Machine Learning In Our Everyday Life

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When we think about artificial intelligence we might imagine something out of a science fiction movie. However, we might not realize that in one way or another we are using some type of machine learning in our day to day routine. Machine learning is a form of artificial intelligence which allows computers to learn from examples rather than having to follow step-by-step instructions. We encounter machine learning systems daily through our smartphones and our computers, and whether we realize it or not we have become dependent. One thing that’s for sure is that machine learning is already part of our everyday life.

The following are just a few examples on how we constantly interact with ML:

  1. Commuting: Through something so simple as using our GPS or taking advantage of online transportation services such as Uber or Lyft. Using location data from our smartphone, Google Maps can analyze the speed of movement or traffic at any given time. While we are driving, our current locations and velocity are being stored in a central server for traffic management. Our data is then used to build a map of the current traffic, thus giving us route suggestions and estimated time of arrival. As for App based transportation services such as Uber, machine learning systems are used to determine an estimate price of your ride, to minimally optimize your wait time, and to optimally match you to the best service.
  2. Virtual personal assistants/Voice to text: A standard features of smartphones today is voice-to-text. Using spoken commands to ask your phone to carry out a search, or make a call, relies on technology supported by machine learning. Virtual personal assistants (VPA) such as Siri, Alexa, or Google Assistant are able to follow instructions due to voice recognition. Machine learning is an important part of VPA since they collect and refine information, and later that data is used to render better results in accordance to our preferences.
  3. Social Media: From personalizing our news feed to ad targeting, social media platforms use machine learning in many ways. Facebook uses AI for facial recognition, so when you upload a photo, faces are automatically highlighted with suggested friends to tag. Instagram, which FB acquired in 2012 uses machine learning to contextual the meaning of emojis. As for Snapchat, the facial features (lenses) track facial movement allowing us to use animated effects or masks that adjust to the movement of our faces
  4. Online Shopping: Think about how Amazon suggests certain products as “customers who viewed this item also viewed”, machine learning is the technology that helps deliver these suggestions through recommender systems. By analyzing data about what customers have bought before, these systems can pick up on patterns in purchasing history (On the basis of our behavior, items liked, items added to our cart, etc).
  5. Music & TV Streaming Services: Recommender systems are also used to suggest movies or TV shows on streaming services such as Netflix. These systems use machine learning to analyze viewing habits and on how we rate that show/film. Music streaming services (Spotify/Pandora Radio) also use machine learning to suggest music.


One Response to Machine Learning In Our Everyday Life

  1. Avans Rophe Beaubrun February 9, 2018 at 8:31 pm #

    Avans Rophe Beaubrun

    Prof. O’Sullivan

    9 February 2018

    Social and Legal Environment of Business

    Blog Post

    For this week’s assignment I read Mayra Luna’s article titled, “Machine Learning in Our Everyday Life”. Her article emphasized that the distinction between machine learning in science fiction and machine learning in our everyday lives indistinguishable, and that society’s use of mechanization in the fields of commuting, cellular communication, social media, online shopping, and music streaming demonstrates that smart technology is not exclusive to science fiction. Luna provided a few examples for each of these categories, and some of them stood out to me during my initial reading. She wrote that when commuting, people in today’s world often use GPS devices such as Google Maps in order to navigate to unknown locations. I have personally used such forms of technology when I am in a new area that is unfamiliar to me, relying on automated machines to guide my vehicle to the correct destination. In order for the computer to know the correct destination and the path to get there, machines must learn to use an internal software that guides the user to his or her destination. I think one point that Luna makes in her article is that machine learning is not something that our society should be unfamiliar or confused by. Contrary to popular culture’s portrayal of computers as robots prepared to take over the world, machine learning is an everyday creation that is both useful and tangible in multiple areas of life.

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