Today it’s all about content; tomorrow it will be about context.
Contextual computing is the most recent development in the progression of technology. Technologies are starting to “understand” things about us and our environment – things like our schedules, our locations, and even our heart rates. The backdrop of this context creates for new anticipatory services and products. The world we’re headed to is a world that knows us. One where commerce, transportation, health care, service and learning are transformed by technologies smart enough to not just meet our needs but anticipate them.
In the book “The Age of Context“, Robert Scoble and Shel Israel state the 5 forces changing what’s possible over the next 10 years. I will be following these 5 forces more closely to try and understand the convergence between the physical and virtual and the relationship between machine and consumer, creating possibilities we have never seen before.
1. Exponential rise in sensors
Sensor devices can be in anything that generates information about the status or environment of things. Many industries have been developing sensors for many decades. Until now, sensors offered a one-way transmission of information. For “things” to be manageable, they needed to be identifiable in terms of type or as a unique entity. Examples of these things still exist today, such as retail products having bar code numbers and books having ISBNs, and so on.
Today, we are experiencing two-way successors of these sensors – enabling information to be sent as well as received from “things” by a software app. We know this as machine-to-machine (M2M) communication. Nonetheless, how things were previously identified is still fundamental to the growth of Internet of Things (IoT). We now see this take shape in the form of NFC, RFID tags or IP addresses.
Many passports now have RFID tags in them, as do hotel room keys, ski passes, RFID-controlled congestion charges in cities such as London and Munich and subway (tube) cards. Animal tracking is also a common use case as seen in micro-chipping on dogs and cattle. Nowadays we are also seeing more applications in sports games such as in football, tennis and baseball where goal-line technologies are helping umpires and referees make decisions.
In the future, these sensors will be able to combine recognition technologies (fingerprint, retina, face) to recognise individuals to items, thus creating more powerful, smaller, smarter I.D badges which allows for secure access for personalised services.
Pervasive or wearable computing is based on the ideas of internet-enabled devices that can communicate remotely. Consumer interest in ‘Quantified Self’ products and services will continue to grow, from functional jewellery, smart watches and glasses, to audio wearables and other powerful yet affordable wearable tech products enter the market. Technology is no longer confined to clunky interfaces and un-portable devices. We are now beginning to see technology become an object of style coming out of our pockets and onto our clothes, skin and surroundings. In 2013, the wearable technology industry will generate global revenues in the amount of USD 2.5 billion and is expected to increase more than five-fold by 2018 (Source: Business Insider, 2013).
Undoubtedly wearable computing is a clear demonstration how technology will continue to infiltrate into our everyday lives – harmonising the mind, body and spirit. Wearables will have the ability to create aggregated data sets from our daily routines such as sleep patterns, fitness regimes via movement and motion, to mood sensing which in turn can help apps to become smarter and ultimately offer better decision-making for the wearer.
Though wearable technology is still at an ‘early adopter’ stage in terms of public and commercial use, privacy concerns are already being voiced. By their very design, many of these wearable devices would be able to capture a great deal of personal data about the wearer and individuals in the vicinity of the wearer. So, it remains to be seen whether future developments of wearable technology will address privacy concerns to convince people of its value and mass appeal.
Global positioning systems had been developed way back in 1960 by Dr. Ivan Getting for satellites used by the military. Only in 1983 President Ronald Reagan issued a directive making GPS freely available for civilian use. Since then, we have seen GPS tracking pop up in all sorts of devices from navigation maps and systems such as the TomTom, to watches, shipping containers and ATMs – making their way into all walks of daily life.
As technology continues to evolve, GPS tracking devices will continue to decrease in size, increase in accuracy, and be utilized by even more businesses as a common, yet powerful tool. Contextual location technology will then become ubiquitous. Driven by the explosion in smartphone adoption globally, people will be offered a more personalized and in-context mobile experience with the help of contextual data – information relevant to a person’s location, surroundings or time of day.
We are already seeing a progression albeit slowly, the industry’s focus on native advertising in a world of increasing localisation and contextualisation. When combined, these “right-time experiences” will start to deliver what we want, when we want it. However, the issue with location-based information is that it exposes another layer of personal information that, frankly, we haven’t had to think much about: our exact physical location at anytime, anywhere. These technologies may help to assist us for the most part, but with a great cost to our security.
For example, a website called PleaseRobMe.com does nothing more than aggregate publicly shared check-ins, but its name and purpose attempt to shed light on the dangerous side effects of location-sharing. No doubt we will foresee numerous personal privacy violations occur with the increasing use of geo-location data, however the powerful opportunities in the future are exciting. Nonetheless, the context of geo-location either through the use of GPS or any new systems and platforms should be used with caution, requiring new laws to protect and preserve individual freedoms.
The capability to exhibit social and affective behaviour is one of the main human needs to involve in a natural interaction, yet, is lacking in artificial companions. However, we see this changing. For example, we have begun telling Facebook how we really feel with its Emoticon features. This potentially creates new ways for social networks to collect data about people for targeted advertising purposes. That means they could be used as recommendations for Pages, eventually winding up in Graph Search, or potentially even be used as ads shown to your friends.
Advances in artificial intelligence, common-sense reasoning about emotion, and user context are important in helping computers predict and understand which emotion is likely to occur in a situation. In the future, we can see affective computing combine various fields such as computer science, artificial intelligence, philosophy and psychology with the aim of linking technology with human emotions.
With the help of face and voice analysis, measuring brain and heart activities, as well as using social media, technological systems will be developed to detect the mood increasingly precisely. These systems can therefore interpret and perform actions based on the emotions they recognise. These emotional machines will be a guiding step to build long‐term human-machine interactions by creating emotional attachment. Technologies that sense and help communicate affect can also be used to enable new kinds of expressive experiences. With affective computing, interaction with computers and robots is becoming more intuitive and human.
Historically, businesses could take advantage of the scarcity of some information, or connectivity, or computing power to attract and keep their customers and repel competition. But today, we are seeing an influx of (big) data driven by newly available resources such as open source software and open data to empower us to make far more informed choices – no longer can a company so thoroughly control its customers’ environment.
Nonetheless, companies can make or save millions or billions of dollars by identifying and understanding new opportunities in large data sets. Through an open ecosystem, it encourages a flood of ideas giving companies a big competitive edge, but only if they are suitably positioned to take advantage of it.
Open technology (open source): More hands working on a product will only improve it. Open allows for testing the initial appeal and actual usage of a potential new product by simulating its core experience with the smallest possible investment of time and money.
Open information: Being transparent about user information collected to provide something valuable to them, and we give them ultimate control over their information.
For example, PatientsLikeMe is a social networking health site built atop the US Department of Health Services’ open data. It allows patients to share information and learn from others with similar conditions. Researchers, too, could benefit from greater openness in the industry. Similarly, Google Flu Trends demonstrates how we know about a particular virus, merely by letting information be shared and collated.
All of this summarises quite well in an article featured in Fast Company “The Future Of Technology Isn’t Mobile, It’s Contextual” the author identifies 4 graphs essential to the rise of contextual computing: social, interest, behaviour and personal.
In the end, context will still be consumer-based and will revolve around “you”. It doesn’t directly replace anything that has existed before, particularly in the consumer space. The only significance is now we can see everything in real-time, and for marketers the ability to generate deep insights into their customers which had not been possible before.