Chicago feels like and is this great big city, but once you scale it down and look over a sizable model, you feel more control of your environment. At least I know I did when I went to the Chicago Architectural Foundation exhibit on Big Data.
When walking through the streets of Chicago, especially in the downtown area, the tall buildings that surround you can be somewhat menacing and make you feel really small and insignificant, but when you are the one looking over the entire city, you get more of a feeling that you are in control and can actually make a difference.
And all the data that we put out every single day can be pulled together, organized, analyzed, and used for greater purposes, such as transforming how we design, build and live in cities. It almost makes me want to participate more to allow them to continue to collect this big data and do something meaningful with it. In a way we’re all in this together. If you tell us what you want, we will give it to you.
But where is this all going?
Scalability is a significant aspect to this exhibit; it helps people visualize everything around them, and puts it in a way that we can understand. It simplifies the entire complex world around us, just like Rushkoff warns in his chapter on complexity. This isn’t necessarily a good thing.
It seems we are trying to take steps towards creating some utopia that I believe is quite unimaginable. Utopia is like perfection, which is ultimately unreachable, but we still do whatever we can to get as close as possible to the ultimate society or utopia.
The big data exhibit shows us the potential for a utopia where we are all one and together, working to make the world a better place completely carved to our needs and wants. It shows a Chicago where everything is in tip-top mint shape, everyone is equal, and everything is just dandy. But there will always be problems with our world and people will always be dissatisfied with something. Each one of us is uniquely different, and it would be very difficult to satisfy everyone’s wants and needs. Of course, we can try, which we are already doing, but could this just turn against us in the long run?
Which now leads into my questions for you:
- What are the advantages and disadvantages in the short- and long-term for such data collection and analysis?
- In this situation, are we fully programming or just being programmed instead?