Talk 1: Using “Found” Data to Understand a Current Problem, Whitney Erin Boesel
I’ve met Whitney at previous QSEU conferences and she always has colourful hair (can’t recall if blue or red). So it was interesting to hear that the subject of her talk was her pelage. I was somewhat concerned, however, when it was about hair loss, feeling a bit worried when people quantify illness or disease since you have to get prepared for an emotional story. But is was not too heart-wrenching, and I think the main take was that, even though she was not expressly taking notes or quantifying her life, she had a bunch of relatively uncurated data that was easy to collect and analyse (i.e., emails, cat selfies, medical tests), to help see when she started to lose that hair. She seems to think that the hair loss could be due to hypothyrodism, which leads to low basal body temperature (she is always cold), which may have been caused by or related to a concussion she had.
Talk 2: What Show&Tell Talks Do, Steven Jonas
Steve mentioned, and I agree, that preparing a QS “Show and tell talk” is very time consuming. Even though it lasts only 7.5 minutes, people work on it for months. So why do it? He suggested for self examination. In a sense we are all unsure of where we belong, who we are and what we are expected to do. So he thinks that the show and tell talks are an honest and self-relective exercise to answer those questions. He mentioned Michel de Montaigne (http://www.iep.utm.edu/montaign/), who wanted to be a philospher and did not know how, so he just studied himself and wrote essays about own experiences, which ended up being quite popular. He also quoted James Joyce who said that “in the particular lies the universal”.
Talk 3: Conference Welcome, Gary Wolf
Gary started off saying that conference attendees are not interested in another’s vision about a certain topic, like health care, but want to know about personal experiences. He then used an interesting aerial picture of an Ikea megafactory in California that looks like a computer chip, suggesting that the same design is used on many levels, all the way down to the computer circuits (like a fractal pattern). All that is necessary to create and maintain routines, repeated steps.
In the beginning, computers were used to handle data quickly (by managers, scientists and administrators) but now its all up close and personal. At present, however, all this up close and personal computing (ipads, phones, fitbits) can be thought of as self improvement, increasing productivity, or, on the other, can help to instill fear, fear of being controlled and changing behaviour based on someone else’s obscure agenda, creating an ikea routine out of all of us.
However, Gary makes the point that we should not confuse making routines with noticing routines. He thinks that its better to use this technology to notice routines and patterns and get insight into why they are they way they are, rather than formalizing them. My basic take here was that enforcing a routine, like the Ikea factory, is very costly for all invovled, including the planet, while technology is better used to notice “natural” routines and learn from them. The latter also usually last a lot longer. He also mentioned about implicit learning (i.e., learning without rewards), and how 100 years ago it was not really thought to exist. Here I think the point would be that we implicitly learn natural routines. If we can recognize them and learn from them, the world would be a better place.