Topic Archives: Conference
“That’s insane! I want to try it.”
Bethany Soule is the co-found of Beeminder, a commitment tool which she characterizes as “goal-tracking with teeth.” Her and Daniel Reeves, the other founder, have spoken on how they tracked the development of the tool and integrating it with other QS tools.
In this talk from QS15, Bethany tells of how she was inspired by Nick Winter’s “Maniac Week“, to focus solely on working for an entire week. She shares what she learned from doing this multiple times, from tools for reducing distractions to tracking accomplishments and ensuring accountability. You’ll also find out how many hours she was actually able to work.
Here is the time-lapse of Bethany’s Maniac Week, as well as, her blog post on the experience:
“I don’t have a concrete goal. I don’t have a concrete aim to advance myself. It’s a way to explore different aspects of my life through data.”
Since 2009 Jacek Smolicki has experimented with using personal data as a mode for artistic exploration. In this talk, he presents some of his practices:
To learn more about Jacek’s practices, explore his website. Check out other examples of self-tracking as artistic expression with talks from Laurie Frick and Alberto Frigo, and pieces from the art exhibition at the 2015 QS Conference in San Francisco.
From the Quantified Self Public Health Symposium.
Larry Smarr’s major contributions to scientific progress are well known. A physicist and the founding director of the National Center for Supercomputing Applications (NCSA), he helped bring the power of computing to scientific research at a time when computers will still highly specialized instruments. Today he is the Director of the California Institute for Telecommunications and Information Technology (Calit2), one of the most innovative research institutes in the world.
He’s also an avid self-tracker, using his own data to correctly self-diagnose the onset of Crohn’s disease. At the 2015 Quantified Self Public Health Symposium, Larry spontaneously launched the meeting with a description of what it was like to be at NCSA in the early 90’s when his student Mark Andreessen, the creator of the first popular Web browser, could review every new website in the world by hand. “We could keep up with that little bit of the exponential.” Larry asked us to consider that a similar experience of scaling lies ahead of us in the Quantified Self movement. What happens at the birth of new technologies and new fields of knowledge, when very early participants get to know each other and reflect together on what values and uses will be encoded in our tools, can influence developments that affect hundreds of millions of people.
In this fascinating talk Rocio Chongtay shares her novel and thoughtfully designed experiments in using music to adjust her concentration and relaxation depending on what she’s doing. Using a consumer EEG device from Neurosky, Rocio tried different types of music while tracking the relaxation and concentration dimensions identified by the Neurosky algorithm. She had experience experimenting with Neurosky in her lab, and then turned these techniques on understanding something about her own mind.
“My name is Lane Desborough, and I’m going to spend the couple of minutes talking with you about Nightscout on behalf of the many collaborators who have been part of this ongoing program. But first I want to introduce you to my son, Haydon. He just got a new quadcopter and he has hacked it to turn it into a bomber so he can drop water balloons on his younger brother. He’s a happy, healthy fifteen year old. But that wasn’t always the case. Five years ago Haydon was diagnosed with type 1 diabetes, and our family’s life took a radical right hand turn…”
Nightscout, which Lane describes in this wonderful talk, allows people with people with diabetes and parents of kids with diabetes the see real time data from a blood glucose monitor on a mobile device. While similar efforts are underway among manufacturers, leadership is coming from patients and caregivers.
The quality and commitment here can inspire anybody who is thinking about how QS tools fit into new forms of knowledge and cooperation. The projects Lane discusses in this talk have continued to grow and evolve. Supported by a remarkable group of activists and a technically expert community made up mainly of people with diabetes and parents of kids with diabetes, contributors to these projects have created a suite of tools that can dramatically improve self-care.
For instance, a couple of weeks ago I saw this tweet from Howard Look, founder of Tidepool:
Did you know that people with diabetes have been building their own artificial pancreas systems? Read more about Nightscout, the Open Artificial Pancreas System, and related projects at these links:
Kouris Kalligas, a long time participant and contributor at Quantified Self meetings, is the creator of the very easy to use data aggregation service AddApp. AddApp is an iPhone app that makes it simple to gain insights from data gathered on dozens of different devices. While running his startup, Kouris has also been doing ongoing self-tracking experiments. At QS Europe 2014, he gave a excellent show&tell talk about his sleep, diet, and exercise data. In the talk below, he discusses using mood data in combination with calendar data to reflect on the relationship between emotion, experience, and self-image.
It’s been an honor to have Beeminder founders Daniel Reeves and Bethany Soule participating in Quantified Self meetings, giving us a chance to watch the evolution of their very useful tool for setting and achieving personal goals. These days they are working on the forefront of device and service integration. In this talk Daniel gives a brief explanation of how to bring data into Beeminder with minimal hassle.
(Note Daniel’s generous shout-out to another great QS toolmaker, Rescue Time.)
Let’s start 2016 with a very interesting talk by Randy Sargent about how to visualize the very large data sets produced by some kinds of self-tracking. Randy’s idea about using spectrograms, normally used for audio signals, to create a portrait of your own time series data, is completely novel as far as I know. If you have tried something similar, please get in touch.
In this fascinating short talk by geneticist Jim McCarter, we see detailed data about the effects of a ketogenic diet: lower blood pressure, better cholesterol numbers,and vastly improved daily well being. Jim also describes the mid-course adjustments he made to reduce side effects such as including muscle cramps and increased sensitivity to cold.
Jim begins: “When I tell my friends I’ve given up sugar and starch and get 80% of my calories from fat, the first question I get is: Why?”
The rest of the talk is his very clear answer.
I talked with Vinod Khosla over the summer about machine learning and the Quantified Self.
Khosla was a founder of Sun Microsystems and is one of Silicon Valley’s most experienced investors in Quantified Self companies. His portfolio includes AliveCor, Ginger.io, Jawbone, Misfit, Narrative, and many other toolmakers that people doing QS projects will recognize. In our conversation, I ask Vinod about the role machine learning can realistically play in QS practices.
Below are links to three papers Vinod mentions in the interview:
Beck, Andrew H., Ankur R. Sangoi, Samuel Leung, Robert J. Marinelli, Torsten O. Nielsen, Marc J. van de Vijver, Robert B. West, Matt van de Rijn, and Daphne Koller. “Systematic analysis of breast cancer morphology uncovers stromal features associated with survival.” Science translational medicine 3, no. 108 (2011): 108ra113-108ra113.
Ioannidis, John PA. Why Most Published Research Findings Are False. PLoS Med 2, no. 8 (2005)