There are many ways AI is being used in our everyday lives. Siri, Alexa, Netflix, Spotify, and even Facebook are all examples of AI in action. However, AI is not limited to the realm of personal entertainment, it’s also being used in the business world to analyze millions of pieces of data every minute of every day—in ways you may not realize. For example, AI plays a big part in data mining.
Strong AI VS. Weak AI
There are two types of AI: strong AI and weak AI, according to Claudia Perlich, Chief Scientist at New York’s Dstillery, an advertising technology company that helps marketers target prospects through scientific methods, and a speaker at Pythian’s 2017 Love Your Data conference in New York.
Strong AI refers to machines that can think for themselves. While there is still a long road to get to the point where we can rely on this type of intelligence, for now, we must rely on weak AI—machines that can do intelligent things. Though it’s called weak, it’s actually quite powerful.
“The same way a three-year-old learns that when you touch a hot oven, it burns, they eventually figure out that this is not a smart move and they will get hurt if they do it again. This is the same way we now train machines,” says Perlich.
For example, if you are an insurance company, you can see historical data on who signed up for insurance. You may have a customer relationship management (CRM) system that holds data about your consumers. You can analyze this data in a spreadsheet, make pivot tables, pie charts, and line graphs. Or you can input the data into a machine and tell the machine to figure the data out and give you the info you need, without having the same margin of error you’d have doing it manually.
This is what is referred to as weak AI. Not so weak, though, right?
AI and Machine Learning
When we talk about weak AI, we are really talking about machine learning. Machine learning is a form of computational pattern recognition, in which algorithms learn how to recognize patterns without being explicitly told what the patterns are. Machine learning shows up in a number of advanced applications, including self-driving cars and medical applications such as image-based diagnostics.
“There are millions of different tools out there that now all fall under the umbrella of machine learning. This kind of technology is embedded into our everyday life. If it really works well, you don’t even know it’s there. You only see it when it actually fails and makes mistakes,” says Perlich.
Think of apps on your phone that give recommendations, such as those that can recommend a dining spot nearby you may enjoy or your email service flagging a message that may be spam.
All of these apps utilize machine learning when making their recommendations/predictions to you. In a business setting, it works the same way.
Using AI to make business predictions
A big use for AI in business is making predictions and having stakeholders decide how to best use these predictions to make solid business decisions.
“Applications can range from oil companies analyzing the underground structure with machine learning to identify optimal drill placements. Machines are now assisting medical personnel in identifying breast cancer based on MRI machines and the images they are taking. The TSA is also trying to figure out how to get you to your airplane a lot faster how to identify possible threats,” Perlich noted.
The many uses for AI in business are endless, however, Perlich cautioned that businesses must be vigilant when entering the AI world.
“These methods can go off the road and you want to make sure if you engage with AI, that you have data scientists or an expert involved. This is not for the faint of heart to just try out because you have a new tool to play with,” she said.