In this technology overpowered world, it now seems impossible to live without PCs, laptops, smartphones and other consumer electronic devices. The prevalence of digital technology and its continuous influence has altered our lifestyles to a point where our dependability on technology has become immense. This has made our connection with technology increasingly complex.
On one hand, we humans struggle to communicate the correct emotions through electronic gadgets in order to understand one another, whereas, on the other hand, emotional AI (artificial intelligence) has taken a huge leap. Face-tracking and recognition technology now has advanced capabilities to analyze even the minutest details of our facial expressions. Some advanced emotion recognition systems can even differentiate between genuine and fake emotions.
What is emotional AI?
Businesses must leverage emotional AI technology to capture people’s emotions in real time. Emotional AI is a technology through which facial expressions can be decoded, voice patterns can be analysed, e-mails can be scanned to understand the tone of language, eye movements can be monitored, neurological immersion levels can be measured etc. For companies, this technology can prove to be a game changer as it can help them understand their customers deeply and make real/personal connections.
According to Gartner, emotion AI capabilities will be present in 10% of personal devices by 2022, a massive increase from 1% in 2018. This could either be on-device or via cloud services. Indeed, a powerful tool, emotional AI will help businesses realign their customer relationship tactics and pave way for new ways and metrics to understand them. Also, resulting in redefining our approach to know more about products and services.
However, as businesses delve into the budding emotional AI technology, the risks associated with it can’t be ignored. The process of interpreting sensitive human emotions and churning out data from it to turn into meaningful insights is a sensitive business. Individuals can consider this as an act of privacy invasion, bias and emotional manipulation. The need for transparency & responsible usage of emotional AI data will be paramount as customers would want to understand how this data is being used after it is collected. According to Accenture, the profit gains are nearly double than that of the average company in a specific industry, when such a company leads in both responsibility and intensity of data usage.
Emotional AI opens new opportunities
For technology and communications companies, with the advent of emotional AI, the pool of opportunity has just opened! A whole new form of data known as “emotional data” is being created, which consists of biometric and psychological data points aggregated through text analysis, eye movement, voice recognition, emotional detection, heart rate etc.
Since a decade now, while several tech giants and start-ups have been investing in emotional AI, the emerging technology is now also a part of various commercial deployments as well such as digital voice assistants, call centers, cars, smart devices like smartphones, TVs, fitness/health trackers, robotics etc.
Imagine if a smart speaker could identify the mood of person based on their voice’s tone or choice of words. Or perhaps, a camera-enabled TV that can capture the viewer’s emotion by detecting their facial expressions. The new emotional AI applications can result in companies providing better customer service, enhance customer and user experience with perfected UX design. Emotional AI can help businesses understand how customers really feel about them and their products or services.
Even though the technology for emotional AI is still on the rise, the discussions around this topic are increasing consistently, giving an indication that emotional data and emotional AI will be of importance in the future. Emotional AI has the potential to unleash a new universe of possibilities and opportunities.
What it means for companies?
The era of emotional AI is here and companies across the world are preparing to embrace it. Businesses are brainstorming the process of data collection, rules of data analytics and the business models to support them. According to Accenture, companies must consider the following 4 factors when they step into emotion analytics – transparency, systems design, data usage, privacy. The sense of responsibility can’t be shrugged off as responsible actions today can prevent the consequences of future. Without correct responsibility measures, businesses can lose the trust of their customers and squander the opportunity to innovate and boost growth by harnessing the power of emotional AI.
Top emotional AI use cases
Companies have leveraged the capabilities of emotion AI to enhance customer experience and growth. Some of the top emerging use cases of emotional AI are:
1. Video gaming testing: During the testing phase, video game makers can analyse, using computer vision, the emotions through facial expressions to unveil critical insights about gaming behaviour as well as provide feedback to improve the product.
2. Ed-tech: E-learning softwares can be developed that can analyse a child’s emotion and tweak the course/task according to his/her behaviour. Suppose if a child shows frustration due to a task being complex, the program can adapt and refresh the task with a simpler one. Such learning systems can also help autistic children recognize other’s emotions easily.
3. Healthcare: Using emotional AI, healthcare workers can easily diagnose mental health issues such as depression and dementia using voice analytics.
4. Safety in cars: By using emotion AI technology, automotive companies can monitor the emotional state of the driver by using computer vision technology to send trigger alerts in case of drowsiness or extreme emotions such as anger, frustration etc.
5. Employee care: Gartner reveals that demand for employee safety solutions is rising continuously. Emotional AI can help companies analyse the anxiety and stress levels of its employees and try to help them out.
6. Call centers: The call center companies can handle an angry customer in a better way if they can detect the emotion of the customer beforehand and re-route him/her to a well-trained executive. The executive can also monitor the conversation in real-time and adjust accordingly.
7. Fraud detection: Through voice analysis, companies on the BFSI industry can detect the real intentions behind a customer’s word/claim. Approximately 30% of users have agreed to lying to car insurance companies to get insurance money (Independent surveys).
The dangers in adopting emotional AI technology
Even though emotional AI has many upsides, there are potential pitfalls as well. People are concerned about their privacy and the risks that are associated with being tracked online. Other concerning factor is the incapability to analyse vast spectrum of human emotions. The current capabilities of emotional AI are not quite advanced. Irrespective of this fact, the technology is currently capable enough to be used for commercial deployments.
Emotions play such a vital role in our everyday lives. If emotional AI can help make our interactions with technology more responsive and intuitive, newer possibilities can be explored. However, certain barriers to adopt this technology remain, and as revealed by Gartner, the trust issues associated with emotion AI technology still exist. The company said in one of its consumer surveys that users feel more comfortable with voice analysis rather than capturing emotions via camera. Still in the emerging stage, the global emotion analytics market is predicted to increase to $23 billion by 2023 (Market Research Future).
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