Emotion AI: How Far Can It Go?
Robots with emotions can perform complex tasks better. But how do machines learn to detect emotions, and what business opportunities does emotion AI present?
In today’s world, digital media progressively filter communication. Instead of a face-to-face conversation, we send chat messages or schedule a video call. We prefer to shop online, and if we encounter any issues while doing so, we turn to chatbots. This filter is not always beneficial — all too often, the communication is distorted, questions are misinterpreted, and frustration develops as a result.
But what if the technology that hinders our communication at times could actually enhance it? Futurologists and trend researchers are optimistic that this will be the case in the future with emotion AI.
How does Emotion AI work?
Emotion AI, like any other AI technique, requires data to enhance performance and comprehend user emotions. The data differs from use case to use case. For instance, social media activity, speech and actions in video recordings, physiological sensors in devices, etc. are used to comprehend the audience’s emotions.
Following the identification of emotional-impacting features, the process of engineering features occurs. Eyebrow movement, mouth shape, and eye gaze can be used to determine whether a person is joyful, sad, or angry. Similarly, in speech-based emotion detection, pitch, volume, and tempo can deduce whether a person is excited, frustrated, or bored.
Later, these features are pre-processed and used to train a machine learning algorithm that can precisely predict the emotional states of users. Finally, the model is implemented in real-world applications to enhance the user experience, boost sales, and suggest relevant content.
Uses for Emotion AI Technology
Mental health treatment
According to a report from the National Institute of Mental Health, more than one in five citizens in the United States suffer from a mental illness. This means that millions of people are either emotionally unaware or incapable of managing their emotions. Emotion AI can assist people by increasing their self-awareness and teaching them stress-reduction coping mechanisms.
Emotion AI-powered chatbots can emulate a therapist or a counselor, automating talk therapy and increasing accessibility. There are also mood monitoring apps, such as Woebot, that assist individuals in managing their mental health through short daily chat conversations, mood tracking, games, curated videos, etc. MIT Media Lab has created a wearable olfactory display as another example of AI-powered mental health technology. It can monitor the wearer’s cardiorespiratory data and, when necessary, release various scent combinations to treat psychological issues such as stress or anxiety.
Call Centers
Inbound and outbound call centers are constantly interacting with consumers regarding calls for various services and campaigns. Call centers evaluate agent performance and customer satisfaction by analyzing agents’ and customers’ emotional responses during contact. In addition, agents utilize Emotion AI to comprehend the disposition of consumers and communicate effectively.
Humana, a prominent health insurance provider, has been using Emotion AI in its call centers for some time now to efficiently serve its customers. With the aid of an Emotion AI-empowered digital coach, agents in the call center are prompted in real time to modify their pitch and conversation according to the customers.
Advertising
The objective of developing Emotion AI-powered solutions for the advertising industry is to create more personalized and engaging consumer experiences. Frequently, the emotional cues of customers aid in the creation of targeted advertisements and the increase of engagement and sales.
Affectiva, a Boston-based Emotion AI company, collects user data such as responses to a specific advertisement. Later, AI models are used to identify what elicited the strongest emotional response from observers. Finally, these insights are implemented into advertisements to increase sales and optimize campaigns.
Automotive
There are approximately 1.44 billion registered vehicles worldwide. In 2021, the automotive industry in the United States alone generated revenue of $1,53 trillion. Despite being one of the world’s largest industries, the automotive industry strives for road safety and disaster reduction to prevail. In the United States, there are 11.7 deaths per 100,000 individuals due to automobile accidents, according to a survey. Therefore, for the industry’s long-term development, Emotion AI can be used to prevent avoidable accidents.
Several applications utilize sensors to monitor the driver’s condition. Software development companies develop apps that can detect tension, frustration, and fatigue. Harman Automotive has developed an Emotion AI-powered adaptive vehicle control system that uses facial recognition technology to analyze the emotional condition of the driver. Under certain conditions, the system adjusts the vehicle’s settings to provide the driver with comforting features, such as calming audio or ambient lighting, to prevent distractions and accidents.
Customer-brand relationships
The greater a company’s understanding of the underlying emotions of its loyal customers, the more effectively it can tailor its products and services to the requirements of its target market. The tools developed by the Boston-based startup Cogito that enable client businesses to assure high-quality employee-to-customer interactions are an example of this technology in action. The algorithms underlying Cogito’s technology help detect symptoms of “compassion fatigue” in customer service agents and provide guidance on best practices for addressing callers’ concerns.
By listening to the conversation between the client and agent, the technology can determine the emotional state of the caller (from anger to happiness) and make insightful suggestions about when and where to apply empathy and change the tone when addressing the customer’s requirements.
Disadvantages of Emotion AI
Despite the numerous applications and potential of this type of AI, emotions are ambiguous, and the application of some of these technologies in high-consequence situations can be extremely problematic.
- Emotion AI does not provide a complete picture of how a person is experiencing. A notorious example is a hiring system that utilizes the facial expressions and voice patterns of job candidates to calculate an “employability score.”
- As with other technologies, emotion AI can exhibit biases and inaccuracies. For instance, if an insurance company wants to use emotion AI to determine driver fatigue based on facial expressions, older drivers will be more likely to meet the criteria, even if they do not exhibit physical symptoms. This is because as you age, your facial muscles tend to stiffen and become less flexible.
- Consumers must consent to emotion AI analysis, which may raise some privacy concerns.
Why does Emotion AI matter?
Daniel Goleman, a psychologist, wrote in his book “Emotional Intelligence: Why It Can Matter More Than IQ” that Emotional Intelligence (EQ) is more significant than Intelligence Quotient (IQ). According to him, EQ has a greater impact on an individual’s performance in life than IQ. This demonstrates that emotional control is necessary for making rational and well-informed decisions. As humans are susceptible to emotional bias that can impair their logical reasoning, Emotion AI can assist with daily tasks by employing discerning judgment and making the correct decision.
Moreover, given the current state of the technological world, the global use of technology is expanding. As people become more interconnected and technology continues to advance, the reliance on technology to address a wide range of issues grows. Therefore, artificial empathy is essential for making interactions with people more personalized and empathetic.
Emotion AI incorporates artificial empathy into machines to create intelligent products that can effectively comprehend and respond to human emotions. For example, a research team at RMIT University developed a healthcare application utilizing artificial empathy. This application is designed to analyze a person’s voice and determine if he has Parkinson’s disease. In the gaming industry, artificial empathy is used to create convincing characters that respond to the emotions of the player and enhance the overall gaming experience.
It is currently unknown how long it will take AI to achieve consciousness and self-awareness. But one thing is certain: AI is just beginning to make great strides.
Final thoughts
It is currently inconceivable that AI could have human rights, make independent decisions, or share the emotions it may be able to recognize in humans. Even though there is a great deal of uncertainty surrounding the future of Emotion AI and how far it can go, it appears that nothing is impossible given the rapidity with which AI technologies have become commonplace and pervasive.
