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What is Cybernetics?

The blend of man and machine has been in existence for many years. However, cybernetics at its core goes way beyond the idea of humans and machines to its root core of communication between naturally occurring elements and man-made machinery. In essence, it helps us understand how the human body and governments work. This has made the field of study a lot more vast than most people would normally expect. 


Cybernetics can be defined as the study of human/machine interaction guided by the principle that numerous different types of systems can be studied according to principles of feedback, control, and communications. It was first introduced by an American mathematician and philosopher, Norbert Wiener, who wanted to understand and delve into the interaction between machines and human beings or other living organisms. While not the most popular, cybernetics is one of the most tremendous and beneficial technologies in the history of mankind.


“Cybernetics deals with all forms of behavior in so far as they are regular, or determinate, or reproducible”  - Ross Ashby


Among many other things, cybernetics has given us DVDs, computers, microwaves, lasers, the internet and so much more. Plato and Aristotle defined cybernetic as the art of piloting a ship, this was in the early days of cybernetics, many centuries ago. Since then it has spread to many different sciences including biology, philosophy, politics, and so on. 


Most recently, what has come to be common when it comes to cybernetics is the merging of humans and machines to produce what is popularly called cyborgs, this is what we will be concentrating mostly on in this article.  


Biological Cybernetics is an interdisciplinary medium for theoretical and application-oriented aspects of information processing in organisms, including sensory, motor, cognitive, and ecological phenomena. It is the application of cybernetics to biological sciences like neurology and multicellular systems.


Evolution Of Cybernetics


When one first thinks of a robot it may be a little wheeled device that springs to mind (Bekey 2005) or perhaps a metallic head that looks roughly human-like (Brooks 2002). Whatever the physical appearance, our thoughts tend to be that the robot might be operated remotely by a human, as in the case of a bomb disposal robot, or it may be controlled by a simple computer program, or may even be able to learn with a microprocessor as its technological brain. In all these cases we regard the robot simply as a machine. But what if the robot has a biological brain made up of brain cells (neurons), possibly even human neurons?


Neurons cultured/grown under laboratory conditions on an array of non-invasive electrodes provide an attractive alternative with which to realize a new form of the robot controller. An experimental control platform, essentially a robot body, can move around in a defined area purely under the control of such a network/brain and the effects of the brain, controlling the body, can be witnessed. Of course, this is extremely interesting from a robotics perspective but it also opens up a new approach to the study of the development of the brain itself because of its sensory-motor embodiment. Investigations can in this way be carried out into memory formation and reward/punishment scenarios — the elements that underpin the basic functioning of a brain.


Growing networks of brain cells in vitro (around 100 000 to 150 000 at present) typically commences by separating neurons obtained from fetal rodent cortical tissue. They are then grown (cultured) in a specialized chamber, in which they can be provided with suitable environmental conditions (e.g. appropriate temperature) and nutrients. An array of electrodes embedded in the base of the chamber (a multielectrode array, MEA) acts as a bidirectional electrical interface to/from the culture. This enables electrical signals to be supplied to stimulate the culture and also for recordings to be taken as outputs from the culture. The neurons in such cultures spontaneously connect, communicate, and develop within a few weeks, giving useful responses for typically three months at present. To all intents and purposes, it is rather like a brain in a jar!


In fact, the brain is grown in a glass specimen chamber lined with a flat ‘8×8’ MEA which can be used for real-time recordings (see Figure 1). In this way, it is possible to separate the firings of small groups of neurons by monitoring the output signals on the electrodes. Thereby a picture of the global activity of the entire network can be formed. It is also possible to electrically stimulate the culture via any of the electrodes to induce neural activity. The MEA, therefore, forms a bidirectional interface with the cultured neurons (Chiappalone et al. 2007; DeMarse et al. 2001).


The brain can then be coupled with its physical robot body (Warwick et al. 2010). Sensory data fed back from the robot is subsequently delivered to the culture, thereby closing the robot–culture loop. Thus, the processing of signals can be broken down into two discrete sections: a) “culture to a robot”, in which live neuronal activity is used as the decision-making mechanism for robot control; and b) “robot to culture”, which involves an input mapping process, from robot sensor to stimulate the culture.



Why is understanding cybernetics necessary to build “complete” AI systems? Just like a purpose-driven human with a certain role in life that learns from various external data under a feedback mechanism, AI systems should be built with a purpose that learns from external interaction or data but stays true to its purpose. The purpose can be guided by principles under which the system operates. In an evolutionary system, the purpose is survival of fittest whereas, in the capitalist system, the purpose is to maximize the economic outcome. If there is a certain external influence in the system that causes the system to behave erratically, the guiding principle of that particular system corrects the course to stay true to its purpose. Similarly, if an AI system behaved erratically due to external data, the principle behind the system should be developed in such a way to self-correct the system to stay true to its goals.

Hence, an AI systems should be built in such a way that it not only learns from objective knowledge but also subjective experience of the external system it interacts with, all the while remaining true to its purpose as defined by its guiding principles.



Neural interfaces, now a topic of significant, multi-disciplinary interest, read out electrical activity from the nervous system, with the aim to decode the signal with computational methods into cognitive, sensory, or motor information. This information can then be used to control a prosthetic device, robot, or computer. With the advent of microelectrode technologies, invasive approaches where neural activity is measured within the skull have advanced substantially and a breakthrough result where two tetraplegic patients could steer a robot arm with their mind was reported in 20123.


In non-invasive approaches such as electroencephalography (EEG), brain activity is measured with electrodes placed on the scalp, which has the advantage that no surgery is required. Decoding the recorded signals into useful real-time information is challenging, but advances in materials engineering and machine learning in the past decade are showing promise. A deep learning algorithm is trained to classify the signals and can be used offline. In one experiment (with able-bodied subjects) it is shown that a wheelchair can be controlled in real-time, demonstrating the practical promise of this approach.


Advantages of Cybernetics 


It wasn’t always clear just how beneficial cybernetics will be to the everyday life of individuals. Over time, however, we see it in almost everything we do, how it changes lives and new innovations and technologies make things that seemed impossible once, become an everyday solution. We’ll look at the benefits to some fields like biology, mathematics, engineering, psychology, and so on. It had already started to impact daily life in subtle ways. The exploration of this technology makes a lot of things that were not feasible previously become things that can now be achieved. This will only increase as technology expands.


Disadvantages of Cybernetics


Like every new technology, cybernetics also comes with its own sets of shortcomings. The first being that the tech is still new and untested, this means there is still a long way to go before it can truly be integrated into society. Another obvious disadvantage is it's potential to be used in non-legal ways. But this is the same for every new tech, while it holds the possibility of great change, it also can be an instrument of great harm.



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