The "Reverse Recommendation Feature" Creates a New You

A one-and-a-half-year-old boy holds his mother's smartphone. He taps the YouTube icon from among the many apps, scrolls with practiced ease, and watches his favorite content. While watching, he simultaneously starts searching for other videos, and when bored, immediately moves on to the next one.

For today's moms of preschoolers, this is now a commonplace sight. For busy moms, YouTube has become an indispensable babysitting tool.

A survey conducted jointly by Dentsu Inc. Media Innovation Lab and Professor Yoshiaki Hashimoto of the University of Tokyo's Graduate School of Information Science and Technology revealed that 23% of infants under one year old have already been exposed to smartphones, and among those infants exposed to smartphones, one in two watches YouTube. (※1)

※1
"The Era of 'Smartphones from Age 0'" - Report from the University of Tokyo Joint Study
 

Thus, the last Heisei generation (or Reiwa generation), born into a smartphone-native world where access to desired content anytime, anywhere is the norm even before they can fully comprehend it, raises concerns about the formation of their interests and preferences.

For example, in the past, there was a behavior called "jacket buying," where people would purchase CDs or records solely based on the design of the jacket. However, today, everything from music, books, and clothing to news can be bought online. E-commerce platforms recommend items to users based on their past purchase (or browsing) history and collaborative filtering (※2), presenting suggestions like "Recommended for You" or "Customers who bought this item also bought..."

※2 = Collaborative Filtering
A methodology that accumulates preference information from many users and automatically infers recommendations using information from other users with similar preferences.
 

YouTube employs the same algorithm, continuously displaying content similar to videos you've already watched. In this environment, smartphone-native generations like those mentioned earlier may unconsciously form their values and preferences within an indirect filter bubble (※3) before they even realize what they truly like.

※3＝Filter bubble
The phenomenon where users only see information they want to see due to features that block information they don't want to see
 

In today's world of information overload and vast choices, I don't deny the convenience of features like recommendations, matching, personalization, and curation that help us efficiently find what we like. But wouldn't it be wonderful if we could also experience that thrilling sense of discovery—that "There might be something here!" excitement you feel in a new shopping mall—or that fresh feeling of "I never thought of that!" that expands your horizons, even within the online space?

Recently, apps like Spotify's "Unplayed" feature have emerged, streaming only songs you've never played before. Going forward, we might see services evolve further, adopting a "reverse recommendation" approach. These would analyze individual preferences and deliberately offer new encounters that would never have crossed paths within your existing interests.

If that happens, even within the online space, which tends to be closed off by individual preferences, opportunities for unexpected discoveries and encounters with unforeseen cultures will emerge. This experience could become vital nourishment for cultivating a discerning eye—one that isn't reliant on others—essential for forming a new self within our information-saturated modern society.

Future Prediction Support Lab: http://dentsu-fsl.jp/