Computers, Society, and Nature

Poole and Ball’s “Eye Tracking in Human-Computer Interaction and Usability Research: Current Status and Future Prospects” gives an introduction to eye tracking technology with a brief history of its uses and designs. For our purposes as geographers, it is useful to think about to what ends this technology may be used, and how we can incorporate eye tracking into applications that are spatial in nature.
While the uses noted (user interaction with a website, text or tool) mostly focus on a stationary user looking at something that is fixed in space, incorporating motion into eye tracking analyses may be very illuminating. I think specifically of analysis of urban planning that might incorporate universal design to make cities easier to navigate, more physically accessible and more aesthetically appealing. By tracking where users look when moving through a set urban landscape, we could infer improvements such need for curb cuts, street sign placement and in more commercial interests, billboard and advertisement placement. The use of eye tracking might help planners to make cites more easily navigable. One could also use this technology in augmented reality applications such as virtual tours of a given place or in identifying points of interest.

One thing that I hoped the article would explore further was research methodology. It might be interesting to know how studies using eye tracking technology attempt to account for the inherent bias of a study who knows to be being observed, or the aims of a given project.

Wyatt

Poole and Ball provide readers, with little to no knowledge of eye-movement tracking, a brief overview of the techniques, equipment, and application of the research. They, unfortunately, do not include a section devoted to geo-visualization, which would make this an exercise in read and repeat. Or fortunately, in that it provides us with a broad spectrum for interpretation.
While eye-movement tracking has made major leaps from its original design, including a metal coil affixed to the cornea, it still fall shorts. According to Poole, researchers still have not developed a standard interpretation of results. An example of which includes the duration and frequency of fixation on a target. Depending on the situation, multiple longer durations are considered positive, in that subjects are more interested in the target, or negative in that subjects take more time to encode the visual information. This does not mean the field does not have applications in GIS, and geo-visualization.
As Poole points out, eye-movement tracking techniques can be used to substantiate claims of what may be visually appealing on a case-by-case basis. GIS serves as a way of conveying spatial data in the form of maps. If maps are responsible for the quick and easy conveyance of information, visually optimal maps may be developed with the help of eye-movement tracking. Whether or not the participant is interested in the topic is up to the researcher.

AMac

M.C. ER attempts to untangle data management from the impact of data use. In doing so, though, he attributes far more value to Decision Support System than it merits. The age of the paper (1988) may have something to do with this, but the idea that DSS will be able to support all levels of decision-making is excessive. Furthermore, the description of DSS makes it seem that it will eventually become autonomous. At least, that seems to be the goal. By that point DSS will have to be relabeled, DMS, Decision Making System. The reason being that M.C. ER describes systems that can act on their own decisions. He even furthers the narrative by mentioning artificial intelligence in the concluding statements.
As for GIS, System or Science, it still has not quite reached the point of making decisions in place of top management. Let alone the fact that GIS has a very narrow spectrum of applications. If we were to use GIS as a case study of the success or failure of DSS, it would fall short of making decisions for management, but is definitely useful in supplementing the knowledge set of the decision maker.
Then again, that is not to say that it has failed or succeeded as a DSS, in that the definition of a DSS is, according to M.C. ER fluid and open to interpretation, considering the numerous attempts at classifying the field.
One assertion of the paper that caught me off guard was this, “It is important to know that human decision makers generally do not make decisions based on the probability of success, because the penalty for a vital decision that turns out to be wrong is normally substantial.” If this were the case, how else would people make decisions? Gut feeling? If gut feelings do not take probabilistic guesses of success into account, than they are no better than random guesses. In that case, creating a DSS is easy. Unfortunately, I do not believe this is the case. The user is a vital source of information and decision-making along the way, and is unlikely to be stripped from the process.

AMac

Although written 15 years ago in 1997, (which seems like an eternity when considering the expansion of the World Wide Web) this paper by Wright et al. raises some excellent considerations when thinking about how we perceive GIS. GIS is a unique field in the fact that it is so closely knit to a “conventional” discipline (Geography), yet seems to now have its own place in academia. Prior to the writing of this paper (and others by Goodchild), GIS was widely considered as a useful tool to display or visualize findings across many spatially relevant disciplines, and nothing really more. While the view of GIS as a science existed among some of those heavily involved in the field, I think that it was less popular view as it is now. Today, more than ever, GIS has become more accepted as a discipline on its own rather than a vehicle for displaying data.
However, I believe Wright et al. drives the point home in the conclusion when they call for a need to shift away from ‘”black and white’ boxes of description” and move towards a more continuous definition of how GIS should be perceived. While I understand that defining GIS as a science eventually leads to more focus (and funding!) on the field, I cannot see the benefits in trying to encompass a set of rules in order to understand GIS as a science. The reason GIS is unique as a field is because of its versatility and it’s increasing power to contribute to societies in the world today. As of 2013, one cannot deny the amount of discourse concerning the scientific theories, models and analyses involved with the creation of various GIS. The paper by Harvey Miller clearly points this out, as we can no longer look at GIS as a purely objective tool but something that must be developed in line with a specific research question. However, being able to take the entire discipline and invoke rules to try and mimic conventional sciences will not work for GIS. Each individual project will have its own set of scientific methods involving a range of academic disciplines.

-Geogman15

The need for a people-based representation of space brought up by Miller is increasingly relevant as we continue in an age where distances are shrinking and populations become more mobile. It is no doubt that space has become less of an obstacle and time has become a larger constraint on our lives. Thus the need for more dynamic methods and models of representing the needs of populations in terms of transportation and urban resources is present. These are of course extremely complex and the sheer amount of information involved leads to a great deal of time and effort spent sifting through incoming data. I believe that this is where the difficulty lies. With techniques such as twitter scraping and SQL, there are ways to get a hold of this kind of data. However, what follows is the hard part. How do we decide what data is important? Does one space or group of people more relevant than another?

I understand that we can limit this by means of things like socioeconomic and neighborhood grouping, however I believe this inevitably leads to the kinds of generalizations that people-based GIS is trying to get away from. By attempting to choose which incoming information is deemed important or not, certain space-time activities will be ignored. This is, of course, combined with the gaps created by the digital divide can potentially lead to the marginalization of certain groups.
Overall, this movement to a people-based GIS will definitely lead to nuanced information and practices. Theoretically, transportation systems will become more efficient and become tailored more to the actual day-to-day activities of individuals in a city. It will just require a lot of work and a style of thinking never done before.

-Geogman15

The need for a people-based representation of space brought up by Miller is increasingly relevant as we continue in an age where distances are shrinking and populations become more mobile. It is no doubt that space has become less of an obstacle and time has become a larger constraint on our lives. Thus the need for more dynamic methods and models of representing the needs of populations in terms of transportation and urban resources is present. These are of course extremely complex and the sheer amount of information involved leads to a great deal of time and effort spent sifting through incoming data. I believe that this is where the difficulty lies. With techniques such as twitter scraping and SQL, there are ways to get a hold of this kind of data. However, what follows is the hard part. How do we decide what data is important? Does one space or group of people more relevant than another?
I understand that we can limit this by means of things like socioeconomic and neighborhood grouping, however I believe this inevitably leads to the kinds of generalizations that people-based GIS is trying to get away from. By attempting to choose which incoming information is deemed important or not, certain space-time activities will be ignored. This is, of course, combined with the gaps created by the digital divide can potentially lead to the marginalization of certain groups.

Overall, this movement to a people-based GIS will definitely lead to nuanced information and practices. Theoretically, transportation systems will become more efficient and become tailored more to the actual day-to-day activities of individuals in a city. It will just require a lot of work and a style of thinking never done before.

GEOGMan15