Technology is becoming a presence without a central focus. We are being encouraged to interact with technology by voice rather than screen or device, irrelevant of time or place, with effort being replaced by instinct.
Interactive, voice-activated AI personal assistants like Amazon Alexa are the most prominent manifestations of this shift. Unlike chatbots, which live on-screen and have a dedicated task, Alexa (currently embodied by the Echo or Echo Dot) lives in the home and can help out in a variety of roles. An open API allows developers to build new ‘skills’ for her, so her capabilities are continuously expanding.
The heated competition by all major IT companies to improve their AI assistants and get them into homes is about much more than the device. The software, and the voice that disembodies it, will become the default operating system which the majority of people will demand their devices, appliances and programs seamlessly integrate with. If Alexa wins this race (which she is currently leading) she’ll be freed from the home and welcome, if not expected, in all other areas of life.
Imbuing machines with human emotions
According to Amazon, close to 90 percent of people in the US who have purchased an Amazon Echo since 2014 say they are satisfied with the device. Early adopters have reported that they quickly start thinking of the device as a member of the family – “Even when I’ve tried to call her ‘it’, it feels wrong. She has a name. She’s Alexa.”
Research has shown that we find it easy to ‘humanise’ robots. Back in the early 1960s, MIT computer scientist Joesph Wiezenbaum invented Eliza – a computer therapist (or in today’s terms, chatbot therapist) whose intelligence was made up of pre-programmed questions and responses. ELIZA was tested on non-technical staff, and Wiezenbaum was astounded to discover that some ended up spending hours sharing personal problems with her and believing she could genuinely help them.
AI can help us change behaviour
Today we have a vast arsenal of digital tools and personal data collectors that AI assistants can quickly cross-process to provide even more self-help benefits.
Consumer products such as Vi, an AI bio-sensing voice-activated personal fitness trainer, show that these voice-activated assistants are being configured into informed, powerful coaches and mentors that help people achieve goals. Put Vi earphones in and she will monitor your physiology, answer questions like “Vi, what’s my heart rate,” check in with questions like “Looks like you’re fatigued, are your legs done?”, and motivate you to keep going or indeed advise taking it easy.
Alexa can be programmed in a similar vein – one user programmed Alexa to help him quit smoking by telling him how many days and the amount of money saved since his last cigarette.
Capital One is working on an Alexa skill to promote saving behaviour. When asked what they did the night before, Alexa will reply with, “I don’t know what happened to you but I know what happened to your money,” and then encourage the ostensible party-goer to make better choices. With predictive intelligence, AI could become even more powerful for behaviour change and of course a narrator of actual behaviour, thus eliminating the faulty memory of real people.
AI assistants capture authentic customer data
As researchers, our ideal sources and methodologies capture people purely, naturally, in the moment, and without bias. More often, we piggyback on existing behaviour – they text, we text; they snap, we snap and so on.
Through AI assistants that act as constant, everyday companions, marketers may be able to access moments, content and data that was previously unavailable. This could facilitate real-time, uninfluenced qualitative and quantifiable data, all efficiently analysed and even cross-analysed to bring authentic customer conversations right into the heart of the business. But how would this work for marketers in practical terms?
Could there be an Alexa skill that willing participants install that allows their behaviour to be recorded? Could the skill ask questions about particular topics at appropriate moments, whereby Alexa essentially becomes a proxy for the researcher? There are already Alexa skills that can detect the mood in a person’s voice, and such psychographic and biometric skills are bound to advance further. It is a rich area in which to experiment and explore.
Being artificial can be beneficial
While much effort is going into making robots and artificial intelligence more human, the fact that robots have always been presented as without judgement can work in their favour. In certain situations, people open up more to robots than humans, particularly when the context may be taboo or illegal.
Consider the US election where Trump supporters were often reluctant to divulge their presidential preference. Had polls been conducted via non-judgemental AI assistants, would people have been more honest? Depending on the context, making AI more or less human can be beneficial to the quality and authenticity of insights we gain.
This is not to say those currently working in the marketing and insights space should worry that they are out of a job. Daniel Fazekas suggests that machines lack the creativity to imitate the human analytical ability to understand context, and as we know, context is highly influential and essential when interpreting behaviour.
Though this may change as technology progresses, we believe that humans working hand in hand with machines is the winning route. There are still many dots amongst the data that only humans can connect, but with AI the dots may come from more varied and diverse moments, have more connections, and allow us to reach deeper, wider and further than before.
These are exciting times for our industry. With their ability to provide uninfluenced, in the moment, highly personalised data, these technologies will enable organisations to become customer-centric in a way that is not currently conceivable given the traditional physical touchpoints of call centres and stores. Our challenge is to not just look at new technologies as tools to do what we are currently doing more efficiently, but to look wider at what added benefits there are that will give us different and more useful insights into our customers and their behaviour, and enable us to optimise the customer experience.