We see many examples of conscious robots in science fiction but things are just not there in the real world.

According to Aleksander, the aim of the theory of Artificial Consciousness (AC) is to define that which would have to be synthesized were consciousness to be found in an engineered artifact. This concept which is also known as Machine Consciousness is related to the fields of Artificial Intelligence (AI) and Cognitive Robotics. As extremely advanced robots have emerged to the scene following the advancement of technology, a massive question is when they will gain self-awareness.

The element of abstract thinking, present in humans, is missing from these revolutionary inventions until now. It requires consciousness which is attained by recognizing yourself and your place in the outside world. In views of Neuroscience, different parts of a human brain work together to generate Neural Correlates of Consciousness (NCC). The researchers working on Artificial Consciousness believes that a system can be developed which will emulate the NCC interoperation in robots.

As discussed above, the opinions of neuroscientists and philosophers contradict as they define Artificial Consciousness. The basis for this diversity comes from different potential implementations of AC. Philosophical literature itself has multiple definitions of consciousness. The phenomenal consciousness revolves around those aspects of an experience that are linked with feelings and cannot be apprehended while the access consciousness deals with those parts that can be apprehended. The application of these philosophical theories to Artificial Intelligence carries significant risks that should be kept in mind.

Some of the processing abilities used in AI are similar to the working mechanism of our brain. Deep Learning, a sophisticated technique used in AI, is a prime example which strengthens this point of view. Incredibly efficient algorithms are arranged in form of layers which gives birth to several networks that perform rapid processing of the information. The communication among these networks is responsible for the outstanding results of this technique as it can solve more and more complex problems in less time. This entire procedure can be mapped onto the working of our brain where information travels rapidly across connections between Neurons.

Deep learning enables a machine to perform several complex tasks like playing Chess or writing a poem. Having said that, all the achievements of any neural network in the world could not have been possible without the excellence of a human brain. It is a human programmer that develops the software for a robot and he is the one who provides the learning data for that piece of code. This is where AC could bring mind-boggling changes. If a neural network is smart enough that it takes all its decision on its own, machines can be considered as Conscious. Edith Elkind, a Computer Science Professor at the University of Oxford, seems to agree to that as she said,

“Machines will become conscious when they start to set their own goals and act according to these goals rather than do what they were programmed to do. This is different from autonomy: Even a fully autonomous car would still drive from A to B as told.”

According to a study, human consciousness can be divided into three stages. This characterization is based on the computation happening inside our brains. ‘C0’ is the 1^st level where calculations are being made without our knowledge. Most of the AI functions are currently at this level of computation. After that comes the 2^nd stage which is known as ‘C1’. This is based on our knowledge as a human brain makes an informed selection after evaluating different quantities of data in a particular scenario. This level is attained, to some extent, through Deep Learning. The 3^rd level which is known as ‘C2’ deals with consciousness and self-awareness.

At this level of thinking, our brain allows us to make decisions on our own without any previous knowledge. We explore more things as we investigate the unknown. Incorporating this in a robot will become a whole lot easier if we know the exact differences. Hakwan Lau, a Neuroscientist at UCLA and co-author of the study, agreed to that by saying,

“Once we can spell out in computational terms what the differences may be in humans between conscious and unconsciousness, coding that into computers may not be that hard.”