The Rise of the Digital Silhouette

How much do you think about the traces of you, that you leave behind as you engage more and more with technology?  There has been a not so subtle intrusion into what used to be our private lives where a lot of what we do and say is now recorded.  Notice how Stream of digital data and eyeapps on our smartphones want access to our photos, contacts, and location.  Sure you can deny such access but then the value of the apps diminishes significantly, often to zero.  Do you remember which apps you have given the go ahead to track your movements, your buying habits, your interactions with others, etc.?  We use our digital tools in very trusting ways not really thinking about what the companies behind them might do with all that data about us.  Google makes something like 97% ($32M) of their revenue from advertising – actually from us.  Our use of their tools generates tremendously valuable data about human behavior including purchasing habits.  They really should be paying us for our use of their tools!  Google probably knows more about people, in recent years individuals like you and I, than any other company.  Perhaps more than the government.  Now with their push into wearable technology like Google Glasses and then other companies like FitBit, people are beginning to give over an enormous amount of data about themselves including every interaction with every person, all their location information, video recordings, phone calls, text messages, photos, heart rate, sleep patterns, and who knows what else.  Where does this lead us to?

Switching gears for a moment…  there are some significant benefits to education systems in the ‘Internet of things’ movement.  Imagine that students, wearing various data logging technologies, including Google Glasses, interacting with each other, with ‘text books’, human teachers, each other, and other learning resources, along with a host of educational apps, are continuously digitally documented.  Imagine that there are ‘intelligent’ algorithms (think IBM’s Watson but even more advanced) that look for patterns, provide real-time recommendations and coaching that adjust the student’s personalized learning plan, directly interacting with and advising the students like a personal learning coach.  Imagine that when a report card is due, the student’s ‘digital learning guide’ automatically produces a summative report card complete with a ‘live’ info graphic on the student’s learning and generates it directly in the student’s online learning portfolio and sends an alert to the parents.  The parents can interact with the repoiStock_000022796717Smallrt card in many dimensions with their smartphone or on a traditional web browser.  They can see point data including pictures, video clips, audio reflections by the student, opinions from their digital guide, and commentary and feedback from their human ‘teachers’ (learning facilitators).  Actually, this access to learning activity and progress would be available in real-time as well – the summative report would simply be a culminating event or check-point along the way.  Such is the potential future of life logging and ‘big data’ analytics when fully integrated and immersed into the learning and teaching process.  You may think ‘this is crazy and impossible’. I say, think again.  I believe that this type of future is not far off.  Machine learning is growing in sophistication and usefulness, exponentially.  Researchers are learning that us humans are far more predictable and pattern driven than previously thought.  Machines are very good at pattern recognition and are rapidly getting better at decision making.  Our machines will one day ‘know us’, perhaps better than we do…

So, whether we like it or not, we are being cloaked in digital information.  Rather, for those of us that regularly use mobile and other technology, our lives are beginning to generate digital information in droves.  I don’t think this is all bad – there are some very good outcomes possible.  Some of the health applications are encouraging.  A significant problem in getting an accurate and timely diagnoses from our doctors is a lack of useful information.  With real-time massive volumes of physical and psychological data and health img-wonderhoto-com algorithmintelligent machine algorithms, knowledge of our health will be orders of magnitude better.  With real-time data on individual student learners and machine algorithms, the dream of truly personalized learning and teaching may actually be possible.  In this future, human teachers will not be concerned with collecting assessment data and making judgments on individual learners.  Rather they would help kids connect with their passions, provide human wisdom to their learning, facilitate human interactions in classrooms (I believe in continued use of classrooms with face to face learning interactions regardless of the technology that is developed), and teachers could be that empathic listener and advisor that kids need as they deal with emotions, wonders, problems, worries, and dreams.

Like anything, history teaches us that most technologies have a dark and bright side to them.  If we attempt to resist the technological data capture and analytical tools, others may use them for darker purposes.  As we engage with these tools, understand them, shape them, and voice our opinions on their uses, we can do our part to ensure positive helpful humanized digital silhouettes are the result.  Be aware about what the tools you use, do.  What traces of a digital self are you creating by using them?  How are the companies behind the tools likely to use your digital data for their gain?  Get ready for a very interesting ride into the future…


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