SXSW Interactive 2016
Your Fitbit Will Never Know the Real You
New technologies promise to track behavior and generate insights: monitor your activity level, review your location data, learn where your time goes. These "insights" are useful but just scratch the surface. We have incredible new ways to gather personal data, but we need a new, active relationship with our data to find meaning. We'll discuss our processes, failures, and successes in turning data into self-understanding. We've measured unconventional data like chat logs, alcohol consumption, headache frequency, and email addiction, and combined it with other data to ask, answer, and ask more questions. We've found important, surprising results which will never show up on a Fitbit dashboard.
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Takeaways
- What kinds of things can I measure about myself, and how can I choose tools to track and analyze the data?
- What are best practices for designing a self-tracking experiment?
- What are surprising things you can learn from failures in self tracking, data management, and data analysis?
Speakers
- Glen Lubert, Entrepreneur, Startup
- S. Shelly Jang, Sr. Data Scientist, AT&T
- Steven Zhang, Software Engineer, Tableau Software
- Mark Wilson, Software engineer, Freelance
Organizer
Glen Lubert, Entrepreneur, Startup
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