OpenAI Reveals Sora Feed Philosophy: “We Won’t Allow Doomscrolling

by

OpenAI Reveals Sora Feed Philosophy: “We Won’t Make You Doomscroll”

  • Creation first, consumption minimized is the core principle
  • New concept recommendation system that can adjust algorithms with natural language
  • Safety measures from the creation stage, a strategy completely opposite to TikTok

What Happened?

OpenAI officially announced the design philosophy of the recommendation feed for its AI video generation app, Sora.[OpenAI] The core message is clear: “A platform for creation, not doomscrolling.”

While TikTok has been criticized for optimizing viewing time, OpenAI has chosen the opposite direction. Instead of optimizing feed dwell time, it prioritizes exposing content that is likely to inspire users to create their own videos.[TechCrunch]

Why is it Important?

Frankly, this is a pretty significant experiment in social media history. Existing social platforms have maximized dwell time for advertising revenue. The longer users stay, the more money they make. The result was addictive algorithms and mental health problems.

OpenAI is already generating revenue with a subscription model (ChatGPT Plus). Since it doesn’t rely on advertising, it doesn’t need to “hold onto users.” Simply put, since the business model is different, the feed design can also be different.

Personally, I’m curious if this will actually work. Can a “creation-encouraging” feed actually maintain user engagement? Or will it eventually revert to dwell time optimization?

4 Principles of the Sora Feed

  • Optimize for Creation: Induce participation rather than consumption. The goal is active creation, not passive scrolling.[Digital Watch]
  • User Control: You can adjust the algorithm with natural language. Instructions such as “Only show me comedies today” are possible.
  • Connection First: Prioritize content from people you follow and people you know over viral global content.
  • Safety-Freedom Balance: Since all content is generated within Sora, harmful content is blocked at the creation stage.

How is it Technically Different?

OpenAI has developed a new type of recommendation algorithm using existing LLMs. The key differentiator is “natural language instructions.” Users can directly describe the type of content they want to the algorithm in words.[TechCrunch]

Personalization signals include Sora activity (likes, comments, remixes), IP-based location, ChatGPT usage history (can be turned off), and the number of followers of the creator. However, safety signals are also included, and harmful content is suppressed from exposure.

What Will Happen in the Future?

The Sora app ranked first in the App Store within 48 hours of its release. It had 56,000 downloads on the first day, and tripled on the second day.[TechCrunch] The initial reaction was enthusiastic.

But the problem is sustainability. As OpenAI acknowledged, this feed is a “living system.” It will continue to change based on user feedback. What happens if the creation-centric philosophy conflicts with actual user behavior? We’ll have to wait and see.

Frequently Asked Questions (FAQ)

Q: How is the Sora feed different from TikTok?

A: TikTok aims to keep users engaged by optimizing viewing time. Sora, on the other hand, prioritizes showing content that is likely to inspire users to create their own videos. It is designed with a focus on creation rather than consumption.

Q: What does it mean to adjust the algorithm with natural language?

A: Existing apps determine recommendations based only on behavioral data such as likes and viewing time. Sora allows users to directly enter instructions such as “Only show me SF videos today” in text, and the algorithm adjusts accordingly.

Q: Are there any youth protection features?

A: Yes. You can turn off feed personalization or limit continuous scrolling through ChatGPT parental controls. Youth accounts are by default limited in the number of videos they can create per day, and the Cameo (video featuring others) function also has stricter permissions applied.

If this article was helpful, please subscribe to AI Digester.

Reference Materials

Leave a Comment