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Machines with the ability to understand you and everything you care about? The future of technology isn’t mobile, it’s contextual!
The Contextual Future of Technology will include the ability to:
Let’s say you’re walking home alone during the night, and suddenly you hear footsteps approaching from behind. You constantly glance backwards and listen for signs of a threat. Your senses awaken and attempt to help your brain figure out what’s going on. You might be prompted to turn down another street, or confront the situation; either way, your brain is quickly going through all the possible scenarios, searching for an answer.
This is known as “situational awareness.” We seamlessly respond to the world around us, absorbing multitudes of information, comparing it to past experiences, and presenting us with a variety of options regarding how to act or react. Then our mind chooses a preferred path, and acts upon it.
This process is our integral ability to act on the situations we find ourselves in, and the process hasn’t evolved much since the times of the caveman. The problem is that our senses aren’t working in harmony with our modern life, a lot of the data we need in order to make good decisions today is unreliable, or nonexistent.
Contextual Computing: Our Sixth, Seventh, and Eighth Senses
In the future, technology will shift towards what is known as contextual computing. The idea was defined by Georgia Tech researchers Anind Dey and Gregory Abowd, nearly a decade ago. Computers will be able to sense both the objective and subjective aspects of any given situation. This will increase our ability to act in the moment, regardless of who we’re with, where we are and what our past experiences were. Computers will act as our sixth, seventh and eight senses.
Subtle hints of this shift have become apparent with mobile devices that include GPS (Global Positioning System)-delivered location-based services, and Amazon or Netflix’s recommendation engines; which aren’t extremely intuitive, yet they’re able to recommend videos or books based on your previous choices and behavior. Even Facebook and Twitter are able to market relevant content to you, based on your interests and acquaintances.
Future platforms will be designed specifically for contextual computing and will make your phone seem more like a toy, and less like a phone with interesting tools. This is just the beginning of contextual computing! With a platform’s deep understanding of the user, it will include combinations of hardware, software, networks and services that can create tailored, relevant actions for the user. Mobile technology is intriguing because it’s equipped with sensors, and is always with the user.
In Order For Contextual Computing To Work, You’ll Need Four Essential Data Graphs
Those who seek to dominate the next era of the web must master all four of these graphs to be successful. Some are well-established, others have randomly emerged in the past few years; yet there are many ethical concerns regarding each of these graphs.
Dealing with all of this from an individual standpoint is difficult, let alone a legal one.
The Interest Graph: Turning Your Passions Into a Marketing Campaign
Regardless of the ethical concerns surrounding contextual computing, companies are actively constructing these graphs today. These services and products are already available in the market, however, most of them only target one of two of these graphs. Few companies in the market are pursuing all four graphs, due to both the lack of targets and space. Unintentionally, this highlights the risk of these services as opposed to demonstrating the benefits. These data sets must be implemented in order for us to realize the full potential of contextual computing.
The Social Graph: All About Connections
Most people associate this graph with Facebook, but the idea and data set has spread far beyond that; displaying how you connect to other people, and how those people are connected to one another. In an ideal state of contextual computing, this graph could be complete—with subtle changes to software and services, allowing two people who are strangers—but would get along wonderfully—to be brought together in the same place, at the same time. For example, two people move far away to a place where neither person knows anyone, yet the social graph can determine that these two people have a mutual friend, bringing them together.
This graph will reach its full potential when it’s open to a wide variety of services. If you don’t know anything about a specific person’s beliefs, interests and activities, all the social data in the world won’t be helpful.
Does Your Personal Graph Contain All Your Beliefs?
This set of data relates to a person’s deepest held beliefs, personality and core values. The social graph is used to display what makes us similar to others, while the personal graph is used to display what makes us unique in the world.
Even psychology can’t entirely explain how our personal identities function, so it comes as no surprise that the idea of documenting such information in a computable form is emerging very slowly. The personal graph is under developed and difficult to design. However, there are indicators that this will change.
For example, Proust.com is a new social-networking website that asks the users to document personal details of their lives and beliefs, based on the idea of the famed “Proust Questionnaire.” Users are reluctant to share such information on a public social network, which is understandable.
Evernote is a more successful example, as they’ve made it simple and secure to document both recently learned information and your thoughts. The intimacy of these files is the questionable part of the personal graph, and the potential of the personal graph will not be reached without the creation of entirely new solutions.
In order for that to happen, technology companies, computer scientists and users will all need to understand the possibilities of contextual computing. It’s similar to the way graphical and networked computing were introduced in technical and conceptual forms, ten years before they were able to reach commercial success.
The Interest Graph: All About Curiosity
Your preferences and tastes revolve around the subjects that tend to correspond with one another. Also consider the similar taste between individuals whose lives closely resemble your own. Many companies are fans of this graph; Twitter believes they’re well on their way to fully documenting how all subjects connect to others.
There are very few applications like this available today. For example, the book site Goodreads.com is capable of predicting what other books you may enjoy, based on your interests. The problem is that the interest graph cannot fully decipher your interests and tastes, and it could never recommend a restaurant or vacation spot effectively based on what you read.
Your Behavior Can Be Easily Graphed
Data can easily illustrate what you’re doing, instead of what you claim to do; with sensors and self-reporting mechanisms. This data can be contrasting to the interest graph, because the computer knows, possibly better than you, how likely you are to go somewhere or do something specific.
Take, for example, a travel site that remembers how you consistently vacation in Europe. A smart travel application would provide you with deals in Paris or Berlin. The behavior graph provides the foundation of Google Search, Amazon and Netflix recommendations iTunes Genius, Nike+ run tracking, FitBit, FourSquare and the entire “quantified-self” movement. When combined with the other three graphs, the potential for real insight increases dramatically.
Contextual Computing Will Eventually Dominate the World of Technology
Contextual computing isn’t about just one of these graphs, the real potential is in the connections between them. Early entrants such as Google’s Now and Glass Projects and Siri are just starting to experiment with these technologies.
Similar to the visionaries at Xerox PARC (who developed the foundational technologies of the modern desktop PC) who couldn’t grasp the long-term impact of the mouse and graphical computing, we can’t predict which contextual applications will be most vital. The path towards the future is paved upon many interesting failures.
Bill Gates once stated “There’s a tendency to overestimate how much things will change in two years, and underestimate how much change will occur over 10 years.” Contextual computing is further down the road than a lot of optimistic pundits would like us to believe, however, this doesn’t mean it’s unlikely to fully arrive.
Within a decade, contextual computing will dominate the world of technology, with office productivity moving towards this a model. Contextual computing will combine relevant sets of data about us and the context in which we live, generating multiple relevant options for us. Essentially, we’ll have wearable intelligence.
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