How Amazon’s Recommendation Engine May Shape Your Destiny

I have recently discovered that Amazon’s recommendation engine is powered by an open source artificial intelligence framework called Deep Scalable Sparse Tensor Network Engine (DSSTNE), pronounced “destiny”.

I have tried to figure out how the Deep Scalable Sparse Tensor Network Engine works but it is very complicated. Essentially it is a narrow AI and uses a neural network for machine learning or deep learning. Let’s just say that DSSTNE is a black box performing very complicated math on a massive amount of input and outputting a list of recommended products.

The input is the wisdom of the crowd, a vast amount of data on what books the entire customer base of Amazon has bought. You can surmise that the books containing the best ideas will have bubbled to the top of the ranking system in narrow domains of knowledge. DSSTNE is not conscious and does not do any thinking. It only does calculations. However, human intentions are added to the system in the form of weighted factors. For example, lets say Amazon wanted to sell you the most expensive book. This intention is mathematically expressed as a weighting factor, emphasizing the contribution of some aspects of a phenomenon (or of a set of data) to a final effect or result, giving them more weight in the analysis. Various other probability factors are added to the input in order to increase the probability that you will be reading the most expensive book available.

Let us say for the sake of argument, that the most expensive book will be the thickest book and therefore the fullest expression of the very best ideas published in the narrow domain of knowledge that is most relevant to your area of interest. What Amazon has done with its “destiny engine” is to increase the probability that you will be reading this book. Their only real intention was to get you to buy more expensive products, but the effect was far more profound.

What sort of books might this lead you to read? Let’s say some expensive, thick books, so dense with meaning that they interrelate with thousands of other books. Let’s start with Maps of Meaning: The Architecture of Belief by Jordan B. Peterson, a book on how deep meaning comes to express itself in myths and stories. This might lead you to read Wired for Story: The Writer’s Guide to Using Brain Science to Hook Readers from the Very First Sentence by Lisa Cron, a book on related topics. Next you may be lead to read Divine Fury: A History of Genius by Darrin M. McMahon, a book on genius, the power to divine the secrets of the universe. And maybe you would even be lead to read The Secret Life of Puppets by Victoria Nelson, a book on the Demiurgic consciousness shaped in Late Antiquity that is emerging anew to re-divinize the human as artists. At this point you might begin to wonder how you came to be reading all these particular books. A terrible suspicion might form in your mind and when you investigate, your suspicion proves correct. There is something fishy and uncanny about Amazon’s recommendation engine. Maybe even something highly improbable unless a whole lot of calculations were done.

What can we guess about the shape of your destiny when it is influenced by artificial intelligence? It will most likely be an emergence of your hidden potential and the emergence of a hidden meaning that is implicit in massive amounts of information.

 

 

This entry was posted in books, Databases, General, Writing and tagged , , , , , , , . Bookmark the permalink.

Leave a Reply

Your email address will not be published. Required fields are marked *

Time limit exceeded. Please complete the captcha once again.