Who Do You Listen to and why?

It is almost worse than a truism to say that modern life is getting more complex. We encounter new things ever more frequently. And at least as likely, we find out more about what is going on just under our noses.

It is no huge surprise, therefore, that we need more recommendations about what to look at and look for. Some have referred to this as the business of curation. Fred Wilson writes about it today as “recommendations”. He writes

Web and mobile apps are getting smarter and smarter about each of us and recommending things to us that until recently we had to figure out all by ourselves. It almost seems like recommenders are table stakes these days. You can’t even play in the game unless you can do this sort of thing. And that requires a data science team to sift through all the data on your service and make smart recommendations to your users.

Interesting, but I think not completely correct. Data sifting provides a certain level of value. Like what Amazon does when you pick a book on its platform – you also get “People who read this also liked …” Nice. But that is not the full story. Data cannot compete with people in informing you why people value what they do. So data mining might narrow a recommendation list down to five or ten options. But a person may help you see why one of those options is a million times better than the others.

And yet, we do not find many places where people can plug into platforms in this fashion —- even if they have great ideas and experiences and recommendations to offer. I think this will change.

I

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