Artificial Intelligence (AI) has already impacted businesses across many industries and sectors. For example, in healthcare, AI processes are making it easier to access patient records. In manufacturing, elaborate algorithms enable machines to predict problems before they happen. And, in the financial sector, AI is automating compliance systems.
The technology may be popular, but today, there’s something missing: humanity. Artificial intelligence technology is great for predictive analysis and automation, but it remains an emotionless technology. However, all this could be about to change. A series of important projects are making the idea of AI with emotions a reality. However, emotional, or emotion, AI must learn how to detect human feelings before it can replicate them.
Learning From The Masters
Before we discuss the possibilities and potential limitations of emotion AI, it’s important to consider where we are today. Interestingly, although common, emotion AI can also be controversial.
AI is already being used to identify and analyze human emotions. Today, it enables many businesses to improve their services and offer a more pleasant user experience.
The technology is being used by advertisers to measure opinions on specific products. In an educational setting, emotional AI is being used to adjust learning resources to individual children. And, in the insurance industry, the technology can identify false claims. These are just some of the current use cases for emotion AI, but there are many more.
The Dark Side of Emotion AI
Although emotion AI technology has multiple benefits, some users have applied it in controversial ways. Most recently, a report by the BBC found out about the use of suspect emotion AI techniques by the Chinese government.
The report said that the government had used the technology to monitor members of the minority Uyghur people. The idea of the exercise was to identify unusual behavior by analyzing facial expressions. Human rights groups have come out against the experiment, but there are likely to be many similar examples.
So, emotion AI has the power to help and in other cases hinder. However, this is just one step toward the goal of building an emotional AI. And, the next move, conversational AI, could be even more impressive.
What’s Next for Emotion AI?
Scientists are coming close to developing AI with emotions, but they’re not there yet. One of the most interesting developments has been the launch of carmaker MG’s new Astor.
The car is packed with technology, such as a blockchain-secured digital passport, automatic braking, and other features. However, from an AI perspective, the car’s personal assistant is the biggest achievement.
The MG Astor’s AI-powered personal assistant is the first of its kind. It shows human-like emotions and engages with drivers. And, with access to Wikipedia, the bot can even provide passengers with information and, potentially, conduct a conversation.
In another important example, researchers at the University of Zagreb, Croatia have developed an AI robot called PLEA. The robot is unique. It uses a process called biomimicking to learn how a person is feeling and responds proportionately.
PLEA assesses the tone of voice, facial expressions, and other social signals of the person it’s talking to. It’s impressive, but the ultimate aim of the PLEA project is to adapt the technology into a care robot.
Unsurprisingly, Google has also been busy developing emotional AI prototypes. One of the most significant was showcased back in 2018. Google Duplex is an AI technology that enables computers to take over certain calling responsibilities. The technology allows businesses to pass over tasks, like appointment scheduling, to AI bots. Using emotional AI techniques, the bots can engage with the customer naturally and to a point that they sound human.
How Can Businesses Benefit?
AI is becoming increasingly ingrained in business operations. However, some business owners might question the importance of giving technology a soul. Of course, the ability to read emotions is a powerful asset. It enables companies to adapt to customer preferences and target services more effectively.
Yet, from a business perspective, it can be difficult to see the benefits of equipping AI with emotions. At a base level, AI with emotions will be easier to reengage with. And, when something is easier to accept, people are more likely to adopt it.
If businesses invest in AI tools that users want to use, the potential for their use is much higher. For example, if a customer can have a genuine conversation with a bot, they might reveal more about their preferences. And, they may even decide to go further along a buying journey. Or, emotion AI could make it easier for companies to improve their services by explaining the things they dislike.
People might be concerned that giving AI so much responsibility will put regular humans out of a job. Google Duplex technology may have already taken jobs away from call center staff. However, this is unlikely to happen on any significant scale.
Emotion AI will most likely be used to grow business operations. Not, as some might believe, to replace humans and take over existing roles.
