Does this title sound familiar? It's very similar to Michael Wesch's viral video from a few years ago: The Machine is Us/ing Us. When I first saw this video in 2008, it inspired me to write a series of posts about how users of the World Wide Web, were Teaching the Machine. Now, just three years later, it seems as if the machine has become smart enough to customize the information it provides to each of us.
Yesterday, after hearing Wesch describe how his video went viral, participants at Canada 3.0 were called by Sonija Monga, to reflect on how we derive meaning and insights from our networks.
By virtue of my membership in a network that is already functioning as a bit of a like-minded hive, I discovered an answer to my question thanks to a tweet from Alec Couros, Take nine minutes to consider Eli Pariser's warning: Beware online "filter bubbles"
I don't know if the machine can yet answer these questions, but there are many things we need to think about:
Is there a problem with each user being the recipient of customized service from a news provider; an online store; a search engine? Does the machine know enough to provide us not only with relevant results, but also with an unbiased determination of the most important content? How good are our personal learning network at discovering content from varying points of view? How might a young person's unseen profile and early online habits, affect their future online experiences?
In this brief interview, Michael Wesch of Kansas State University, affirms many of my personal beliefs about teaching and learning. In less than 10 minutes, he reminds us of the importance of collaboration; of the critical role played by modern learning tools; of the empowering nature of engaging questions; and perhaps most importantly, that teachers can demonstrate respect and love for their students.
While educators are aware that they have great responsiblity to teach content and skills to learners of all ages, we are mostly unaware that we are providing reflections of ourselves to 'the machine' each time we use the World Wide Web'.
I first happened upon the phrase "Teaching the Machine" in Michael Wesch's Video: Web 2.0... The Machine is Us/ing Us. Just past the half way mark of the video, an article that I'd read many months earlier, is referenced. The Web version of "We are the Web", first published in Wired Magazine in August 2005, remains timely in helping us understanding our role in 'wiring' the neural networks of the World Wide Web:
"...And who will write the software that makes this contraption useful and productive? We will. In fact, we’re already doing it, each of us, every day. When we post and then tag pictures on the community photo album Flickr, we are teaching the Machine to give names to images. The thickening links between caption and picture form a neural net that can learn."
It was earlier this afternoon that I experienced how quickly the machine can learn. In uploading a batch of outdoor auto show photos I'd taken two years ago, I taught the machine by adding appropriate filenames and tags to each of the images. Although time has yet to provide me the liberty to provide more descriptive detail, by zooming in and clicking on a global map, I was also able to plot the location where I'd taken these photographs.
What I didn't realize, is that I also taught the machine by providing metadata that was included in the image files themselves. Flickr now knows the camera I used, and the dates/times the photos were taken. The once amazing ideas shared almost a year ago in the Photosynth Talk at TED, suddenly seem all the more real and personal to me:
Teaching the machine about images, is only part of the role we all play in teaching the machine. In the next few days, I'll be trying a focused thought experiment to consider what we teach it when:
1] we link to ideas; 2] we define words and ideas in Wikipedia; 3] we refine searches in 'Google'; and by following the 'right' link, provide feedback to the machine; 4] we play, then win or lose at games like chess or Texas Hold 'em; 5] we make online purchases; 6] we send and receive text messages, tweets, and email to members of our networks...
When the morning arrives, I'll begin expanding on these ideas via the Teacher 2.0 Podcast.
As a teacher; learner; consultant; speaker; and collaborator, I'm on the lookout for opportunities to engage in meaningful conversations with others who see themselves as learners. Professional development; project based learning; and Creative Commons are topics that are always on my radar.
