The video discusses the role of algorithms in shaping our digital experiences, from recommending videos to setting prices. It explains how these algorithms are built and how they work, often without the creators fully understanding the process. The video uses a metaphor of a "bot" that builds and tests other bots to illustrate this process.
The video also highlights the importance of data collection for improving bot performance. It suggests that the more data a bot has, the longer the test it can be given, leading to better bot performance. The video concludes by emphasizing the increasing role of algorithmic bots in our lives, and the need for users to interact with them to improve their performance.
1. Algorithms are prevalent on the internet and are responsible for various actions like recommending videos to watch, deciding what you see on the TweetBook, and even setting prices when you buy something .
2. The stock market is full of algorithms trading with other algorithms .
3. Algorithmic bots are built to answer complex questions that humans can't write simple instructions for, such as identifying fraudulent financial transactions, recommending videos, or determining the maximum price a user will pay for an airline seat .
4. The exact workings of these bots are often not known, even to the humans who built them .
5. Companies that use these bots guard their trade secrets, including how the bots' brains are built .
6. Algorithmic bots are built by creating a bot that builds bots and a bot that teaches bots .
7. The builder bot builds bots, but it's not very good at it. The teacher bot tests the bots, and the students (bots) are built to improve over time .
8. The student bots are tested and built upon until they can perform tasks such as telling a bee from a three in a photo they've never seen before .
9. The wiring in the student bot's head becomes incredibly complicated after keeping many useful random changes .
10. The student bot is only good at the kinds of questions it's been taught to. For example, it's great with photos but useless with videos or if the photos are upside down .
11. Companies are obsessed with collecting data because more data equals longer tests, which equals better bots .
12. The human overseers direct the teacher bot to score the test, which is what the bot is trying to be good at to survive .
13. The student bot gets to be the algorithm because it's point one percent better than the previous bot at the test the humans designed .
14. There are tests to increase user interaction, set prices just right to maximize revenue, or pick the posts from all your friends you'll like the most, or articles people will share the most, or whatever .
15. If it's testable, it's teachable. A student bot will graduate from the warehouse to be the algorithm of its domain .
16. We are increasingly in a position where we use tools, or are used by tools, that no one, not even their creators, understand .
17. We can only hope to guide them with the tests we make, and we need to get comfortable with that .
18. The bots are watching. The algorithm is watching. It won't show people the video unless you do certain actions .