Recommended by algorithms !

While I was thinking about the post title( binging vs recommended by the algorithms) I realized that there is a page on whether it’s binging or bingeing [0]. And thankfully Microsoft bing did not become popular enough to be used as a verb.

This morning while commuting I was wondering about what David Foster Wallace [1] said in one of his videos to have empathy for fellow beings. So here I was on my daily metro ride observing people, having resisted the urge to take out my phone or the novel. Most of my fellow beings were lost in their phone – remember how we used to say lost in thought. Now our phone is our thought, an extension of our thoughts, made possible by data churning machine learning algorithms. The algorithms learn about us, categorically places us in sets and subsets, and then do their recommendations. Hmm, let’s see an Indian who lives in Singapore, so facebook ad settings should be likes Chinese, Indian, Buddhism philosophy. Go have a look at your Facebook ad preferences and prepare to be astounded by the amount of data FB has on you. The image below is my ad preferences :

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But without digressing coming back to diurnal ride ceremony, there was a lady worried if his son was a street singer or a street busker. Another one was lost in mobile game Contra. Some were glued to whatever Netflix/Amazon Prime/ (or the chinese equivalent of NetFlix – https://www.iqiyi.com/ ) series they swear by.

By the way if you are recommending a series, it means the machine learning algorithm match was a success. It successfully interpreted your preferences.

This is how a typical Recommendation enginethis looks for a layman.[2] [3]. Probably I might cover it on my tech blog https://medium.com/@arunabh010

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Other day I was lamenting how previously we were warned of the perils of TV – the idiot box. But now talk to any of your friends, and conversation inadvertently ends up talking about the latest shows. It’s our daily prayer on the altar of our digital gods ( American Gods fans?) and us paying obeisance. And like a clockwork ask anyone, ya post work we end up watching Netflix. “Ya man have to watch something while having dinner “.

Exempli Gratia:

  • Sacred Games 2 isn’t as good as season 1 yaar!
  • The new season for mind hunters is out.
  • We watched stranger things together.

But then this word of mouth still counts as a human-based recommendation engine, right? Now Netflix needs to somehow track these conversations and make an algorithm for “word-of-mouth” publicity. Huh (I need to see if this thing exists or not) Ahh it does welcome home Alexa and Google Assistant [4]

It’s like the whole generation (including me mea culpa !) has been bogged down by this phenomenon. And business-wise all the cable tv companies( those still in existenence) are still wondering whether they should have distributed “Innovator’s Dilemma by Clayton Christensen”[5] to their execs when the time was right.

 

References

[0] Binging vs Bingeing https://www.writerscentre.com.au/blog/qa-binging-or-bingeing/

[1] This is water https://www.youtube.com/watch?v=8CrOL-ydFMI

[2] Netflix recommendation engine https://uxplanet.org/netflix-binging-on-the-algorithm-a3a74a6c1f59

[3] https://www.kaggle.com/laowingkin/netflix-movie-recommendation

[4] Alexa based marketing https://hbr.org/2018/05/marketing-in-the-age-of-alexa

[5] Disruptive Innovation http://claytonchristensen.com/key-concepts/

 

 

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