Artificial Intelligence has literally stormed numerous industries, business processes, and our lifestyles. With Artificial Intelligence technology, today it is possible to augment human intelligence and utilize it in decision-making and customer interactions. The current digital transformation has brought many cutting-edge technologies to the forefront and is stressing the significance of AI and Big Data in revolutionizing industries. The role of artificial intelligence in the business arena has proved to be positively redefining operations and thereby encouraging cost-efficiency.
However, there are areas connected to AI that researchers are still studying to enhance the simulation of human intelligence to an extent, which enables sentiment analysis. Researchers at the University of Helsinki and the University of Copenhagen have come up with a technology wherein AI can read the brainwaves to understand and define subjective notions.
A brain-computer interface (BCI)is a communication system that connects the brain with an external machine or device. A brain-Computer interface is capable of measuring the activity in an individual’s Central Nervous System (CNS). The measured brain activity is converted into electronic and software signals to be interpreted by AI.
Electroencephalography (EEG) and electromyography (EMG) are the technologies already used by doctors to understand the neural activities of our brain and muscles, respectively. BCI is extensively implemented in the healthcare industry pertaining to broken neural connections between our brain and other body parts.
How does it work?
This study is opening up new avenues for artificial intelligence, machine learning, and data analytics. Generative Adversarial Neural Networks, a machine-learning model, was trained to familiarize with individual preferences of faces to facilitate the generation of new facial dimensions according to the brainwaves.
The researchers created new portraits for each participant involved, to test the validity of their modeling, and interestingly, predicted that they will personally find these models attractive. Further, the researchers tested them in a double-blind procedure as opposed to matched controls finally leading to the conclusion that the new images match the preferences of the subjects with an accuracy of about 80%.
Connecting artificial neural networks to our brain can now produce results entirely based on our personal preferences through a non-verbal communication process. This development is new as the neural networks or BCIs cannot peek into our personal choices and hence can only establish the pattern of activities.
AI is not very far from augmenting and understanding the human brain more extensively. However, such an invasion of technology such as AI into the internal structures of our brain will surely raise concerns about privacy and ethics. This new development will make possible the understanding of individual and subjective biases that are internalized deep in our brains.
These innovations and developments in the field of AI will surely aid AI companies in expanding their business avenues and services.