Machine learning has become more pervasive in society. While consumers are becoming more aware they are interacting with AI when interacting with chat bots, most individuals are not aware of the other forms of artificial intelligence with which they interact.
In fact, most people are not aware of the various types of artificial intelligence and how it plays out in their lives.
The most publicized and visible discussions revolve around job security. Although most automation concerns involve robots with artificial intelligence taking jobs, machine learning is moving rapidly into all industries. Retail specifically has seen huge jumps in technological adoption.
So what is the difference, if any, between machine learning and artificial intelligence? And what does the future spell for retail?
Machine Learning and AI
There is a difference between machine learning and AI, despite people using the terms interchangeably.
AI is a broader term, referring to the ability of a machine or robot to carry out tasks we consider smart. While machine learning can be considered a subset of AI, most in the field consider it more state-of-the-art artificial intelligence.
In basic terms, machine learning is a generalized form of artificial intelligence.
This means machine learning can do any task given to it, rather than specific tasks based on algorithms. The premise is the machine is given access to data freely, allowing the machine to re-write its software as it receives and processes data.
Deep learning is a further subset of machine learning, or the cutting edge of technology. Deep learning is when the machine makes critical thinking choices similar to a human. The machine is built with sensors and transmitters in replica of the human brain and sensory system.
An example of current deep learning is self-driving cars that recognize and respond to obstacles.
Mainstream discussion of machine learning often restricts this technology to health and other high-tech fields. However, the technology is much more pervasive than people are aware.
Machine learning and retail
Yesterday Amazon opened the first cashier-less store to the public in Seattle, Washington. While the Amazon Go store has been in beta testing since 2016, this is the first time the consumer will have access.
While Amazon has been very quiet about the technology, the basics can be seen. The turnstile scans a consumer’s phone. Then 100s of cameras scan and watch to see what a customer removes from the shelves. The system places the items in an online cart, and the system charges the customer once the item moves past the turnstiles.
The technology appears simple, yet it is not. Behind the cameras and scanners is a deep learning system. If the camera cannot be sure which item you picked up, it verifies your shopping history. It watches body type and other features to ensure the item is put in the correct cart.
Behind a smart phone, a few hundred cameras, and subway turnstiles is a machine that is watching behavior. As it’s exposed to more customers and more data, the software will further define its algorithms for accuracy and speed.
AI robots versus machine learning
Amazon is not the only retailer playing with artificial intelligence. As we mentioned in a previous article, Japan’s retail sector has robots already in place. Although prevalent, the robots are often ignored. Their purpose is to assist and answer questions, yet adults avoid most interactions.
A grocery chain in Britain attempted a similar approach, using an AI robot to alleviate simple requests and questions from their human staff. Unfortunately, the software was too general and did not fit the needs of the consumer.
The store fired the robot after a week.
Humans seem not ready for artificial intelligence in consumer shopping. Yet robotic artificial intelligence is not the only option in retail. AI humanoid robots tend to get a lot of attention, partly due to their appearance and human discomfort.
Yet robots are not the next step in retail.
As data scientists can attest, the combination of IoT, big data, and machine learning has opened a door to consumer behavior. Retailers can use information to tailor consumer responses for an individual shopping experience. Though retail technology is not limited to this and robots.
As Amazon proves, machine learning has the potential to completely disrupt our shopping experience. Beyond Alexa’s assistance and Google’s algorithms is a new world combining internet, shopping, and the physical human experience.