As we know, the next frontier after AI (artificial intelligence) is to teach machines to touch, feel, and respond to human emotions—or emotional intelligence in a broad sense.
Few people will argue that artificial intelligence is needed to simplify the healthcare experience. But will the humanization of healthcare not become a victim of transactional artificial intelligence in healthcare?Recent deactivations and deactivations black pepper and Fabio Respectively are suitable examples, demonstrating the difficulty of programming empathy for robots, whether humanoid. Pepper has been tested on a series of transactions, from supporting students with autism to advanced peer care; but in all of these, the cost-benefit analysis did not benefit Pepper. Therefore, Pepper’s production suspension seems to revolve around cost efficiency relative to value. In addition, on the other hand, Fabio in the artificial intelligence world seems unable to translate empathy gestures in the correct context, so the “creep” factor is rampant. So in the UK, Fabio was tested as a welcomer in a high-end wine shop for the first time, and customers played a game of “hide and seek” to avoid Fabio!
The exciting (some say frustrating) thing about emotion or “emotional” machine learning is that the machines being created have amazing capabilities to analyze and continuously monitor our hidden emotional responses, not just our actions And purchase response. Whether we like it or hate it, we are all hooked on our devices now. In the new, always-on virtual world, when we embrace virtual normality, it is difficult to completely disconnect from smartphones, computers, TVs, live broadcasts, and even cameras in clinics or stores.
These ubiquitous devices continuously record our smiles and frowns, and reflect the emotions deep in our hearts. In the healthcare sector, if these data are captured and used appropriately, we can better understand consumer mentality in the healthcare sector. It can more accurately understand the pain points of consumers in real time. Artificial intelligence can help us decode body language, such as understanding whether consumers fully understand their follow-up instructions in the doctor’s office; in addition, it can help us decode which patients are most willing to follow up. This will avoid consumer waste that is not ready to participate and enrich the consumption of customers and those who are ready.
The new technology called “emotional artificial intelligence” is part of a broader artificial intelligence technology. Emotional AI now means that machines can interpret our thoughts and emotions in a variety of ways, and give value to smiling, frowning, or confused eyebrows. The machine has been able to analyze large amounts of data in a few seconds. In the past 20 years, people have begun to teach machines to read emotions and images. They can associate these with positive experiences (such as brand realization) or negative experiences (such as fear, stress, disappointment, or anger).
In our business as healthcare professionals, we know that AI and EI are already in use. They are a valuable tool for healthcare research because they can link subconscious responses to actual buying behavior, satisfaction, and future net recommendation value or at least the likelihood of recommendation. In call centers, emotional AI can provide nurses and welfare navigators with useful feedback on the mindset of customers. It can be said that these emotional indicators can help nurses and navigators adjust their tone and pitch to best suit consumers’ calls. When we combine emotional AI data with voice analysis software, we can learn how to adjust the functions of healthcare products, modify the blueprint for delivery, and improve customer satisfaction in real time.
Emotional artificial intelligence has a wide range of applications in mental health, remote monitoring (through voice and other biometric technologies, such as blood pressure and heartbeat), and telemedicine. For example, in the field of mental health, emotional AI can help decode and predict patients with varying degrees of depression. Smart cars will soon be alert to the driver’s mental state, frustration, or fatigue. People with autism cannot tell you how they feel. But emotional AI can recognize facial expressions or increased pulse rate and create an emotional profile of a person’s health and mental state. In workplaces that still require shift work and long hours, such as manufacturing and retail, healthcare companies that deploy emotional AI can help employers track employees’ frustrations or reduced enthusiasm, and provide active employee assistance programs (EAP) to improve Connect with counseling and guidance.
The way to think about this beautiful new world may not be as a threat, but as a useful intermediary. It’s not that machines control humans, but humans have become better at being humans and healthcare professionals, and they have the ability to drive focused initiatives for each industry and outcome.
This is another appeal to those who can take advantage of EI…Despite the pandemic, what I call Covidacity is to embrace positive and bold goals.
Photo: wildpixel, Getty Images
