Using Recommendation Systems To Bring A Human Touch To Billions of Humans

Using Recommendation Systems To Bring A Human Touch To Billions of Humans

Tue, 03 May 2016 03:55:31 -0400

Tags: academic, philosophical

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Since I was born, the planet population increased by 50%. (I even heard half the humans ever existed are alive, that's false, more like 6%.) This is all anecdotal but my recollections from childhood speak of a place with just fewer people, where shopkeepers know you by name and expected you to buy certain items regularly. They would know what you like and bring products catering to their audience. Such experience for the most part is lost (it might remain in small towns and such).

Interestingly, human population was rather small for tens of thousands of years. Our human expectations about relating to each other are in line with small communities. This topic is outside my realm, but I heard about it before, Google points to an Urban Ecology paper from 1978 that says

the persistent human propensity to identify with small groups is a consequence of our evolution as a mammal

A machine learning / information retrieval technique that has grown immensely in popularity in the last two decades are recommendation systems. When teaching them before (see my class on the topic, in Spanish), I realized they bring that much needed small village feeling to on-line transactions. When you enter Amazon or Netflix, they "know" you and recommend things based on what they know about you. It is paradoxical that we now need computers to bring a much needed human touch to our interactions.

Moreover, some of the techniques used in recommendation systems (such as user-based recommender), build such small villages as part of their algorithms. In that sense, when Netflix recommends you to watch Anastasia for the fourth time, it actually has enough information to recommend you other people who, you never know, might actually want to form a small village with you.

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