Have you swiped Douyin?
As the most popular short video product nowadays, Douyin has detonated a new era of intelligent recommendation algorithm①. Many people can’t stop using Douyin because the videos it recommends will make people want to watch it continuously. Why is Douyin’s recommendation so accurate? Because it will understand and count your viewing habits when you watch short videos, and recommend more videos of the same type to you by counting the length of time you watch different videos, whether you have finished watching them, whether you have liked, collected, and followed. It will use big data to push the videos that users like yours like to you. Douyin has created a product that netizens around the world can’t put it down through its recommendation algorithm. Many people describe the addictive magic of Douyin as “you can’t stop once you see it.”
How much do you know about algorithms
From a realistic point of view, whether you like it or not, recommendation algorithms have penetrated into all aspects of our lives. WeChat and Taobao are using similar algorithms to recommend content and products for us. Applying similar algorithms can obviously bring more to these companies. economic benefits. Since algorithms recommend things that make us addicted, do algorithms understand us? It depends on how you define “understand”.
for example. Some time ago, I downloaded the small × book in order to buy a gift for a friend. I want to use it to search for the real reviews of some online celebrity products to see if it is worth buying. As soon as I logged in, Xiaox Shu asked me about my hobbies and interests. As a straight man and a science worker, I naturally chose sports, social sciences, technology, and other fields that are related to my work and interests, and then the homepage of the small × book recommended these contents to me. I swiped casually and found that the recommended content was actually not very interesting to me, so I slipped away from the homepage to search for a few reviews of gifts I was about to buy, and then turned it off.
After a few days, I had nothing to do, so I logged in to Xiaoxu again, and this time I casually swiped the contents of the homepage. Because there is a lot of content about food in Xiao × book, and good things are always pleasing to the eye, so as a foodie, I just watched all kinds of food and became fascinated… Later, when I read Xiao × book again, I found that there are obviously more and more food videos, while the sports, science, technology and other content I checked basically do not appear. I realized that Xiao × Book had learned my browsing habits and discovered the love of food that was hidden deep in my heart. So, for the algorithm of Xiaoxbook, what I think I like is not important, but what I actually like to watch is important. This is the essence of recommendation algorithms.
low-level and high-level requirements
So, why does Xiao × Book always recommend food content and ignore the preferences I checked at the beginning?
In fact, we can make a simple classification of human preferences. One is “low-level needs”, such as food, handsome guys and beauties, which more reflect your biological instincts; the other is “high-level needs”, such as Learning knowledge, it satisfies your curiosity and desire to explore, as well as the pursuit of achievement and power (such as the ones I checked). But the latter is difficult to recognize by machine, at least the current recommendation algorithm in this area is not successful, and the machine can’t simulate the “Aha, so it is!” moment when humans learn knowledge, but we often need us Search by keywords.
In fact, there is another system for recommending content in reality, that is, social recommendation through likes from friends. The logic behind it is that the content that a friend likes should be the content that moves him and makes him recognize. Especially in the social circle of acquaintances, when we realize that the content we like will also be seen by others, we will tend to recommend to others those things that reflect his own taste, pursuit and personality. So, if you have a lot of intellectuals in your circle of friends, you will be able to see a lot of content that includes knowledge, thinking, wisdom, and philosophy. That is to say, this recommendation relationship first ensures the quality of the content and its circle attributes through “real person review”. On the other hand, because you will pay special attention to certain friends, the information that these friends like the content will encourage you to consume the content – if you find that the person you have a crush on likes a piece of content, you will also be very happy. Want to know what that content was written about, no? This kind of social recommendation engine is actually the logic adopted by many early Internet products, and it has also created many popular Internet products.
Get out of the control of the algorithm
So why is it that today, algorithms that learn and exploit our “low-level needs” rule the world, while social recommendations are squeezed into a corner? In fact, there are many reasons. For example, people who pursue knowledge and are full of curiosity in this society are far less than those who are bored and need to pass the time. For example, the difficulty of producing content with deep thinking is much higher than that of producing vulgar comedies. For example, it is becoming more and more difficult for people to squeeze in half an hour or even 10 minutes to read an article, but they can easily take 15 seconds… Therefore, the algorithm recommendation will inevitably be biased towards the mainstream.
However, we don’t have to be fully committed to algorithms, let alone fully immersed in our own low-level needs. Although low-level needs are happy, they are not the whole of life. There are more advanced pleasures and pursuits in life that are outside the calculation of algorithms, and they need to be obtained from books and friends.
Therefore, if you want to get out of the control of the algorithm, you can start by recommending the good books you have read to your friends. Maybe some people are very interested in the content you recommend and are willing to exchange their life experience.