Emotion AI – the artificial emotional intelligence
Robots with emotions can master complex tasks better. Researchers are convinced of this. But how do machines learn to read emotions, and what opportunities does emotion AI open up in the business world?
Emotion AI: human-machine communication 2.0
In today’s world, communication is being increasingly filtered through digital media. Instead of interacting in a face-to-face conversation, we send chat messages or arrange a video call. We prefer to browse through online shops and if we encounter any problems there, we turn to chatbots. This filter is not always beneficial – all too often, the communication is distorted, questions are misinterpreted, and frustration grows as a result.
But what if the technology that sometimes hampers our communication could actually help to optimize it? Futurologists and trend researchers are optimistic that emotion AI will do just that in the future.
How does AI detect emotions?
Emotion AI, also known as affective computing, is essentially all about detecting emotions using artificial intelligence. Machines with this kind of emotional intelligence are able to understand not only the cognitive but also the emotive channels of human communication. That enables them to detect, interpret, and respond appropriately to both verbal and nonverbal signals.
In the research field, a lot of work is being put into imparting an emotional understanding to machines. Machine learning and deep learning are especially relevant in this respect. With these technologies, images and speech recognition systems are used as input for the machines. In this way, the machines learn how to recognize and interpret a smile or change in tone of voice, for example: Is it a happy or sad smile? Does it make the current situation better or worse than before? However, researchers are also working with parameters such as skin temperature and heart rate, which, among other things, are practical for developing wearables that are as smart as possible.
The enormous potential of emotion AI
Emotions have an enormous influence on our behavior. That can also – and in fact especially – be seen along the customer journey from a marketing perspective. When customers have positive emotional associations with a brand, they are much more likely to be loyal to it than if the evoked associations are detached or even negative. Therefore, if brands want to improve the customer experience, they need a system that doesn’t work on the basis of purely rational intelligence, but is also able to
- learn from every interaction,
- understand both the cognitive and emotive pathway of human communication,
- sense intentions, and
- distinguish between literal and non-literal statements.
In short: marketers need emotion AI.
How Affectiva has implemented emotion AI
Emotion AI is a valuable marketing tool with enormous potential for optimizing the customer relationship. The U.S.-based company Affectiva, which is specialized in the field of advertising research, among others, demonstrates how to harness this potential. With the consent of its users, the brand uses emotion AI to record and analyze their reactions to ads – and thereby gains insights into what is received well by users and what isn’t.
This strategy allows online ads to be tested and precisely tailored to the target group before they are officially published. So, if your brand is about to plan a new ad campaign and consequently has to choose between different options, emotion AI could simplify your decision in the future with the help of targeted data.
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#Advertising is getting #emotional. We analyzed 10 million consumer responses to 53,000 ads in 90 countries, to understand how brands are building positive connections with their customers. Go to our website to check out our analysis for insights that inform how advertisers should shape content to effectively engage consumers on an emotional level, especially during the COVID-19 pandemic.
Possible application fields of emotion AI
Apart from its use in advertising research, there are a wide range of ways in which brands can benefit from developments in the field of emotion AI. For example:
- Smart chatbots that identify different customer types, their behavior, and their motives can strengthen the customer relationship in the long term – e.g. by giving personalized product recommendations or providing individual answers to questions.
- Smart CCTV cameras enable retail stores to record customer reactions to products, prices, etc. in real time and thereby improve their range and pricing.
- Cameras integrated in computers, smartphones, or connected TVs make it possible for brands to leverage emotion AI in order to test reactions to certain content and adapt their online presence accordingly.
Emotion AI requires transparency
More and more people are developing a high level of alertness to data protection and online privacy. For emotion AI to work and not have the opposite effect, i.e. unnerving users instead of providing positive reinforcement, it is crucial for companies to clearly communicate their digital ethics and be transparent.
- What data will be collected for what purpose?
- Who will have access to this data?
- Where and how long will the data be stored?
If you want to take the next step toward a digital future with your brand, it is important to keep these questions in mind, demonstrate your corporate digital responsibility, and not shy away from engaging in a dialogue with your customers. That will set you up well for building the trust with your users that is needed for this next step.
Emotion AI – embarking on the path to an emotional future
When it comes to reading and understanding emotions, humans are (still) way ahead of machines. Nonetheless, emotion AI already offers opportunities for personalizing the user experience and thereby strengthening the customer relationship. It is foreseeable that with further scientific progress, the emotional intelligence of machines will become more accurate.
The technical cornerstone for this evolution has been laid – now we just have to closely observe how quickly the machines learn to show empathy and thus become an increasingly integral part of our communication and our consumption behavior.