How to apply the Uncanny Valley Theory to virtual agents or CallBots?
The Theory of the Uncanny Valley: methodology and subsequent interpretations.
The theory of the “uncanny valley” or “inexplicable” was developed in 1970 by the robotics expert Masahiro Mori, and basically argues that when a bot shares a greater number of characteristics with a human, our empathy increases, generating a positive reaction. However, there comes a time when before this humanoid figure, this feeling changes drastically, generating rejection – a disturbing valley – or aversion to the degree of similarity of an entity that does not come to be considered “human”. This rejection becomes positive again the moment we approach what could be considered a healthy person, as can be seen in the following graph:
In order to corroborate this controversial theory, in 2011 a team from the University of San Diego conducted an experiment based on a robot (R), a human-like android (A) and a human (H). This experiment consisted of analyzing the effects on the brain when shown images of the three figures, using magnetic resonance imaging.
The answer was clear, while the robot (R) and the human (H) barely generated any reaction, the android (A) produced a great alteration in several areas of the brain. Therefore, these scientists concluded that, faced with a human appearance but with robotic behavior, we experience a different reaction is that does not fit in our brain
This particular reaction can be associated with a certain cognitive dissonance, since our brain has innate expectations about the appearance and characteristics of a human being, which this type of bots (by having a human appearance but with the “psyche” of an AI) these expectations are not fulfilled. On the other hand, religious motives and standards of how a human being should be can also greatly contribute in this circumstance.
Application of the Uncanny Valley Theory to conversational AI or CallBots
According to the Theory of the Uncanny Valley, a limit of “humanization” will arrive for our AI that supposes rejection, which in the particular case of CallBots or Conversational AI could have its origin in the shock of having on the other side of the line an Artificial intelligence capable of handling low value-added requests just as a human would, but with a notably “robotic” voice.
To tackle this problem, the best option is to act directly on this cognitive dissonance, in order to modify one’s expectations about what “a bot should and should not do”, so that we will flatten the curve. Two alternatives are proposed:
- Increasing our knowledge on the operation of CallBots, so that we will avoid the reaction caused by the fear that an unknown entity (in this case without physical form) that performs customer service functions that are often associated with a human.
- Provide our virtual agents with efficient voice technology, to avoid the “gap” produced between the human like attention but with a
Regarding the first point, a very interesting similarity to understand the aversion towards an Artificial Intelligence whose operation we cannot understand, we can find it in aerophobia, or the fear of flying, since many times this irrational fear is caused by the unknown, the airplane, its handling, the reliability of the technique and the training of the pilots. But when the individual affected by this phobia attends flight education classes, and understands the operation of an airplane, the fear usually subsides or even disappears.
In the case of the androids from the previous experiment or our CallBots, a very similar situation can occur. We must understand what they are designed for and their main functions, and we will lose our fear of the unknown, shifting or even flattening the curve.
The function of CallBots is to make life easier for the agents carrying out repetitive and low-value tasks. For example, they are able to identify the client’s needs, and refer them to the department or agents that best corresponds to their request. They can also draw up a profile based on predefined setups, which the telephone agent will have before picking up the call, having a prior source of information saves time and improves the communication with the client. Seen like this, it doesn’t seem so disturbing, does it?
Regarding the minimization of the robotic voice, it is necessary that our virtual agents have neural voices, whose resemblance to human voices makes them more pleasant compared to any conversation than other more outdated voice systems. In addition, to effectively solve each phase of the conversation correctly and quickly, as well as to create a perfect user experience, the integration of more than 5 AI providers is almost mandatory, taking advantage of the best qualities of each of them at each stage of the CallBot’s conversation with the customer.
Finally, although natural language processing is improving considerably, we must bear in mind that CallBots cannot understand certain characteristics of human language such as sarcasm, double meaning, or complex moods, which can confuse the user. In this sense, we must be advised by specialists in the programming of these cognitive systems who can determine exactly what a CallBot can and cannot do, to avoid unnecessary deviations from their interaction with the client.
Conclusions and expectations of the evolution of the curve
As we have seen, the Uncanny Valley Theory can be taken as a guide to improve the interaction mechanisms between humans and Artificial Intelligence, in this case CallBots, and not as an impediment, thus increasing the level of knowledge we have about its functionality and application, while eliminating the “android” effect caused by robotic voices.
That said, we must bear in mind that since the year in which it was developed -1970 -we have experienced a remarkable evolution in the field of technology, and currently we live in a world in which we interact more and more frequently with Artificial Intelligence, and whose tendency is to be present in all aspects of our life, from our homes to our moments of leisure, so we must consider that there is the possibility that this curve has already flattened and even that it tends to disappear.
At Vozitel we generate your custom CallBots for recovery functions, appointment management, medical appointments, data protection, etc. We work with the main cognitive services on the market, and simultaneously, all thanks to a team of specialists who will advise you from the beginning so that you get the most out of your virtual agents. For more information