The race to integrate artificial intelligence with human emotion is on and as you’d have noticed, we humans have always had a connection with machines, from the first time we saw electricity light up our world.
But now that artificial intelligence is quickly catching on to human emotion and also learning how to interpret it, the next step is going to be how to use that knowledge to improve everything from marketing campaigns to health care.
This technology is called “Emotion AI” and means Helen Keller’s famous quote “The best and most beautiful things in the world cannot be seen or even touched. They must be felt with the heart” could be on borrowed time!
Emotion AI is artificial intelligence that detects and interprets human emotional signals. It can be sourced from the text (sentiment analysis and natural language processing), video (facial expressions analysis, gaits and physiological signals), audio (voice emotion AI) and also a combination of these.
For example, to understand how you’re feeling, the AI will scan your face and be able to determine which of the 8 emotions you are feeling based on where your eyebrows, eyes, mouth is positioned. This includes neutral (no specific emotion detected), happiness, sadness, surprise, fear, disgust, anger or contempt.
As I said in another article these facial expressions are universal, which means someone born in India makes the same expression to indicate an emotion as would someone born in America. Research shows that children born blind also have the same facial expressions for these universal feelings, and this leads psychologists to believe they aren’t taught.
In other words, Emotion AI machines possess emotional intelligence; they are capable of analyzing not only cognitive, but also effective channels of human communication, and are able to identify and respond appropriately to both verbal and nonverbal signals.
Normal people like us often find it difficult – if not impossible – to understand what people are feeling without seeing facial expressions and hearing tones.
Essentially, these machines are improving by detecting our intent and emotions, even going so far as to determine if smiling would significantly enhance an already positive situation.
Researchers also discovered that machines can be programmed with a wide variety of variables, including skin temperature, which can provide insight into complex moods like anxiety and stress, among other things.
Our behaviour is driven by our emotions. There is a fascinating example of this in marketing, where customers with positive emotional associations tend to stay loyal for longer periods than those who are detached or have negative feelings about a brand.
Hence, in order to build a successful brand, you need to understand your customers’ feelings and create an environment where they feel special and appreciated.
I know Emotion AI might sound really cool, but at the same time, quite scary. What if I asked, “If you could have an emotional interaction with your customers and make them feel better about you/your business, would you use technology for that?”
Or if I asked you to consider this from the opposite angle: If a brand were able to comprehend your feelings, deliver an extraordinary experience and do everything possible to please you, would you accept that?” What would be your answer?
The potential uses of emotional AI may be more valuable than ever before for consumers, who are increasingly demanding emotional connections from brands.
In building relationships, brands can personalise the user experience and thereby strengthen customer loyalty.
Nonetheless, if brands really wish to improve customer experience, they must develop a system that is not just based on rational intelligence, but one that’s also able to understand both the cognitive and emotive pathway of human communication, sense intentions, distinguish between literal and non-literal statements and then learn from every interaction.
It shouldn’t be the intent to replace people with machines (at least for now), but instead, use the AI tools as a support for surface level interactions when needed.
It could then catalogue the most common interactions and strive to improve these experiences by making them less stressful or more seamless.
Mental health: Cogito has built a solution that allows users to monitor their mental health using just the sound of their voice and an accompanying app. The CompanionMx is able to detect changes in mood or anxiety levels by analyzing the speaker’s voice and phone use. This technology can increase the self-awareness of users as well as offer coping skills that help manage stress levels by providing techniques on how to relax more easily.
Automotive: A new car AI service from Affectiva has been developed to track and measure a driver’s state, as well as the passengers’, in order to ensure safety. It can detect if drivers are arguing with their passengers or falling asleep at the wheel by looking for elevated blood pressure levels or listing movements respectively. If it detects either of these activities, then it will make subtle adjustments that bring all parties back into alignment before any accidents occur.
Advertising: Here I’m using Affectiva technologies as an example again – so, in the case of advertising research, once a client has been vetted and agreed to the terms of Affectiva’s use (like promising not to exploit the technology for surveillance or lie detection) they are given access to Affectiva’s technology.
With a customer’s consent, this cutting-edge software uses their phone or laptop camera in order to capture their reactions while watching ads that have already garnered public attention; these responses correlate strongly with actual consumer behaviour such as sharing it on social media platforms like Facebook. This research can show us how a customer truly feels about a product or a service.
Surveys: Emotion AI can reveal the unspoken details of a survey by using moment-by-moment feedback. The answer ‘yes, that was great’ or ‘no, that was terrible’ no longer suffices. We can now add facial expressions analysis to see “how were the eyebrows?”, “did their pupils dilate?” Then you’ll get a real answer to the questions posed.
Assistive services: Some people with Autism Spectrum Disorder (ASD) have difficulty communicating emotionally. Fortunately, there’s a way emotional assistive technology may serve as the perfect “assistive device” in these situations with wearable monitors which are able to detect subtleties in facial expressions sometimes misread by those diagnosed with ASD.
There are also smart chatbots that know what kind of offer to make a customer feel special, as well as smart CCTV cameras that enable retailers to record their customers’ reactions in real-time to their product assortment, product location, and pricing.
The use of personal data has become a common worry as people are now more conscious about their online privacy. In order for emotion AI to be effective, companies must state what ethics they follow and be transparent with the public otherwise it may have the opposite effect: unnerving users instead of reassuring them.
Overall, when technology is used thoughtfully, its benefits can outweigh its costs. Machines can help us do more, but we should be aware of the limitations. It’s not really about human versus machine – it’s about how humans and machines can work together.
Companies should use Emotion AI transparently if they want to build trust with customers.
Answering questions like “how is the data collected?” and “why is it collected?”, “who will have access to this information?” and “where and for how long will the data be stored?” exhibits the corporation digital responsibility – and this is the most important aspect of the game.
When we approach Emotional AI with these things in mind, there is huge potential to upgrade business and life and take us into a brave new world of emotions! Are you ready for artificial emotional intelligence?
I’m interested in hearing your thoughts on this.