Hello fellow Ed Tech-ers.
Please enjoy this brief travel through the failures and the (potential) future of smart glasses.
Is That a Camera on Your Face?
4 responses to “Is That a Camera on Your Face?”
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Hi Mitchell. I haven’t thought of how this piece of technology could be used in the educational setting until you presented this. Would the moment to moment feedback be used for educators to help students learn about personal growth? Would students then develop this dependency as they carry on through their professional careers? I’m think about this as one who works in a corporate setting and have managed an operation before. How can this device be beneficial to these settings? I believe this would be strictly be prohibited in a healthcare setting because of patient confidentiality, but might be in areas where patients are present. What is the added benefit of using this device when people work in front of a computer most of the time – information is already at the tip of their fingers. How would the moment to moment feedback help with a corporate employee?
Great questions Sarah. Two answers here depending on if you are working with information flowing into the headset about the user or about the environment.
If we are talking the environment being used on a headset they are actually being used in heathcare already as surgeons can use them for technical overlays during a procedure. https://www.ucsf.edu/news/2013/10/109526/google-glass-delivers-new-insight-during-surgery
Additionally, this could be used as a piece of perfect feedback; one of the resources on Google Glass Enterprise Edition 2 talked about how it could be used to either record or transcribe a medical visit verbal exchange. This isn’t going to make them a better physician, but it may save them some time. I go back to the diffusion of innovation curve, at some point that tech becomes good enough and the potential risks to data become small enough that it gets adopted.
If we are talking information coming from the user (biometrics) we can already see things like the cyclist version giving live feedback. Those cyclists are not elite because of the wearable, but are likely slightly better because of it. I relate this to your question about dependency; a wearable will not make a student a good learner, but it might make a good student a better learner. I liken it to some of the commercial applications like Noom that are using “nudges” and Richard Thaler’s work around that concept https://freakonomics.com/podcast/frbc-richard-thaler/ If a headset can nudge you back into learning after it finds that you are having a stress response, then a classroom teacher doesn’t have to do a much larger action to push you back to a good state of learning.
To answer your last question about where this adds value…mobility. What happens if that same employee can escape the computer screen and do some of the same work while walking around the office? This is already happening with some innovators using treadmill desks, but may be a much less intrusive if combined with a haptic control device. https://www.youtube.com/watch?v=zioE1YRixwE
Hi Mitchell,
I truly enjoyed this presentation, well done.
You discussed some of the key issues with AR glasses, particularly the google glasses and why they ended up being functionally dead. However, in addition to the medical issues (e.g., headaches), and privacy concerns that you spoke about, they were some other worries that users were having. The biggest matter was vulnerability of the device, particularly being targeted by hackers. It was never clear how all that user information would remain safe. Moreover, the device itself looked clunky and unappealing. Having said this, I agree with your conclusion, the device is capable of collecting information about the user such as what they are focusing on, their mental state, and anything else that can be considered moment-to-moment feedback. However, my question is that where do you see the potential use of such data for educators? In other words, how would this data be essential in education? Look forward to reading your response. Thank you.
I agree that there were other problems. That being said, those issues that you’ve mentioned are universal IoT issues; just exasperated by the visual nature of the data collected.
When I was doing my undergrad in Kinesiology at UCalgary one of my Professors Joan Vickers was doing research on what she called the Quiet eye. This concept was born from researching a question about how athletes do what they do to perform. She hooked up a headset similar to the eye reader at the end of my video to basketball players and discovered they they actually weren’t focusing directly on the target. Their eyes were using a significant degree of their peripheral vision to make the shot. They didn’t know this, they just did it. Where I see this tech going is in a simple question: what things do we do physiologically when we are in a positive state to learn that we don’t know about?
An AR headset could be trained to coach you, the student, into an ideal learning state (much like the Muse headbands are marketed to do) with visual or auditory prompts based on your biometrics such as heart rate, galvanic skin response, and the focal area of your eye. I foresee this being a feedback mechanism in exactly the same way as the Garmin heartrate monitors where we would tell students that we wanted them to run for 20 minutes with their heartrate between 120 and 150 beats per minute. That kind of feedback totally changes the context of an experience as it is no longer based on a standard but is completely personalized to the student.
And the cynic would say that that data could potentially be abused. This isn’t sci-fi, this is now. https://interestingengineering.com/companies-in-china-are-monitoring-employees-emotions-with-ai
I just want to note that in that article the jury is still out, so to speak, as to how effective this technology is right now technically, but it is probably good that we are talking about the implications anyway.