GPS

Software-sorted geographies

Jess Hemerly — Wed, 30 Jan 2008 11:12:05 -0800

Description

Abstract:

This paper explores the central role of computerised code in shaping the social and geographical politics of inequality in advanced societies. Arguing that ‘software-sorting’ techniques are now being widely applied in efforts to try and separate privileged and marginalised groups and places across a wide range of sectors and domains, the paper analyses recent research addressing three examples of software-sorting in practice. These address physical and electronic mobility systems, online Geographical Information Systems (GISs), and face-recognition Closed Circuit Television (CCTV) systems covering city streets. The paper finishes by identifying research and policy implications of the diffusion of software-sorted geographies within which computerised code continually orchestrates inequality through technological systems embedded within urban environments.

Source

Graham, S. (2005). "Software-sorted geographies." Progress in Human Geography 29 (5):562-580.

Bruce Sterling SIGGRAPH 2004 speech "When Blobjects Rule the Earth"

Jess Hemerly — Wed, 30 Jan 2008 10:58:32 -0800

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From the spech:

So what's a Blobject? And why might they rule the Earth?

Since I write about design quite a lot, sometimes people think I made up that word, "blobject". If you Google it, my name pops right up, but I didn't coin the term. A famous industrial designer named Karim Rashid made it up, and he wrote about it in a book aptly called "I Want to Change the World." A good book, very educational, you should buy it and read it. I did. Karim's not kidding.

A Blobject is commonly defined as "an object with a curvilinear, flowing design, such as the Apple iMac computer and the Volkswagen Beetle." But computers and cars are just end products, they're not the process. The truth about a blobject is that is a physical object that has suffered a remake through computer graphics. It was designed on a screen with a graphics program. A blobject is what a standard 20th century industrial product, a consumer item, looks like after your crowd has beaten it into shape with a mouse.

Source

Sterling, Bruce (2004). “When Blobjects Rule the Earth”, SIGGRAPH, Los Angeles, August, 2004

Geospatial technology blurs the boundary between cyberspace and urban space to form geocomputable cities

Paul Torrens — Thu, 10 Jan 2008 21:21:06 -0800

Description

The boundary between computing infrastructure and urban infrastructure were blurred to a fuzzy line some time ago and much has been written (and speculated) about on the ramifications of their consociation across a spectrum of topics, from sociology and public policy, to cyborgs and robotic management [1, 2, 3, 4]. Somewhere along the way to the fusion of the computational and the urban, cities became geocomputable spaces.

A number of catalyzing factors are, perhaps, responsible. First, software and computing became increasingly relevant in the management and production of space [5], across the board. Urban utilities are now monitored and managed as large-scale Geographic Information Systems of sensor networks and automated notification systems.

Second, cities and the throngs of people, vehicles, and things that pulse through them have become ambient physical and social infrastructure for large-scale distributed communications networks: digitally interactive crowds with hand-held devices, ubiquitous Wi-Fi signals leaking into the airwaves, and a spaghetti-knot of fiber sequestered in the urban fabric.

Together, these have provided the network-cloud for massively distributed information exchange and computation.

Fourth, digital positioning systems became important in cities, guiding fleets of bike messengers and mail trucks to their destinations with optimal locational accuracy; then, they became ubiquitous, public, and really cheap.

Fifth, near-field and locative technologies based around RFID readers and tags have become ridiculously cost-effective, to the point where individual stores can set up their own geo-grid for automated asset tracking, monitoring, and management. (The navi-wagon shopping cart is just one of many examples.)

Sixth, pattern recognition concentrated on spatial structures of, and spatial compositions in, the urban fabric became useful across applications, from monitoring cars and their licenses remotely in downtown congestion pricing schemes, to law enforcement and policing.

Seventh, intelligent transport systems with strong geospatial components enjoyed a surge in their development and deployment in cities, within roads and across transit systems.

Your location in cityscapes, and your geography in socio-technical urban networks, will become a commodity
Business models fashioned around location-based services have blossomed in very recent years, thanks in large part to a drop in the cost of integrating Global Positioning Systems (GPS) with mobile devices (cell-phones, handheld gaming platforms, personal display assistants, digital cameras, and so on). Concurrently, alternative positioning technology and algorithms based on triangulation of cell-phone and Wi-Fi signals with base stations and access points have evolved to the point where the positional accuracy they produce is useful for consumer mapping. Knowing where you are in a cityscape--and its mirror world in cyberspace--and, particularly, what is around you, will continue to become a commodity that consumers will pay for. At the same time, maps will continue to evolve as the new portal between meatspace and cyberspace, particularly for urban activities, services, and markets, with many groups jostling for position in this new emerging commodity-scape, where commercial interests can pay for brand-name territory. Undoubtedly, there is keen interest in harvesting users’ place-based search and queries to train a new generation of geospatial AI for location-based services. What remains to be seen is whether this arena will become dominated by traditional geospatial technology providers (the potential for Garmin’s nuviphone to erode iPhone market share because of superior positioning technology is an early example [6]) or existing cyberspace behemoths (Intel and Microsoft both have long-standing R&D investment in alternative positioning technologies, for example [7,8]).

The potential for function creep
The emerging glut of technologies used to geoprocess and geocompute in urban areas is so massive that it is difficult to keep track, manage, and regulate them. This latter point is particularly salient with respect to the potential emergence of function creep in the use and application of these technologies and the vast stores of data they will produce. Geospatial technologies of this kind create a bridge between cyberspace and cyberplace and users’ Online data-shadows can be potentially traced to the real-world with greater ease. This creates new emerging opportunities for marketing, advertising, and commercial data-mining, and as with most emerging technologies, it creates privacy concerns. Already, geodemographics for marketing have begun to farm these data-sets, and algorithms for creating privacy masks and filters are emerging. How these data and services creep across interoperability boundaries to add value to related (or unrelated) services will shape the future development and application of these technologies.

The potential for things to go wrong
What happens when geocomputable cities are hacked, crash, or succumb to malware or viruses? Thus far, we have been spared any serious locative-based mechanical, software, or system failures. As geocomputable cities begin to play host to intelligent highways and robotic drivers, thorny issues regarding positional accuracy and spatial ontologies will likely surface. These are not issues that are easily solved with version 2.0 iterations to existing technologies and they pose grand challenges for future research and development.

Geospatial technology will expand the Digital Divide
Many of these technologies already divide and partition urban spaces based on place-time tuples that authenticate some people as valid participants in particular buildings, places, and spaces at particular times (at the simplest level through RFID-embedded card access, for example). The potential for socio-technical spatial polarization among the geodigital valids and invalids is profound [9]. As geospatial technologies develop in sophistication and their application-sets grow and expand, newly segregated divides may well emerge.

References
[1] Mitchell, W. J. (1995). City of Bits: Space, Place, and the Infobahn. Cambridge, MA: The MIT Press.

[2] Batty, M. (1995). “The computable city”. Paper read at Fourth International Conference on Computers in Urban Planning and Urban Management, July 11th - 14th, 1995, at Melbourne.

[3] McCullough, M. (2004). Digital Ground: Architecture, Pervasive Computing, and Environmental Knowing. Cambridge, MA: The MIT Press.

[4] Rheingold, H. (2002). Smart Mobs: The Next Social Revolution. London: Perseus Books.

[5] Graham, S. (2005). “Software-sorted geographies”. Progress in Human Geography 29 (5):562-580.

[6] Jonson, Joel (2008). "Nuviphone: Garmin Announces First Credible iPhone Competitor, boingboing.net, January 31, 2008.

[7] Knies, Rob (2005). "Using Wi-Fi to make your device find where you are", Microsoft Research News and Highlights.

[8] Cheng, Yu-Chung; Chawathe, Yatin; Krumm, John (2003). "Accuracy characterization for metropolitan-scale Wi-Fi localization". Intel Research IRS-TR-05-003.

[9] Dobson, J., and P. Fisher. (2003). “Geoslavery”. IEEE Technology and Society Magazine 22 (1):47-52.

Signals

Software-sorted geographies

Geoslavery

The Computable City paper

Broadening Amateur Participation in Science

Alex Soojung-Kim Pang — Tue, 23 Oct 2007 11:10:30 -0700

Description

Interested amateurs are likely to have increased opportunities in the future to donate resources, time, or labor in support of scientific research, thanks largely to low-cost distributed computing.

The growth of peer-to-peer networking systems has created opportunities for amateurs to play a role in scientific research by donating computer time or labor. The pioneers in this arena are SETI@Home, Folding@Home, and other projects that invite people to load a piece of analytical software onto their computers. During periods of inactivity, the software downloads some data, analyses it, and then sends back the results. These programs enable those with computers to "donate" processor cycles to computationally intensive scientific or charitable activities.

It's important to remember the difference between:

Doing science on a personal level, and for the individual being involved in the science as a scientist. Advanced computer systems could help leverage individuals.

Exploiting distributed resources (e.g., SETI@Home) without the individual participating much themselves. Other examples are informed participation in medical developments (e.g., on the individual). In the future, people (and their houses, etc) will have lots of sensors, so possibilities here are substantial, especially for informing social policy (energy use, etc).

Gathering data, typically geographically specific data, or otherwise being a lab assistant, the individual devoting time and basic labour. Involving school children here, especially, can make them feel part of doing science, which will (hopefully) influence them for the rest of their lives.

SETI@Home, Folding@Home and other experiments have shown that amateurs can donate their time to analyse scientific data directly. The NASA Clickworkers system put volunteers through a simple training program to do routine analysis of Martian landscapes. The success of the system suggests that complex professional tasks done by highly trained and salaried individuals can be reorganized to tap a vast pool of tens of thousands of trained volunteers.

The strategy of Clickworkers and SETI@Home is to make science more accessible by making pieces of it very simple and by taking advantage of low-cost computing and communications. In the future, it is possible that more scientific research projects willdraw upon volunteered equipment or labour. In addition to distributed computing projects and efforts to mobilize volunteer observers, volunteers could be involved in gathering data using existing mobile communications or computing technologies -- for example, taking pictures of flora and fauna at specified times, or noting the GPS coordinates of certain objects.

Peer-to-peer and analytical computing projects have shown that it is possible to mobilize massive quantities of unused processing power or unskilled labour to do basic data analysis; such groups could be mobilized by advocacy and interest groups (e.g., supporters of breast cancer research or environmental causes) to create massive networks of volunteer labour. Expert knowledge that currently is underused in scientific research could be harnessed by custom-designed instruments with simple interfaces Finally, a new generation of sensor and smart dust technology could be used to make small instruments that volunteers carry with them, scatter about their environments, or leave in specific places, thus increasing scientists' mobility.

This will be enabled by:

Falling cost and increasing ubiquity of mobile communications and computing technologies
Growth of the open source movement
Establishment of the precedent of distributed computing projects in the 1990s and 2000s

Early indicators include:

"Proliferation of open-source, distributed computing and analysis projects such as Clickworkers and SETI@Home"

What to watch:

Volunteer projects are organised around popular issues like climate change and pollution.
NGOs and advocacy groups like Greenpeace or the World Wildlife Fund organise research projects for amateurs.