already like, and the machine learning algorithms provide choices about potential new hits for each user. Machine learning has also been put to use in many other fields, like agriculture, credit card fraud detection, insurance, speech recognition, and more.

Like any emerging technology, machine learning is not perfect. Many machine learning programs have failed to do what they set out to do, facing issues such as privacy problems, lack of resources, and data biases. Any technology we create can only be as effective as the people who created it. Machine learning can be subject to the same biases that we see in our everyday lives.

For example, machine learning in companies like Google and Twitter has, in the past, picked up on racist or sexist terminology used by consumers of these websites. These incidents led to a backlash from the public and may make this technology take longer to be globally accepted.

Is It Ethical?

The creation of machine learning has brought up several ethical questions. Because of the data biases we've discussed, some people wonder if it is ethical to involve machine learning in the recruiting process. If a company has racist recruiting policies, the technology may pick up on that language and discard the application of a qualified candidate because of a pre-exposed bias.

Another concern lies in the field of health care. Many working in the healthcare industry believe that involving machine learning may not be in the best interest of patients. There may be a conflict of interest with the stakeholders of the company to which the algorithm belongs. Some professionals believe that machine learning technology cannot guarantee to provide the best care if an alternative treatment method would earn money for their company.

Emerging Technology

Machine learning is still a relatively new addition to the overarching picture of AI. It remains to be seen how much of an effect this technology will have in our future. While we have already seen the benefits machine learning can have on our everyday lives, there is still much to be researched and discovered as far as the impact machine learning can have in specific fields.

While all of this technology may seem overwhelming, it is becoming more and more a part of our daily lives. The rapid growth means that AI is expanding before we can even predict its path, leading to many theories about the future of the technology. Some believe AI will be able to save humanity from the areas it's currently struggling in, while others think the concept of a super-intelligence presents a considerable risk.

One thing is for sure: it's becoming increasingly hard to predict the impact that machine learning and AI, in general, will have on our future and the next generations. As technology progresses, will it take on a life of its own, or will our progress within humanity limit it? We'll have to wait and see. We can, however, take advantage of all the good that machine learning is doing in today's world - even if it's just finding our next favorite TV series on Netflix

Topics: Artificial Intelligence, Digital Transformation, Machine Learning

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