Here we are at the end of our series of Transparent AI with episode 4 of this series, talking about the applications of AI, types of AI, and the AI effect. If you haven’t seen the old episodes, please make sure to check them all here:
Transparent AI Part 1: It’s all about Emotions
Transparent AI Part 2: Modeling Emotions
Transparent AI Part 3: How to train an AI
Applications of AI
Let’s start with the applications of AI. In other words, it’s time to find a job for our adult artificial intelligent agent in this world. Let’s say there are two types of jobs we propose to our AI:
1) Jobs that make our lives easier, 2) novel Jobs that we as humans can’t do them.
For example, an emotion recognition application in a call center can help the agents reflect on their tone objectively and adjust themselves in real-time if necessary. Besides, they can also see how the tone of the customer changes throughout a conversation and how much happiness they are bringing into this world. This example clearly shows an application of AI in which it helps humans shoulder to shoulder and augments them.
Now, let’s take vocal biomarkers as another example. Science shows that some diseases make changes in our vocal cords and our voice. These changes are so subtle that we can’t hear them, however, an AI can look into the changes in frequencies and audio waves, and find patterns there that are otherwise hidden to us. It would then help us detect diseases like Parkinson, and hopefully Covid from these changes. You can donate your voice to AI-sound-lab and have a role in the creation of a health AI.
If we look at the gaming industry, we can see both of these categories there. entertAIn observe can help companies in their playtest process to ensure that their game resonates with their audience. In this example, AI saves you a lot of time to listen to every session and tells you which parts are more important for you to focus on. On the other hand, entertAIn play helps game designers and developers to create games and implement new emotional interactions that are otherwise not possible. In this case, AI is enabling us to implement completely novel scenarios.
Types of AI
Now that you know more about Artificial Intelligence, you are probably wondering about different types of it and the future of AI.
In these episodes, we talked about emotion recognition AI using audio which is a narrow use case. That’s why we call it Artificial Narrow Intelligence (ANI). It can perform a task as well as a human or even better.
Most scientists think that by the end of this century, we will have artificial intelligence that can hypothetically learn and understand any intellectual task that a human being can. We usually refer to it as Artificial General Intelligence (AGI). It means you can possibly have an AI agent at work that can help you in a more humane way than searching in google for hours to find an answer.
Hypothetically speaking, scientists believe that at some point in the future of humanity, we will have Artificial Super Intelligence (ASI). ASI is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds. In other words, the relation of ASI to our intelligence will be the relation of using our muscles to shovel and using bucket-wheel excavator (BWE). It took mechanical engineers a few decades to go from a steam engine to a BWE, and now we are witnessing it again for the software engineers and AI researchers in their field.
The AI effect
When looking at the evolution of AI and changes in the definition, we come across a concept called “The AI Effect”. In simple words, it means whatever the computers can do and we understand it, we don’t call it AI anymore. Back in the day, AI was some algorithms that can understand the environment and interact with it. Now, it’s a system that can learn and performs tasks that are considered doable only by humans, and maybe in the future, our expectations of AI would be to do super-human tasks and it would be totally normal for us.
So, in this series, we started a journey to understand the definition of emotion, and we learned how we can model them. Afterward, we delved deeper into the world of AI, and we saw how an ANI can be trained using our data. Finally, we saw some of the applications that this “emotion AI” can be used in and we learned some bonus points about different types of AI and the AI effect.
If you are interested in using our AI technology in your industry, please feel free to contact us, and we would be glad to help you take one more step towards a brighter future.