There’s so much information around these days, how can we possibly deal with it all? Many of us are overwhelmed just by our email, so when you add in everything else (TV, books, newspapers, blogs, twitter, facebook, etc.), it’s just too much.
And yet, we’ve always been faced with more information than we’re capable of processing ourselves. If we’ve been in a state of information overload for centuries, is that really the problem?
In his book The Information Diet: A Case for Conscious ConsumptionClay Johnson argues that the answer is “No!”
The book is very good. Here is how Johnson makes the case on the website to support it:
The problem of “information overload” isn’t particularly new — it’s a problem older than our nation, and a problem that still has not been solved. You know why? Because the problem isn’t information overload. Trying to solve an overload problem is impossible. Are we obese because we have “food overload”?. Of course not— it is not the poor (mostly) inanimate food’s fault. We’re obese because we have “food overconsumption” and while the abundance may make it easy to be fat, it isn’t as though the food’s mere existence is making us fat. Simply putting Paris Hilton in a room full of Tyson Anytizers won’t make her gain weight.
The right question to ask is: How do we deal with information overconsumption?
We’ve gotten dealing with food overconsumption down to a practical science. While there’s 55,000 diet books available to us, they all boil down to the same thing: eat less, exercise more. I think that if you’re interested in improving your focus, productivity, and stress levels, building conscious information consumption and attention fitness into your daily routine seems [eminently] worthwhile.
To do this, we have to filter.
I’ve run across two great examples of very different types of filtering recently. The first is my current favourite iPad app – Zite.
There are at least five forms of filtering, and Zite is a great example of algorithmic filtering. Here is how it works in a picture (made by DDO):
The explanation in words is pretty interesting, so I recommend reading the full description on the company blog. Here is part of what they say:
There are tens of billions of web pages out there and more than two million terabytes of text, images and more are created every hour. So, where in this deluge does Zite start looking for what’s interesting to you? Zite observes what’s happening around the social web, because the community, in aggregate, creates a strong signal for what’s interesting. User-generated content, sharing, commenting and bookmarking have overtaken email and web pages in sheer volume of data created and total time spent online – eMarketer expects 115 million people in the U.S. to be creating content by 2013. What’s important is either happening on, or reported through, social media. What’s more, mining the social web makes it possible to personalize content at the moment you start using Zite for the first time .
The app then tracks what you respond to, and it customises its recommendations so that they are increasingly personalised over time. I’ve been using the app for a month now, and it is incredibly useful.
It doesn’t replace twitter or my RSS feed, but it is a great addition to them.
It definitely provides high quality information.
However, there is a limit to the power of algorithms. There isn’t an algorithm in the world that will tell you first to read Changing the Game by Roger Martin, then A Fine Balance by Rohinton Mistry.
But that’s exactly what Nilofer Merchant did in the list of books that she put together for the latest TED Conference.
Maria Popova also put together a great set of books for TED too.
This is a form of judgement-based filtering – Expert Filtering.
This form of filtering is based on a few key components including judgement, reputation, and trust. Judgement-based filtering is where you get the out-of-the-blue recommendations – connections that are too obscure or too creative for an algorithm to come up with.
The upshot for me is that because I trust Nilofer’s judgement, I’ll read Mistry’s book.
In setting up your information diet, using effective filters is essential. Algorithmic filtering is great. However, to maintain a balanced information diet, you also need to include some judgement-based filtering.
Howard Rheingold calls building your aggregation and filtering routines Infotention. Since attention is becoming one of the scarcest commodities these days, you need to spend yours wisely.
If you do, you will consume better information, and your information diet will be a lot healthier.
Good article. I, too, enjoy Zite and am very impressed by its personalization. Like you, I find that human filters, even experts like Maria Popova, are not enough by themselves to filter information. There are other algorithmic discovery services that complement Zite, too.
Trapit is similar to Zite, but it is available on PCs and Macs, while Zite is only available on iPhones, iPads, and Android devices.
Trapit also lets you follow any topic at all, while Zite limits you to following topics they have defined. In addition, Trapit reaches further back in time when initially finding items for your feed. When you first follow a topic, Trapit will immediately find relevant articles published in the last 30 days. This way, you can jump start personalization by immediately rating a bunch of articles. With Zite, you can only personalize as new articles are published, so it takes longer to get a personalized feed.
Finally, Trapit gets more items on many topics. Zite will only find a set number of articles every day. About 20 or so. There is no way to see more articles than that. Trapit, too, offers a daily digest of best items it finds, but it also allows you to see everything it finds for the topic as it comes in. So if you really want to know everything that is written about a certain topic, especially if it’s a very niche topic, Trapit will be better. http://trap.it
I have a written a full round up of Trapit, Zite, and other information filtering services here: http://colemanfoley.com/post/18856605707/breaking-down-personalized-news-readers
Thanks Coleman, I’ll check that out too.
Hi Tim. This is something that I too grapple with on a daily basis. There is so much interesting stuff to know and so little time! I mainly use Twitter as an expert filtering system, although this presents a problem when people such as you who essentially read for a living suggest too many “must read” articles!
Having said that, I would also like to suggest that effective filtering might stifle innovation. One of the things I love most about Zite is how the algorithm fails. It will often display some completely erratic articles in amongst my selected categories. This means that I read about things I wouldn’t normally read about, which can only be good for innovation.
That’s a really good point Jeremy. That’s partly what Eli Pariser is getting at with his Filter Bubble concept, though he isn’t addressing innovation specifically.
Actually, reading is my hobby – I write and talk for a living. 😀