Currently, 9 out of 10 people are experiencing the mental effects of phantom vibrations. Phantom vibrations are when you imagine your cell phone vibrate in your pocket. The large number of notifications we consistently receive to our devices irritates this feeling. The reality is, phantom vibrations are just a result of being connected all the time.
Deloitte has been studying the number of times people check their phones over the course of a day. In 2015, that number was 46 times per day. This number is up from the 33 times per day in 2014 and will to continue to rise. As the number connected devices increase so does our desire to check those devices.
What is the IoT?
According to Wikipedia, “the internet of things (IoT) is the internet working of physical devices, vehicles, buildings and other items—embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.” We are entering into a phase where more and more of our everyday devices will connect to the network. These devices will be able to push, receive, and share our data.
In 2016, the average person connects with three devices. Most of us carry a smartphone, a tablet, and a computer. Current predictions estimate that by 2025, this number could rise to 10-15 devices. Over the next 25 years, the number of connected devices we interact with is going to grow exponentially. This figure could reach as high as into the thousands.
On the surface, this sounds like an exciting world. A world in which all your devices can collect and receive data. Your fridge notifies you when you are running low on milk. Your oven sends you a push notification when your food is ready.
A little too much?
With only three devices, people are already imagining receiving notifications. How would your world change if you connect with 10-15 devices? What about if you had 100-200 connected devices all competing for your attention at the same time?
Phantom vibrations are the result of the friction produced by connecting to the network. As we are in the early stages of this transition, more and more devices will be introduced. This friction is going to get much worse.
That friction is going to cause some people to start to repel new technologies. Others are going to continue to adopt the new technologies. Not only does this divide slow down the global rate of adoption it creates some pretty big problems.
The data bias
As society splits into these two buckets, something happens to all that data. We introduce a massive collection bias. Power users are going to be producing much more data faster than the later adopters. This bias creates huge holes in the way we are looking at our information. Automated systems start to shift focus towards the early adopters. With more of our data collection being automated, this creates massive skews in our data sets. These skews lead to wasting time, resources, and money that many companies can’t afford. It could even get as far as hindering our ability to innovate meaningful solutions.
When we take into account our dependence on machine learning, this data issue escalates. To get the full benefits of machine learning, you need access to a significant amount of clean data. The more information we add into the algorithm, the better our predictions get. If we are adding biased data from the start, we will naturally create waste. With the compounding effect, the more data we add, the further we would move away from where we need to be.
Currently, scientists are exploring a new field of artificial intelligence called “Context Awareness AI.”
In comparison, artificial intelligence is slower to roll out than other technologies. Given enough time, this AI will help to surpass that friction. Once that stress is reduced, the rate of adoption for the IoT will begin to move towards equilibrium. That balance is known as ubiquitous computing. This is a period when we can add more and more devices without any additional friction, only value.
In other words, your devices will be smart enough to understand context. An example of this would be your cell phone would be smart enough to know when you are using your tablet. You would only get notified on the device you are currently using. This would significantly reduce the number of notifications you are receiving. Another example would be if you were in an important meeting. Your devices would recognize where you are and postpone your Facebook notifications.
We have already seen this friction curve happen during the introduction of electricity. When electricity was introduced into society, it was intrusive. Now, most people don’t even think about it when they turn on a light of walk over to the TV to turn on their favorite show. The internet of things is destined to follow a similar trajectory.
Over the next couple of years, this transition is going to get harder before it gets any better. Things are not going to work the way we intended them. This creates gaps in the way we collect and analyze user data. We need to be conscious of the early risks associated with the transition. Understanding the risks it poses for our data collection and ongoing optimizations.
During ubiquitous computing, the way we interact with our devices will be different. For the first time, people will have all the benefits of being connected while simultaneously feeling completely unplugged.
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