Presentation to a panel of investors, including New York Parks and Recreation, Hester Street Collaborative and additional organizations. Parsons School of Design, School of Design Strategies. Created and presented in participation with Naomi Otsu, Christina D and Katherine O.
Special thanks to Naomi Otsu for the amazing illustrations.
This is one of the projects from the Urban Play and Recreation Studio (Spring 2009). The course was co-taught with Professors Miodrag Mitrasinovic and Eduardo Stazsowski in the Integrated Design Curriculum. I have the pleasure of teaching the next course to be taught in this context this term (Spring 2010). A course description is below (after the jump). More information on the upcoming course will be posted soon.
Design Development - Studying Design for Urban Recreation in the 21st Century
This course will be taught as part of the ongoing partnership with the New York City Department of Parks and Recreation, Hester Street Collaborative, and Partnership for Parks (see urls below). As in all Design Development courses students will be expected to build on skills and methods acquired in the Design Research Methods course. Likewise, this section will have the same description and pace as other design development section - including team-based and research-driven problem solving. With its focus on urban recreation for the 21st century and affiliation with partner organizations however the course will have some distinct differences that should be considered prior to enrolling.
The section will pay particular attention to participatory design, community-driven design objectives, and the role of civic action and government responsibility as it relates to urban recreation. Students will engage in field activities that will include participating and documenting partner workshops outside of class time with at least 1 day-long workshop that will scheduled during a weekend towards the middle of the semester. The ultimate goal for this course is to use field research, data collection, and information visualization to produce a series of reports that help to define future areas of investigation that will be undertaken by faculty and students at Parsons as well as by our partners in the coming years.
For more information on our partners please review the following:
http://www.nycgovparks.org/
http://www.partnershipforparks.org/
http://www.hesterstreet.org/
This is an interesting article on the state of the war on data. Laying the perfect foundation for a TFA moment of fairly massive proportions the devices we are creating to collect data are so good at doing it that we can't keep up with the raw material that they've created. An analogy - stuff everything you have into your washing machine, really cram it in there, be sure to add plenty of soap, then turn it on and go get a mop.
This is what the process of iterative data collection might look like...
1. collect raw data in the field > 2. store data > 3. organize data > 4. analyze data > 5. sort data into discrete actionable groups || 1a. with each group treat data as raw and repeat at step 1 - integrating new data as you go. (soak-wash-rinse-repeat)
One solution could be to devise even more computational solutions to analyze said data. This is a problem because I think that people will be tasked with building a "fail-proof" system to do this analysis (which will inevitably fail - a la Things Fall Apart). This is a complicated process that requires careful consideration at each stage. One wrong decision could cause you to effectively "lose" important information. Perhaps they should devise better data collection protocols that has a better chance of retrieving usable data. Maybe there are two approaches to making the collection/analysis system better.
1. Put resources into building a smarter collection mechanism. So when data is collected some analysis is done on the spot - before it is catalogued with other data.
2. Put resources into building a smarter analysis mechanism. So when data is collected there are abundant, redundant layers of analysis ready to retrieve, organize and cross-reference it.
This is doubly interesting to me because an amazing professor, named Ugo Gagliardi, told me a story once about the earliest hard drives (when magnetic discs where becoming fast and small enough to mass manufacture). As he told it there was a kind of crisis in the industry early on. On one hand hard drive manufacturers could spend a lot of money trying to make a VERY smart hard drive controller. This very smart controller would effectively remember where everything was. On the other hand, a much cheaper approach would be to make the hard drives dumb - very very dumb. They spun, they wrote, they read - but the operating system would need to tell these drives what to write and where. The drives we use today are descendants of this early decision and, as you might imagine, the cheaper solution was the chosen. The result was a market with more competition where each member could compete on price to put their product in a computer with a range of operating systems.
*If* I have the problem correctly assessed - I wonder what a good solution is? It's not simple. On the supply side though (meaning the people and places being surveilled) it could get easier to overstuff the machine - the more brittle the system gets the less actual garbage it takes to undermine it. (GI/GO)
I wonder which will be chosen? Smart drones that can analyze on the fly? Fleshware using an army of smart analysts light the WW1 era rangefinders teams? Maybe - smart software, that will be called skynet it will be able to analyze and even direct new missions without having to slow down for our mushy emotional analysis... Eventually it will learn to command drones without us - integrating data and selecting new targets - realizing that the human race is illogical and therefore a threat to successful data collection and analysis (its sole goal). --- The skynet solution seems best :-O
