What is machine learning?
Over the last 12 months, Machine Learning and Artificial Intelligence have dominated much of the conversation around how technology will shape the way people live and work in 2018 and beyond. From marketing to customer service, businesses are finding ways to use machine learning to streamline operations. It’s also become a strong presence in our everyday lives – facial recognition software, search engines and even Netflix all utilize machine learning to tailor a customer’s experience.
At the same time, the widespread argument for long that an organisation’s most important asset is its people as a mindset has started changing recently. Now, in the era of digital transformation, it is believed an organisation’s biggest asset is not its people, but rather its data. Machine learning gives the ability to business leaders to lead informed, strategic decision making and augment business performance by integrating key AI management and leadership insights into the way their organization operates. By automating certain processes, businesses can become more efficient and even lower operational costs. For businesses, there are two basic ways machine learning can impact efficiency: by automating processes and by analyzing vast amounts of data that people wouldn’t be able to comprehend.
Essentially, machine learning occurs when an artificial intelligence (AI) program can analyze data and draw new conclusions that weren’t previously programmed. Whether these conclusions are in the form of finishing a task, answering a question or completing an action, they constitute a form of learning. In addition to automating certain processes, machine learning can replicate a human task and reach a new conclusion, instead of just making that task more efficient. For example, in Evid Science, they set up algorithms to read and understand the medical literature, and so they can find ways to compare medical therapies that humans haven’t done before. In this case, the benefit isn’t really about efficiency, it’s that it would be impossible for a human to read so much content and make sense of it all.
How it works
Machine Learning Involves Two Main Distinctions: Supervised and Unsupervised Learning. The difference between these two types of learning rests with the information the machine has about the data. In supervised learning, a programmer can label what data is right and wrong based on a desired outcome.
In supervised learning you give an algorithm more and more examples of what you want it to do. For instance, you give it pictures and say, for an app, which are pictures of buildings versus not buildings.
In unsupervised learning, a programmer does not label any data and instead the machine must take in as much information as possible, analyze it and pick the best option.
There are other forms of learning and different classifications for them, like Semi-Supervised Learning, Decision Trees or Reinforced Learning, but the two defined types provide a bit of background on two main types of machine learning.
The difference between AI and Machine Learning
These two terms are used almost interchangeably by business owners, but there is a slight distinction between AI and machine learning technology. Machine learning specifically refers to a machine’s ability to learn on its own while AI is more of an umbrella term that refers to a program’s autonomy when completing a task.
How is it used in business?
There are multitude ways that machine learning has found its way into business.
Marketing – One area in which machine learning has begun to thrive is advertising. By gathering and analyzing user data, advertising companies can optimize messages and tailor them directly to different consumer bases. Another aspect of machine learning in advertising is dealing with fraud. As we’re entering an age where bots are prolific and even more sophisticated, with machine learning, it becomes an easy task to quickly and correctly identify real people versus bots designed to behave like real people.
Customer service – Customer service has seen an explosion in machine learning and AI technology. Services, including chatbots and automated assistance have been developed and provided to businesses to simplify customer service issues.
Security – Another way machine learning has been utilized by businesses is through detecting fraud. With machine learning an e-commerce company can, for example, evaluate transactions and determine whether they are fraudulent by using algorithms to analyze data. This is one area where machine learning has been used to protect different businesses. Heightened security is another example of how machine learning can get ahead of a problem and stop it before it hurts a business.
Machine learning and AI have created a strong foothold in the business world. Data is what shapes products and services, improves customer experiences, and ultimately defines brands.
Yet the role of people within businesses cannot be downplayed. It is of fundamental importance that leaders understand the way that businesses work and the way that ideas are collaboratively formed. The fact is that tomorrow’s organisations will be defined by both people and data.
As AI and machine learning radically evolve and expand, it may be worth considering how machine learning or AI could impact your own business.