Earlier this week I picked up a copy (or rather downloaded a copy) of Robert Scoble and Shel Israel’s new book The Age of Context. Given my interest in context-aware computing from a design and philosophical perspective, I wanted to see what a tech pundit and business consultant had to saw about this trend. I’ve been following Scoble’s talks and tweets on the subject for a while and always felt that while they are excellent for creating wider awareness, they lack analytical depth. Unfortunately, the same is true of this book. Instead of interrogating new technological capabilities or performing a deep analysis of potential effects on consumer culture, Scoble and Israel instead chose to rely on listing product after product while repeating the same concepts over and over.
But that’s not to say the book isn’t worth reading. One of the most interesting things about it is, even if perhaps not intentional, it frames the discussion of context-aware computing not around the concept of intuition, but rather of the uncanny (as I’ve written about before). That is, instead of relying on colloquial notions of what is “intuitive,” they avoid this trap and instead refer to the function of technology that “knows you” as uncanny, which is, I think, much more accurate. There is only one instance of the uncanny reference, but even the single mention frames context-aware computing as that which is so familiar it’s too familiar. Scoble and Israel later later give this the name “freaky factor,” which is a bit unfortunate, but I think what they’re really getting at is the sense that context-awareness creates a relationship with technology in which the system “knows too much.” The “freaky factor” line is really the difference between familiarity and the hyperfamiliarity.
I wish they would have taken this a step further and attempted a definition of context. They take for granted that readers—and perhaps themselves—have some unarticulated definition of context that needs no further explanation. This is far from the case. There are a number of ways to define context, and each definition frames further discussion in a certain way. At the very least, they could have used someone else’s definition.
Another great point they made is on the concept of big data:
“So, there’s lots of focus on the “big” aspect of data. It sometimes gives us the image of truckloads of data being heaped upon existing truckloads somewhere up in the cloud, creating a virtual mountain so immense it makes Everest look like a molehill. In our opinion, the focus is on the wrong element: It’s not the big data mountain that matters so much to people, it’s those tiny little spoonfuls we extract whenever we search, chat, view, listen, buy— or do anything else online. The hugeness can intimidate, but the little pieces make us smarter and enable us to keep up with, and make sense of, an accelerating world. We call this the miracle of little data.” (Scoble and Israel, Kindle Locations 337-343)
While “miracle” might be a bit hyperbolic, I appreciate that they took care to point out that the “big-ness” of big data does not necessarily equate to deeper insight. This is a point that has been missed in much of the early discourse around big data, but lately many qualitative have been advocating for a more humanistic approach to data. This “little data” is key to successful interactions between users and context-aware systems.
A major downfall of the text is the constant name dropping of various context-aware products and sponsors of the book, and the unrealistic future use cases for these products:
“Perhaps you paid for your adult beverage in advance with a web-stored credit card activated by a nod, blink or gesture your digital eyewear understood.” (ibid, Kindle Locations 606-607).
Or referencing the TV show Cheers:
“When his regulars walked through the door, Sam poured them their usual drink without asking what they wanted. As he handed them the drink, he asked questions that showed he understood what was going on in their personal and work lives. This is a lot better than telling you what people who bought the book you just selected on Amazon also liked. It takes a lot of baby steps to get from there to the Cheers retail experience.” (ibid, Kindle Locations 1050-1053)
These types of example use cases only serve to dampen the importance of studying context. While the book is supposed to have something to do with privacy concerns, the first use case above deliberately undermines any sense of security users can have with a system. And in the second example, Scoble and Israel seem to imply that context-aware computing will soon result in the “Cheers retail experience,” forgetting that greeting someone by name only has value is you actually know the person. Knowing someone’s data and knowing someone as an actual human are two completely different things, but this difference is ignored.
Finally, the greatest downfall of this book is that the authors completely fail to engage with the vast amount of research on context-aware computing. The topic has been vigorously studied by both academics and practitioners in fields ranging from computer science to anthropology to cognitive science. But this history is completely ignored in The Age of Context. The theoretical foundations of their claims, case studies of what has worked and what has not, early prototypical examples of today’s technology, philosophical examinations of meaning and context...all ignored.
I have been compiling a reading list on context if you’re interested in going deeper on the topic. It contains texts from many fields focused on what context is, why it’s important, and how context-aware computing is a paradigm with which designers should concern themselves.
Scoble and Israel had a big opportunity here. I am happy that big names in the tech industry are talking about context. However, I am disappointed that they chose surface level description over critical analysis. To be fair, I’m sure the authors were aware of these criticisms and came across research while writing and thought anything beyond surface description would not be enjoyable for a “general audience.” But if we don’t pay attention to theoretical work, the practice of context-aware computing will never reach its full potential.