Artificial Intelligence Can Now Read Minds, Until recently, it seemed like a fantasy, and to top it off, one worthy of the best fantasy films. Today, however, it is a question of what we can effectively consider reality.
The credit for having developed software based on the use of artificial intelligence belongs to some American scientists, who have managed to create an algorithm capable of transforming thoughts into a series of written words.
This system analyzes people’s brain activity, contributing, in fact, to transforming it into words. The software has already been tested with good results but is still far from being used in a detailed and precise manner.
The creation of this program is the work of scientists from the University of California (in San Francisco). They have developed software that can read people’s minds by translating their brain waves. The study was published in Nature Neuroscience.
The degree of reliability that the software development team has reported hovers around the 97% level. Therefore this program is considered very reliable, managing to translate people’s brain waves into words in a very precise way. The scientific world is already talking about the recent discovery made by American researchers since it is a disruptive activity capable of overturning the most common scientific concepts.
The peculiarity of this type of system lies in the fact that the software does not have to listen to any text, not a single word. The reading takes place through sensors on the person’s head that generate the electrocorticogram, through which the tracing of all the movements carried out in the center of the cerebral cortex is analyzed.
Artificial intelligence will allow, shortly, to avoid all those systems that need voice input, focusing on other methods of data acquisition, which only involve the need to analyze the frequency of the cerebral cortex.
Until recently, it seemed like a fantasy, moreover one worthy of the best fantasy films. Today, however, it is a question of what we can effectively consider reality.
The credit for having developed software based on the use of artificial intelligence belongs to some American scientists, who have managed to create an algorithm capable of transforming thoughts into a series of written words.
This system analyzes people’s brain activity, contributing, in fact, to transforming it into words. The software has already been tested with good results but is still far from being used in a detailed and precise manner.
For many years now, the world scientific community has been trying to create a system capable of transforming into words the image of brain activity capable of replacing the human speech apparatus. However, most inventors tried associating brain signals with movements of speech organs or pronounced sounds. Scientists at the University of California at San Francisco have decided to distance themselves from their colleagues and have invented software that combines neural signals with sentences. To do this, they had to adapt the algorithms used in machine translation from one language to another. Thus, the brain, which perceives language, translates it into a graph of electrical activity, and artificial intelligence helps to perform the reverse translation.
Although the translation accuracy is very high, the possibility of error was still foreseen and, as already mentioned, is equal to 3%. This essentially means that, at least initially, using this instrument could still entail various problems, including low reading accuracy.
The main errors in using this program are due to the confusion that can be created between words with similar meanings. Considering that even a single letter could completely change the meaning of the word, misunderstanding the purpose of the thought could be very simple. The artificial intelligence in question can still constitute a 100% new benchmark.
To develop the neural network, scientists David Moses and Joseph Makin of the UCSF Center, led by Mr. Edward Chang, using data collected from various people who offered to participate in an experiment.
Various brain electrodes were attached to these people’s heads while, at the request of experts, they were told to read a series of sentences aloud, and the science team recorded the activity of their brains. Subsequently, the collected signals were passed on to the neural network algorithm. This algorithm was developed to identify language patterns regularly created as a combination of vowels and consonants by analyzing the repetitive aspects of communication.
The received patterns were then transmitted to a second neural network, which tried to ” translate ” the data into words to form various sentences. As a result, in the test, the best AI result showed only 3% of errors. However, there were also results with a wider margin of error. This, in turn, makes it mandatory to work further on the reading algorithms of this software. In addition, only short and simple sentences were given during the tests. As has been shown, the program starts making more mistakes with an increase in the number of words read. For these reasons, initially, it will be necessary to use this artificial intelligence only to read pretty short sentences.
Despite what is often portrayed in movies or works of art, this is not bad or bad technology. Quite the contrary: the system promises many benefits to a wide range of sectors.
Edward Chang suggests that one-day such software could be used to read the minds of those who have lost the faculty of speech due to illness. Just think of people who are bedridden or wheelchair-bound and who cannot move or speak.
But that’s not all: this type of program can also be used successfully throughout the tech world.
Currently, various information is transmitted to computers or smartphones via words or using a keyboard. In the future, however, this technology could be used without problems precisely to control the various electronic devices of daily use. Instead of talking to our smartphone or typing on the keyboard, we could entrust our thoughts to artificial intelligence, which will transmit our requests directly to the device.
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