Augmented Memory Part 1 – Introduction

Google remembers pretty much everything we do online and we are all more or less freaked out about it. But if Google remembers, if Google has a memory, why aren’t we benefitting more from it? Re-finding is defined as the activity to find previously viewed search results and has been estimated to constitute as much as 40% of all online searches.

Search engines are designed first and for-most to help us find new information but they offer a couple features that aid re-finding. Perhaps the most helpful is the color change of previously clicked hyperlinks. The history function is arguably the most useless. Even though many people are aware of it, most people will rather use the normal search function instead of pouring over a chronological list of links. “I remember a rather nice article I happened upon a couple of weeks ago. Now, lets see. It must have been on Tuesday the 14th at 3.28PM.” Not many people’s minds operate in this way, mine certainly doesn’t.

We are already starting to treat the web as an extension of our memory and this tendency is likely to increase as we develop and define cloud computing. Our demands and expectations on search engine capabilities are going to grow. Can we look to our own memory structures for inspiration to improve re-finding (i.e our online memory)? What can we learn from our Long-Term-Memory, Short-Term-Memory, and our episodic memory to create a better experience? A few short design exercises will follow where I explore some of these possibilities.

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