What’s your unpopular opinion?
September 17th, 2019
With Love Island as the highlight of (most) of our lives, especially now the football is over; it got me thinking about how data and dating can go hand in hand, and how when it comes to finding love technology is making some serious progress and advancements in such a short space of time.
As a massive Love Island fan, I wanted to have a look at how artificial intelligence (AI) and machine learning (ML) is being used to find love, and how apps like Plenty of Fish and Tinder rely on AI to predict who we will match with and whether we will find the love of our lives with the help of an algorithm.
For any of you that are using dating apps to find love, AI and machine learning is playing its part. If you use Amazon, you’ll be used to seeing the suggested products based on your previous purchases, these apps are using similar algorithms but instead of suggesting shopping they’re suggesting love interests.
As you continue to use the dating sites the AI and machine learning is continuously learning more about you and your preferences. With each swipe, left or right, the technology starts to understand what (or who) you like.
As well as using this data to find who you might match with, it also works the other way around, finding who matches best with you.
One company is using AI, machine learning and deep learning to create an ‘attractiveness score’. By looking at the historic data of who has previously matched with you, your confidence levels, message response rates and your matching preferences it can calculate a score that “will help find the people who would find you attractive and thereby increase response rate”.
While finding love is never easy, unless you are put in a house with 10 other people (and even then, there is plenty of drama!), artificial intelligence and machine learning might just help make it easier to find the man or woman of your dreams.
Do you think AI and machine learning can help you find love? Can algorithms make dating easier?
This blog was originally published on LinkedIn. To read the original blog click here