Thursday, June 12, 2008
It is easy to tell from the title of my blog that I am interested in how technology impacts human interaction out in the world, beyond the confines of the desktop. Every so often, usually after reading an article from IEEE, or even Scientific American, I find myself having a math dream, where I'm trying to solve problems that have a lot of "delta", change over time. There is a need for new mathematical models to help us better understand our interactions with technology when we are out and about in our world.
Apple announced the next generation 3G iPhone, which will be in the hands of thousands, if not millions, by July 11th, 2008, out in the land of mobility. The new iPhone will have GPS, and provide users with interesting location-aware applications.
Just imagine the reams of data that this will generate when the multitudes are in action! How will we make sense of this? Will there be a way to ensure that this information will be personally useful? Is it something that we all will care about, if appropriately informed?
Like the child said in Annie Hall, "The Universe is Expanding!". In 2008, the data universe is expanding.
Fortunately, our universe has a handful of gifted scientists who have the drive and mathematical knowledge to think about these problems in real life. Here is a great example of what I am talking about:
Understanding Human Mobility Patterns (pdf) Marta C. Gonza´lez, Ce´sar A. Hidalgo & Albert-La´szlo´ Baraba´si in NATURE Vol 453|5 June 2008|doi:10.1038/nature06958
Barabasi is the director of Notre Dame's Center for Complex Network Research.
Here is the abstract:
- "Despite their importance for urban planning1, traffic forecasting2 and the spread of biological3–5 and mobile viruses6, our understanding of the basic laws governing human motion remains limited owing to the lack of tools to monitor the time-resolved location of individuals. Here we study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six-month period. We find that, in contrast with the random trajectories predictedby the prevailing Le´vy flight and random walk models7, human trajectories show a high degree of temporal and spatial regularity, each individual being characterized by a time independent characteristic travel distance and a significant probability to return to a few highly frequented locations. After correcting for differences in travel distances and the inherent anisotropy of each trajectory, the individual travel patterns collapse into a single spatial probability distribution, indicating that, despite the diversity of their travel history, humans follow simple reproducible patterns. This inherent similarity in travel patterns could impact all phenomena driven by human mobility, from epidemic prevention to emergency response, urban planning and agent-based modelling."
This sort of research sets the stage for people to develop applications to discover and anayze, and predict everyone's daily patterns. In many urban areas, security web-cams are on buildings and street corners. Data collected from webcams, combined with data from GPS enabled cell phones running location-aware programs, might be prove to be useful for emergency planning, homeland security, and crime prevention.
The same mix of data might also prove to be useful to marketers. Can you imagine walking around the city, trying to dodge all of the virtual pop-up and banner ads that might worm out of cyberspace into the streets in the form of electronic billboards, and at the same time, pushed to your mobile device?!
What if all of this information got into the "wrong" hands. Privacy and security issues, in my opinion, have not been carefully considered at this point.