Tag Archives: Meta

First QS Masters Thesis: How Do the Meetup Groups Work and How Can QS Improve?

I’d like to present to everyone in the QS community the results from my research. I’ve spent almost a whole year now, conducting research for a masters degree in applied anthropology at San Jose State University. For the last six months or so, my research has focused on the QS meetup groups. In my MA program, we are encouraged to conduct a research project where we apply ethnographic methods to produce research that is useful in some way.

For my research, I teamed up with QS and designed a project with the help of Gary Wolf on the meetup groups. New groups are springing up all over the place, and Gary was interested in finding out more about what goes on in some of the groups, and some of the barriers and challenges for organizing. I conducted an ethnographic assessment to basically survey the “landscape” of the meetups. You can read more about it here in the report! (PDF)

Everyone in the QS community I connected with was so helpful and encouraging during the research process. I didn’t get a chance to put acknowledgements in the report, so I’d like to make a few right here.

First I’d like to thank Gary Wolf for coming up with the idea for a research project. I’d also like to thank everyone that I interviewed or talked to during the research process, especially John Amschler and Chloe Fan (for submitting to both rounds of interviews) and Scott Orn and Bo Adler (for being especially supportive). A very special thanks goes out to Alexandra Carmichael. Without her help and assistance with so many things, I don’t think this research would have been possible.

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How to Start Your Own Quantified Self Show&Tell

Since we started the Quantified Self in 2007, we’ve enjoyed watching the idea grow and spread. Recently, I decided to revise our FAQ about how to start a Quantified Self Show&Tell to take advantage of what we and others have learned from doing this many times over. I asked Show&Tell organizers around the world to chime in, and tried to distill all the best practices that we’ve discovered so far. Here it is:

How to Start Your Own Quantified Self Show&Tell Meeting

There are a few highlights I’d like to share here.

You do not need permission.

We urge you to use the common QS tools to share knowledge:

Quantified Self on Meetup

#QuantifiedSelf hashtag on Twitter

Quantified Self Forums for deeper discussion

Quantified Self blog to share videos and summaries

– Remember to ask Three Prime Questions

Have fun.

PS: If you look at the map above, you will see that we are primarily a North American and European “movement.” We would like to learn from users and makers of self-tracking tools in Asia and Africa. Please help us make these connections.



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Joe and Lisa Betts-LaCroix on Meta-QS

Long-time Quantified Self regulars Joe & Lisa Betts-LaCroix co-present their comparison of QS to the better-studied practice of journaling, and their vision for meta-QS research: finding out whether self quantification can actually bring about desired changes in the people doing it.  In their engaging video below, they also suggest how a new age of personal enlightment could result from widespread adoption of QS. (Filmed at the Bay Area QS Show&Tell meetup on 3/24/11 at TechShop.)

Joe & Lisa Betts-LaCroix – The Quantifying Mirror from Gary Wolf on Vimeo.

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Alien Data

A column by Olivia Judson in today’s New York Times touches on both scientific and literary testimony about the self-blindness of human beings. In “Wanted: Intelligent Aliens, for a Research Project,” Judson points out that we are terrible self-analyzers, at least using the tools of our ordinary understanding and perception.

If there is anything living on Mars, it’s going to be weird bacteria or the like, not little green men. Which is a pity. Because what we humans really need is a group of friendly, intelligent aliens to study us, and give us a report on what they find.

The problem is, in many respects it’s difficult for us to study ourselves.

First, there are practical problems. It’s easier, for example, to study organisms with much shorter lives than our own: when organisms have short lives, we can accumulate lots of knowledge about them in a single human lifetime. Hence, we know far more about bacteria, fruit flies and mice than we do about elephants, giant tortoises or sequoia trees.

Another difficulty: it’s hard to do certain sorts of experiments. Many of the experiments we can do on fruit flies would be impractical or unethical to do on people.

But there’s a deeper problem as well: it’s hard for us to see ourselves in an objective way.

Judson gives some good scientific references and some literary testimony about human bias.defoe.jpg She even quotes the 18th century novel Moll Flanders, whose heroine warns young women about the dangers of vanity. I appreciated this mention of Moll Flanders, one of the great instructive books about self-delusion, because from its author comes an answer to Judson’s appeal: we ourselves can be the aliens we seek. Moll Flanders, of course, was not written by an elderly adventuress, but by Daniel Defoe, a novelist, journalist, and connoisseur of human blindness. Moll Flanders is a fictional human, and the words on the page – highly abstract instruments, when you think about it – let us see ourselves as if from the outside.
Among the papers Judson mentions is one by Emily Pronin: “How we see ourselves and how we see others.” Science 320: 1177-1180. (PDF). This is a review article whose footnotes contain an entire education on human nature, and whose moral is that we owe each other a good deal of charity. We tend to judge others based on their outward behavior, not awarding much extra credit for any inward feeling of goodness, which – since we are not inside their head – we cannot perceive. Pronin asks us to perform novelist’s trick of imagination; to indirectly perceive our own self-blindness in the evident self-blindness of others.

Pronin is a psychology professor at Princeton. In another paper, called “Doing Unto Future Selves As You Would Do Unto Others: Psychological Distance and Decision Making” (PDF), Pronin uses some experiments to show that when we make decisions about things that will affect us in the future, we discount the subjective feelings of this future version of our self in much the same way as we discount the subjective feelings of other people in the present. We choose good experiences today even if they will lead to bad experiences tomorrow, because we can’t feel tomorrow. Our future self is a stranger to us.

Many self-quantifiers collect data because they believe it will have some value in guiding their experiments, and in informing their choices. Through collecting data, we fight bias. But by stepping outside ourselves, we also step away from what Pronin, quoting William James, calls the “warmth and intimacy” of our thoughts and feelings. This may be why so much personal data sits around unused. Such data may have implications, but it doesn’t have rewards. I wrote about this problem in my profile of Piotr Wozniak, the inventor of a tool to make people learn things faster. Wozniak thought his software would take over the world. Instead, it is used by a relatively small number of highly motivated, scientifically oriented students; for everybody else, such a tool is not rewarding enough. Most people prefer something like Rosetta Stone, which doesn’t really teach you very much, but which provides a great subjective feeling of learning.

How can we take the experiences of our future selves, and make them subjectively real for ourselves in the present? This is a great problem for self-quantifiers to try to solve. It is key to making our data meaningful. Novelists taught us to feel the inner experiences of strangers. Now, who will make the future feel real?

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On September 10, 2008, twenty-eight people interested in collecting all kinds of data about themselves held the first QS Show&Tell in Pacifica, California. Even before the meeting started, it attracted some good-natured ridicule in the Washington Post. People tracking their most mundane activities? Why? It’s a reasonable question. One of the most interesting things I discovered at the QS Show&Tell is that even people who had wonderful graphs built from self-tracking data were wondering how to put this data to use.
Last night’s meeting began with Kevin Kelly asking us to say our name and five words that contained some information about ourselves. The words give a good sense of who was there. Here is a partial list:

software, math, chess, history, machine learning, athletic performance, language acquisition, cognition, sleep monitoring, unix, physics, design, radio, open-source health research, utopia, self-experimentation, lambda , graphics, usability, life-streaming, futurism, python, jazz piano.

People told me about tracking sleep, work, diet, location, weight, hormone levels, sex, attention, and many other things. I am going to be writing some accounts of these projects in the next few weeks. But for now I want to come back to why. The very first person to present, last night raised this question. He had a beautiful graph of his work, sleep, and other activity, based on data he had been tracking for three years. And he was at the meeting to get ideas about how to extract more meaning out of it.
Over the course of the night, I think he got some answers. The general consensus was that personal data has value as a basis for self-experiments. Aggregating this data can support new types of research. Sometimes the mere act of collecting the data helps lead to a better life through increased awareness. It can also be beautiful – a type of art. And at the end of the night Seth Roberts gave a brief account of how he uses his self-tracking data as a source of new ideas.
Still, I think if we’re to be honest, most of us will admit that the utility of self-tracking in achieving some specified goal doesn’t fully explain its fascination. There’s a compulsion, a curiosity, that seems to operate in advance of any particular use. This made me think about the early days of the personal computing revolution, when hobbyists bought themselves an Altair 8800 out of pure enthusiasm and then sat there asking themselves, “now what?” I’m glad they weren’t embarrassed to tinker. They enjoyed their curiosity, and used it to discover many new things.
The very first issue of Byte, published in September, 1975, tried to explain what the new, amateur-sized digital machines were good for. Note the large headline at the bottom of the cover. I take this is a very good reason.

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