"Michael, are you sure you want to do that?"

Pull over Kitt - you've just been lapped.

On Monday November 14th I attended a presentation by Sebastian Thrun, an AI researcher at Stanford U. whose team recently won the Darpa Grand Challenge.

The idea behind the Grand Challenge is to accomplish something that seems impossible, along the lines of crossing the Atlantic, the X-prize, etc. Darpa had previously funded cars that drive themselves, but after numerous failures decided to turn the task into a contest and see how far teams would get in a competitive setting. Last year none of the entrants managed to finish the course, but this year 5 finished, 4 within the alloted time.

The difference between last year and this year was primarily improvements in software, not hardware. In fact, once the software has been developed, outfitting a car with the necessary equipment to drive itself (the perceptual apparatus - laser, radar, and video guidance, the gps, the inertial motion systems, the general purpose computing servers, and the fly-by-wire control systems), were estimated by Sebastian to cost < $5k once they are mass produced.

Sebastian spent a long time conveying how hard it is to teach a computer to answer the question "What is a road?" The entire time the audience was left wondering - how the @(*^*#@ do we do that?

One of the issues that tripped up the lasers is the systematic pitching forward and backwards of the car as it bumps over the terrain - this causes the perceptual systems to jerk back and forth, perceiving parts of the ground over again, and mistaking these discrepancies for obstacles. No inertial guidance system is precise enough to correct for these errors, and their team won by discovering a systematic regularity in the errors themselves (and a probabilistic model to capture them). Instead of finding theoretically precise values for the constants in their equations, the Stanford team tuned these parameters by actually driving the vehicle, and "tagging" safe terrain. During the training, they also took calculated risks, let bad things happen, and looked back at the earlier optical flow.

Sebastian is aware of the military applications driving (sic) the development of this technology, but is personally motivated by the lives he thinks can be saved in civilian applications. In fact, boasted that he was now planning on having a vehicle drive itself from San Francisco to Los Angeles by 2007! I am beginning to wonder how much longer it will be legal for humans to operate motor vehicles.

When asked if any of the team's research findings would be applicable elsewhere in CS, Sebastian replied that he had no idea, yet. His philosophy is to first build the system, and then afterwards spend years pouring over the data to figure out what happened. In case you hadn't realized it yet, the robots are already here (some of them killer)!

New York's Darker History

This weekend I attended the masterfully produced Slavery in New York exhibit at the New York Historical Society. The exhibit was deeply moving, and vividly and viscerally captured a portrait of African American history I was not fully aware of previously. I left the exhibit with a new understanding of how the 400 year long institution of slavery was a tragedy fully on par with the Nazi Holacaust.

I will save a discussion of the show's content for another time, but for now I want to focus on the amazing use of educational technology woven throughout the exhibit. From start to finish, the show effectively incorporated video, interactive kiosks, and innovative displays which pushed the boundaries of some of the best work I have seen in this field.

The use of screens is a topic that is on my mind from my studies of Lev Manovich this semester, and this exhibit incorporated many cutting edge treatments of the screen.

To start with, at the beginning of the exhibit, the visitor is confronted with video commentary of the reactions of past visitors, and at the end of the exhibit a self-service video booth allowed visitors to record their own commentary. I have never seen a self-service video booth like this incorporated into an museum exhibition, and it was very powerful and impressive.

Beyond that, their ability to transport the visitor to the reality of the past was greatly enhanced by their translation of historical abstractions to modern day interfaces. In particular, I am thinking of the classified ads advertising slaves for sale and offering rewards for runaways, the presentation of the slave ship logs, and most strikingly, the presentation of the slave economy in a bloomberg-style terminal. The cold economics of slavery were driven home by the scrolling marquee listing the numbers of Negros arriving on incoming ships, and the fluctuating going rates of various skills.

The incorporation of video throughout the exhibit, from overhearing the conversation of slaves gathered around a well (in a brilliant interface), to the dialogue between the portraits of ornately framed talking heads, to the interactive choose-your-own-adventure kiosks was incredibly well done, and offered accessibility and deep learning even to the fragmented attentions of the postmodern era.

I highly recommend visiting this exhibition, as the web site barely begins to do it justice.

Wikibases and the Collaboration Index

On October 27th I attended a University Seminar presented by Mark Phillipson. The seminar was lively and well attended, and Mark managed to connect the culture of wikis with their open source roots.

Sometime soon I plan on elaborating on ways in which software, as a form of creative expression, inevitably expresses the values of the creators in the form of features. But right now I want to focus on the taxonomy of educational wiki implementations that Mark has identified since he began working with them.

Here is how Mark divides up the space of educational wikis

• Repository/reference - eg Wikipedia
• A website whose primary function is to create a repository of knowledge on a particular topic.
• Gateway - eg SaratogaCensus
• A website whose primary function is to collect, assemble, and present references to external sources
  
• Simulation/role playing - eg Holocaust Wiki
• A "choose-your-own-adventure" style simulation/game environment
  
• 'Illuminated'/mark-up - eg The Romantic Audience Projects
• An environment that provides tools for detailed exegesis on primary sources, where the students are instructed to leave the source material unchanged, and create subpages with detailed commentary on supplemental pages.
  

I think this taxonomy is accurate, but doesn't completely capture one of the most interesting educational implications of wikis - the process of creating them.

In particular, I can think of a number of variations on the repository/reference wiki, where the final products might all look similar, but where the "collaboration index" might differ substantially (for more on the popularity of the repository/reference, see Database as a Symbolic form, Manovich 2001).

Wikis are a very flexible tool, whose usage can vary from a personal publishing tool, to a simple Content Management System, to a collaborative authoring environment. Additionally, while wiki software doesn't usually support the enforcement of a strict workflow, policy can be stipulated and adhered to by convention (like in Mark's class, where the original poems were meant to be left intact).

Consider a few different applications of reference wikis in the classroom:

• One way Publishing
• A simple means for instructors to publish and organize information for their class.
• Examples include:
• Instructional handbooks, assignment "databases", completed examples
  
• Collaborative Mini-sites and/or subsections
  
• Exercises where individuals or groups work on subsections of a wiki which are combined and referenced within a single larger site
• Examples include:
  
• Students dividing large assignments amongst themselves, each sharing their own results with the group.
  
• A site like the social justice wiki where groups of 3-4 students each worked on a reference element of the site.
  
• Collaborative Websites
• Sections of the site where everyone in the community is supposed to be contributing content
• Examples include:
• Common Resources, Glossary of Terms, and the larger information architecture and organization of the entire site.

• Portals and Meta-tasks
• Also, consider that due to their flexibility, many wikis end up being repurposed beyond their original conception, and begin to serve as portals, where many meta-issues and conversations can take place beyond the assembly of the content itself. Some of these tasks include mundane administrative work, like students forming groups, coordinating assignments, taking minutes, and scheduling time.
  

While the end results of many of these collaborations might certainly all look similar to each other , perhaps the differences in the process by which this content is developed is crucial in capturing part of what is happening with wikis in the classroom.

This analysis probably also has implications relating to the archiving and the use of a wiki environment in a classroom over time. If the act of creating the wiki is central to what the students are supposed to learn from the exercise, then should they start with a fresh wiki every semester? How is the experience different when they are contributing to an existing system (or even have access to prior versions of the project)?

For more on this, see Mark's comment's on CCNMTL's musings blog.