Posted: February 11th, 2007 | 13 Comments »
On Friday, I gave a talk on Embracing the Real World’s Messiness (slides, video) at the Lift Conference open stage session. Some people in the audience took notes and pictures, including Tom Hume (Future Platforms), Hubert Guillaud (Fing, en français) and Mark Meagher (EPFL).
Relation to my thesis: While I did not present the core of my research, the topic can serve as introduction to my thesis.
I felt a research or engineering talk would not have completely fit to the audience. Therefore, I rather preferred taking the role of the observer of the current integration of sensor technologies in our everyday life in order to question the seamlessness and calmness visions in ubiquitous computing. Even though I feel I only communicated 1/3 of my thoughts, the feedback I received suggest that I delivered my message. In his wrap-up talk (video), Daniel Kaplan shared my observations in highlighting that “we’re using technology to create disorder – you can call it innovation, I call it disorder”. I have been enjoying reading Daniel since he coined the term “Désordinateurs” in reaction from the “Utopie du lisse“.
This talk was based on a few previous blog post, including:
Posted: February 6th, 2007 | No Comments »
Rogers, Y. Moving on from weiser’s vision of calm computing: Engaging ubicomp experiences. In Ubicomp (2006), pp. 404–421.
This paper urges for an alternative agenda in ubicomp research that shifts from Weiser’s calm vision to engaging people (i.e. proactive computing, persuasive computing, engaged living). Yvonne Rogers acknowledges that research in context awareness, ambient intelligence and monitoring/tracking have been somehow fruitful. However they have yet failed to reach Weiser’s world. Indeed, there is an enormous gap between the dream of conformable, informed and effortless living and the accomplishment of UbiComp research. In fact, the fundamental stumbling block has been harnessing the huge variability in what people do, their motives for doing it, when they do it and how they do it. While it has been possible to develop a range of simple ubicomp systems that can offer relevant information at opportune moment, it is proving to be much more difficult to build truly smart systems that can understand or accurately model people’s behaviors, moods and intentions. This makes it difficult, if not impossible, to try to implement context in any practical sense and from which to make sensible predictions about what someone is feeling, wanting or needing at a given moment. Therefore, ubicomp technologies should be designed not to do things for people but to engage them more actively in what they currently do. Rather than calm living it promotes engaged living, where technology is designed to enable people to do what they want, need or never even considered before by acting in and upon the environment. Examples include extending and supporting personal, cognitive and social processes such as habit-changing, problem solving, creating, analyzing, learning or performing a skill.
The author mentions the problems of calm computing in the most prominent ubicomp research themes (i.e. context-aware computing, ambient/ubiquitous intelligence and recording/tracking and monitoring).
Context-awareness
Key questions in context-aware computing concern what to sense, what form and what kind of information to represent to augment ongoing activities. Many of the sensor technologies, however, have been beset with detection and precision limitations, sometimes resulting in unreliable and inaccurate data. While newer technological developments may enable more accurate data to be detected and collected it. However, people often behave in unpredictable and subtle ways in their day-to-day contexts. Therefore, it is likely that context-aware systems will only ever be successful in highly constrained settings.
Ambient and Ubiquitous Intelligence
While there have been significant advances in computer vision, speech recognition and gesture-based detection, the reality of multimodal interfaces – that can predict and deliver with accuracy and sensitivity what is assumed people want or need – is a long way off. In consequence, when a ubiquitous computing system gets it wrong – which is likely to be considerably more frequent – it is likely to be more frustrating and we are likely to be less forgiving.
Recording, Tracking and Monitoring
Much of the discussion about the human aspects in ubicomp has been primarily about the trade-offs between security and privacy, convenience and privacy, and informedness and privacy. This focus has often been at the expense of other human concerns receiving less airing, such as how recording, tracking and re-representing movements and other information can be used to facilitate social and cognitive processes.
Yvonne mentions 2 goals of my research, one being to use ubicomp technologies in the wild, the other to evaluate how to present data and information:
In addition, more studies are needed of UbiComp technologies being used in situ or the wild – to help illuminate how people can construct, appropriate and use them. With respect to interaction design issues, we need to consider how to represent and present data and information that will enable people to more extensively compute, analyze, integrate, inquire and make decisions; how to design appropriate kinds of interfaces and interaction styles for combinations of devices, displays and tools; and how to provide transparent systems that people can understand sufficiently to know how to control and interact with them.
Currently, the more engaging approach is beginning to happen through the areas of playful and learning practices, scientific practices and persuasive practices.
As already mentioned in Comparing AI’s Failures with Ubicomp’s Visions, Yvonne Rogers concludes on “strong” and “weak” UbiComp.
Just as ‘strong’ AI failed to achieve its goals – where it was assumed that “the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind”, it appears that ‘strong’ UbiComp is suffering from the same fate. And just as ‘weak’ AI2 revived AI’s fortunes, so, too, can ‘weak’ UbiComp bring success to the field.
Relation to my thesis: I would argue that current “strong” UbiComp problems not only lays on modelling people and their activities, but also in the integration ubicomp systems in the real-world (e.g. co-existence of systems, real-world constraints). I enjoy the difference between what is “relevant” and what is “smart”, as I find the word smart or intelligent are widely (over)misused. Finally, the agenda proposed in this article, goes in the direction of my research: in sitiu (out of the lab) studies, investigate the playful approach of ubicomp and how to present relevant information rather than seeking the seamlessness utopia.
Posted: February 5th, 2007 | No Comments »
The CommonCensus Map Project redraws the map of the United States based on a survey questions, to reveal the boundaries people themselves feel (i.e. sphere of influence), as opposed to the official state and county boundaries.
The national maps shows the response to the question “On the level of North America as a whole, what major city do you feel has the most cultural and economic influence on your area overall?”
Regional maps show the response to the question “Please choose the name of the local community that you feel is the natural cultural and economic center within your local area.”
Local maps show the response to the question “What do you consider to be your local community?”
Relation to my thesis: People do not always follow the official boundaries to refer to areas. A local neighborood might reveal very fuzzy and fluctuating edges depending on a context. This is what Ian White highlights in User-centered approach on geodata by saying “In practice, a neighbor is defined with average centroid based on population density and then a radial curve is drawn. This barely represents reality in many cases and in the context of use many time useless”.
Due to the low amount of data, the areas of the map are still highly inaccurate and subject to change. It is an example of bottom-up generated information uncertainty.
Posted: February 5th, 2007 | 1 Comment »
The G-Econ project maps the world’s economic activity on a one-degree grid (i.e. 1-degree longitude by 1-degree latitude resolution). It includes 27,500 terrestrial observations of “gross cell product” in 1990. The basic metric is the regional equivalent of gross domestic product. Gross cell product (GCP) is measured at a 1-degree longitude by 1-degree latitude resolution at a global scale. Animations for the entire globe are available, as are maps of individual countries and data sets. Via The Map Room.
Reminds me of Richard Florida’s The World is Spiky
Update: The G-Econ dataset can also be analyzed with the InfoScope. The 27’079 geographical cells about economic data can be compared with other important demographic and geophysical data such as climate, physical attributes, and population indicators.
Posted: February 2nd, 2007 | No Comments »
A discussion with Nicolas and Laurent on inflatable simulated targets in the form of tanks/aircrafts, reminded me of the inflatable dolls used in California to drive in carpool lanes. Answer.com reports on this life-hack:
When HOV lanes were first introduced in California in the 1970s, some drivers would place an inflatable doll in the passenger seat in an attempt to fool regulators. This was soon outlawed, but the practice persists. In the UK, for example, in 2005 a camera that was claimed to distinguish mannequins or dolls from humans was being tested on the Forth Road Bridge in an effort to thwart cheaters.
The ruses to drive alone in carpool lanes include:
- Applying make-up to a wig stand and affixing it to clothing stuffed with newspapers (then strapping the finished product into the passenger seat with a seatbelt)
- Store mannequins, blow-up dolls, kickboxing dummies, cardboard cut-outs, and even balloons (with faces drawn on them in marking pen).
- Buckling the passenger-side seat belt and pretending to talk to someone reclining in that seat.
- Covering an empty infant seat with a blanket or placing a doll in it.
- Taping a styrofoam wig stand to the passenger headrest and topping it with a blonde wig.
- Strapping the family pooch into the passenger seat.
Source
Relation to my thesis: getting into the LIFT mood. The Cyclops employed to detect “fake passengers” is also an interesting example of having to build a system to compensate the people’s abuse of automation. The new system was seen as vital in monitoring traffic when new electronic tollbooths come online, which would further encourage cheating as they allow for variable rates depending on how many passengers are in the car.
