When most people hear the word "ambient" they think of music and, perhaps even more specifically, of Brian Eno and his landmark album, Music for Airports. Eno conceived of the album after a frustrating wait in Cologne airport and decided to design the music to diffuse the tense environment and provide a more contextual stimulus for inspiration.
However, when we see the term 'ambient' applied to concepts like customer experience, it can be confusing to know what this means in a material sense.
The wider definition of ambient music helps draw the connection. Ambient music, unlike background music, supports a spectrum of focus, from being completely ignorable to helping draw attention to the environment around us. It does so by enhancing acoustic and atmospheric idiosyncrasies and, ultimately, is intended to engender calm and to provide a space to think.
Ambient intelligence moves the concept into the business realm. User experiences driven by ambient intelligence put a new perspective on what consumers do in the real world, by providing them with low intrusion, minimum-friction opt-in features that make their lives easier and more interesting. Stanford University defines the concept as "the field to study and create embodiments for smart environments that not only react to human events through sensing, interpretation and service provision, but also learn and adapt their operation and services to the users over time."
What is now referred to as ambient intelligence had its origins in a field called ubiquitous computing—a term coined by its "father," Mark Weiser. He proposed a model where humans will not interact with just one computing device but rather with many, in the form of a set of dynamic, small, networked computers—often invisible and embedded in everyday objects. Today, we recognize the shoots of this idea bearing fruit in our serial use of multiple devices like smartphones, tablets, laptops, and consoles, where consumers begin a transaction on one device, progress it on another, and complete it on another still. We also use these devices in parallel, and the past couple of years have seen experimentation in the form of second-screen experiences for TV shows, gaming, and customer support experiences.
Today, adaptive and responsive design take into account not just screen real estate available but also the characteristics of the device—mobiles are more action centric, while desktops are better suited to more expansive functions, such as research. The technology is still literally visible, but its availability and the depth to which it is integrated into our lives effectively make the process invisible or, at least, very low friction. We don't think about the mechanics of the experience any more than a drummer overthinks each hit of the stick on a drum.
Our smart gadgets, however, are just the beginning. For ambient intelligence to really flourish, we require many more objects to be digitally enabled and for these objects to listen to and respond to the environment and each other. The midterm will see the Internet of Things (IoT) enable inexpensive networking and connectivity, to be applied to everything from stockroom crates to tables and children's toys. The protocols supporting this pervasive communication are being enabled by mobile signals, Wi-Fi, NFC tags, and Bluetooth Low Energy. Ambient intelligence is not just one technology; it is a coalition of many working in unison.
One of the most abiding models for understanding a complex system such as this is an agent model. These models are popular in artificial intelligence and are able to support decentralized, self-learning systems that have goals such as those outlined above. This model sets up a circular cycle: sense, think, and act. Customer experience professionals should view ambient intelligence from this framework and consider the following:
1. Sense: Ask permission for unobtrusive listening and interaction with the consumer's environment. Today, smartphones kitted with a slew of onboard sensors provide the most accurate "remote viewing" of people, objects, and places. Context is the key for relevance and requires lots of data signals, so the goal for experience designers is to obtain permission from customers to sense their location, orientation, identity, nearby temperature, and other environmental, social, and emotional cues. Interaction design supported by onboard cameras and microphones will provide insights into consumers' moods, as well as what they are saying and doing.
The new Moto-X Android phone by Motorola/Google points the way here, with its always-on audio capture that continuously senses the environment and is ready to serve at any second. According to its website, the Moto-X "responds to your voice—no touching necessary. Twist your wrist twice, it becomes your camera. Information quietly appears on the screen—it doesn't interrupt."
2. Think: Spend the majority of time thinking on how you can provide utility now and in the near future. Experiences will not be ambient if users are presented with a bazaar of bleeps and messages that sound like a Tokyo high street. Therefore, ambient intelligence mandates restraint and relevance. The majority of your development will be spent on models that hypothesize how your brand can help consumers—not sell products to them. Today, web analytics are maturing to multi-signal, sense-making tools fueled by Big Data. Additionally, business logic is expanding to work alongside algorithms and expert systems developed for artificial intelligence to realize the goal of understanding context and relevance.
3. Act: Push messages to the user only when they are hyper-relevant and allow users to train your systems easily. Experiences driven by ambient intelligence need to react quickly to events or signals from the user. The systems also need to proactively support via pushes and alerts. Consider Google Glass, with its subtle conveyor belt of alerts about locations, meetings, and other augmentations of the real world that consumers can either ignore or act upon. Users must be able to calibrate these push messages to train the system to respond appropriately.
An ambient intelligence approach to experience design will increasingly be necessary over the next few years. Without this approach, the signal-to-noise ratio will be poor and the experience will be bad.
Estimates for this new dawn have been penciled in for around 2020, but the technologies needed to deliver it are all present today—albeit unevenly distributed. Public spaces are the most complex, so in the short and medium term, it's likely we will see ambient customer experiences in dedicated retail environments and in the home, where more control of the digital and physical ecosystem is possible.
What benefits will ambient intelligence bring to the customer experience? Future users won't have sore thumbs from jabbing at screens as we do; their technology will be hidden away, continually listening to them and anticipating what they need. They will train it like a pet through their voices, faces, and gestures—and they'll see our continual button-clicking as efficient as starting a fire with a flint.