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The literacy of Self Data

I was at a presentation from Gary Wolf (co-founder of Quantified Self) yesterday at MediaX in Stanford.

And while I have been at several QS meetups, it was very interesting to hear the story told by Gary. Here is what I got from it:

- Quantified Self introduces a new paradigm in health data collection and usage.

- The current movement is more about building a literacy for self data collection, visualization and analysis than about tracking all the gadgets and apps that can capture personal data.

 

The current standard process is:

- some discovery at the theoretical or chemical level

- trials in animals- case studies

- clinical trials 

 

This is an accepted way to move drugs from the lab to patients, and the data from clinical trials is the gold standard that confirms usage for a specific drugs. Except that what works statistically for the mass may not work for me. It can be argued that Quantified Self is the real gold standard because while clinical trials provide statistical validation there is always the issue of how that specific drug applies to Me: my own case within my own context. And since Quantified Self is about measuring what happens to me specifically, it will always be the very best data that I can get. 

 

So Quantified Self, while coming into the picture from a very different angle (computing becoming personal to the point of capturing my vital signs and my moods), opens the opportunity to revolutionize healthcare by helping us move away from the tyrany of the mass into personal customized diagnostics and treatments.

 

The open issue of course remains the literacy of Self Data capture, visualization and analysis: while many people have all the smarts needed to do the right job, they do not necessarily use the tools that are available because they do not know about them, or do not understand them, or do not have an easy way to implement them. And we may not have all the right tools yet.

 

This is why the current QS meetings are about sharing personal stories about data collection, visualization and analysis, so that we can all learn from each others what can be done and how. 

 

Interestingly enough the world of sports, which is often times considered to be on the opposite side of academia (muscles vs. brain), is a place where best practices to optimize performance are very advanced. Athletes are very good at utilizing specific techniques to improve their bodies and health. Unfortunately there are usually little to no scientific papers to document these techniques.

The good news is that QS meetups have proven to be a good place to (re)capture this knowledge.

 

Definitely we have a fascinating journey ahead of us.

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