By Gareth Price, Technical Director, Ready Set Rocket
As a digital marketing agency, Ready Set Rocket likes to keep its finger on the pulse of new technologies that can help our clients better communicate with their customers. Recently, we’ve started experimenting with wearable technologies, a market we find very promising, but prone to a certain kind of feverish hype and techno-utopianism. Products are announced to great fanfare that record a certain metric or data point, but forgetting to answer the question of how recording all that data will benefit or help an end user. Devices that fail to fulfill real needs end up quickly relegated to a dusty shelf after the initial novelty wears off.
In a world where consumers demand and even expect technology that can connect to other devices, wearables just aren’t ready for their close-up. The majority of these products comprise what are basically self-contained empires: Google Glass doesn’t talk to the FitBit, for example. To achieve a future where wearables truly benefit people’s lives, they need to talk to each other. What’s more, the data they are capable of producing needs to be more accessible to end-users and other devices.
To further these efforts, Ready Set Rocket advocates for wearable makers to open up their devices and to focus on how devices will improve people’s happiness and satisfaction.
One of the areas we see as most closely tied to how technology will revolutionize the science of individual happiness is Brain Computer Interface (BCI) technology. BCI technology employs electrodes to read a person’s brainwaves, and to see how certain thoughts trigger certain actions or emotions, a process known as biofeedback. Right now, BCI devices are rather clunky and awkward—think of a helmet full of electrodes—but over time, they will evolve into more unobtrusive headbands that people can slip on very simply.
BCI devices combined with software to monitor emotional states will give us a stronger idea of someone’s true reaction to a product or service. Unlike traditional focus group testing, where responses are highly subjective and filtered through conscious filters, BCI technology elicits one’s subconscious response. Marketers can then compare the responses to multiple variations of content, product elements or services to discover patterns of responses. This way, they can advise brands on creating products offering the best possible consumer experiences.
Although BCI technology is potentially capable of providing unique insight into a range of human emotions, both positive and negative, right now we’re interested in measuring what we call the Happiness Quotient. This is how wearable technology, especially in the form of the headsets and other devices that read BCI data, might contribute to helping brands and creators to develop products and experiences that increase individual happiness and satisfaction.
One way we can do this is by using BCI technology to measure and create responses that are readily definable as specific emotions, from happiness, sadness and anger, to engagement and focus. At the moment, this is difficult. We can read brainwave frequency and amplitude modulation to show us certain responses to specific stimuli, but the algorithms that can pull together these groups of responses to indicate a specific emotion are primitive.
Speech recognition technology offers a good analogy for understanding this problem. While it has existed in some form since the 1950s, it’s only recently become useful in a general purpose way. It has always required extensive, strong training to recognize a particular voice. Current generations of speech recognition, for example Apple’s Siri, or voice-activated call-center technology, has improved on this, with a greater capability to understand different voices than in previous generations. It took years of researchers collecting thousands of voices repeating certain words over and over, however, for this to happen.
To create better products and services, we need similar amounts of data on emotional inference. Just as with speech recognition, we need to put BCI-enabled headsets onto a large number of research participants, gauge their response to a stimulus, and use that to calibrate a model that can be applied to everyone. But in order to create the algorithms that will tell us that this product or element makes this person happy, or this person bored, we need to gather a large amount of this information, ideally in a quick timeframe.
This is where the open source element comes into play. If we can offer access to the data BCI devices generate to everyone, it will make it that much easier and quicker to create algorithms defining specific types of emotions. Makers of BCI-enabled wearables can aid in this by allowing users to easily access to the data they collect on emotional responses. They can also make it possible for consumers themselves to engage in training these algorithms by allowing them to transmit (in a private, protected manner) their own data back to the manufacturer for research purposes.
Some manufacturers of headsets have developed proprietary algorithms that have begun to infer some emotions. Unfortunately, they have kept this information proprietary. Yet they could also benefit from open source BCI technology. These proprietary algorithms are trained with data from only a small number of focus group participants. With access to data from other sources, they could greatly improve the accuracy of those algorithms.
There are efforts underway to manufacture open-source BCI devices. One organization making promising headway in this is OpenBCI, a non-profit that designs affordable open source BCI-enabled technology. It has developed a circuit board that is compatible with any type of electrode, and can be used to sample electrical brain activity (EEG), muscle activity (EMG), heart rate (EKG), and other parameters. It is compatible with any type of electrode and is supported by a growing open-source framework of signal processing applications. In essence, it allows users to build their own BCI-capable headsets.
Through allowing individuals to measure and better understand their emotions, BCI technology is the key to a potential revolution in the science of individual happiness. By opening up devices, data and source code, device manufacturers will tap into a growing ecosystem that will result in a wide range of as-yet unimagined applications for their devices that will fulfill real human needs.
By allowing open access to devices and data, marketers like Ready Set Rocket will be able to harness it to help create products and services with our clients that will improve people’s satisfaction and happiness. It’s that Happiness Quotient—an element no one should overlook in the rush to crown the next big thing.
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About Gareth Price
Gareth is Technology Director at Ready Set Rocket, bringing over 10 years of experience in software and development to the agency. In his role, Gareth has consistently led the development team in the application of innovative digital strategies for brands such as Univision, Michael Kors and Deutsche Bank. Additionally, Gareth defines development strategy, manages and further expands the development team, explores new technology and helps keep the agency at the forefront of the web.
At the 2015 South By Southwest Conference, Gareth will be co-hosting the panel “Wearables and the Happiness Quotient,” where the aim is to answer, through an open and spirited discussion with experts and attendees, if wearables can indeed help us be happier.
Prior to joining Ready Set Rocket, Gareth worked as a consulting web developer from 2008 to 2012 for several companies including, WebStandard, Push, and Purple, Rock, Scissors. He also served as a web developer for Florida Hospital. Gareth’s specialties include; content management systems, Drupal, Laravel, PHP, LAMP, Responsive, Agile development, Scrum and git.