An ongoing theme in my
articles has been how interaction with complex modern machines affects the
psychological development of human beings.
I have discussed how, for young humans, complex modern machines like
video games, computers and smartphones become unconscious models for their
behavior patterns. I have also explored
how these complex modern machines mirror young human beings such that they, the
young human beings, interpret their own behavior through the machine processes
that they experience and with which they create an emotional connection. More recently, I have discussed how intense
interactions with machines lead to a fusion of images of machine and human in
the minds of people. And it seems that
more and more scientists and engineers are trying to find new ways to blur the
boundaries between human and machine on the path to making the fusion between
human and machine complete. One of the
means by which this fusion will be advanced further is emotion recognition
technology.
Scientists
are developing the technology by which machine software will be able to “read”
human emotions on the basis of vocal expression and human gesture. Machines talking with humans on the telephone
for sales calls will be able to adjust their presentation according to how this
software perceives a person’s voice: the inflection, the pitch, the tone, the
speed and the volume. For any
human-machine interaction, the main purpose is to make the interaction as
smooth, as frictionless as possible.
The
purpose of this more frictionless communication is not just so that people and
machines can actively commune. Rather,
emotion recognition technology allows some machines to make ongoing adjustments
in their presentation in order to control and manipulate the flow of the
conversation. But there is no doubt that
one result of these adjustments is that machines will appear somehow more human
to humans.
With
facial expression, other machines are able to read many different points on the
face like the corners of the mouth or the curve of the eyebrows. Notice that this process is done by reading
discrete points of the human face. Here
we are again back to defined discrete stimuli.
Humans are reduced to a series of discrete points, because modern
complex machines operate on the basis of discrete stimuli. The continual flow of a facial expression,
which is the basis of human intuitive interpretation, is completely lost in
this process. There is a synthetic
wholeness to a facial expression which is greater than the sum of its
parts. This wholeness provides for a
greater variety of nuance than can be simply reduced to discrete emotional
categories like happy, angry, depressed.
It is like the machine is breaking up the human face into pixilated
fragments to facilitate interpretation.
The
purpose of visual emotion recognition technology is for the machine to monitor
the flow of engagement of a human with other people in a social situation, as,
for example, a student in a classroom.
The way the machine does this is by reducing the vast blendable
continual emotional range in a person’s facial expression to a discrete finite
series of emotional categories. The
machine is programmed to respond according to which emotional categories are
activated by its sensors. But the
response is not going to be nearly as subtle, as nuance as that of a human
being who responds intuitively to a whole flow of blendable continual emotional
social communication. The machine is responding
to categories or to combinations of categories – combinations of emotional
pixels. The machine has a diminished
infinity of responses with its limited awareness based on finite discrete
categories of emotional signals from humans.
The response of an emotion recognition machine will never be as
fine-tuned as the natural response of one human to another.
Nevertheless,
it will have a profound effect on humans, if they have to respond to these
machines on an ongoing basis. The
machines will stimulate unconsciously how humans start to configure their
emotional responses to other humans.
In
particular, they will start to act as a primary source of mirroring for
people. People will start picking up
unconsciously the gross limited patterns of reaction these machines
display. In turn, they will start
utilizing these patterns with other people, thus diminishing the quality of the
rich vibrant interactions that are so important for making, preserving and
receiving meaningful imprints. Human
interactions will increasingly become implicitly more patterned and
formulaic. More based on patterned
figure responses in an emotional vacuum.
People will not necessarily be conscious of this shift, but it will make
relationships less satisfying and less strongly bonded.
And
as organic connections start to suffer, people will become more remote from one
another. And without the strong organic
rejuvenation that comes from them, people will gradually become more
machine-like. And as they become more
machine-like as a result of all these intense interactions with machines –
machines monitored by emotion recognition software – they will fall into a
state of mind where they will be highly susceptible to being controlled and
manipulated just like machines. Rather
than having a coherent sense of self, the people who interact regularly with
machines monitored by emotion recognition software will develop a fragmented
pixilated sense of self.
More
and more technology innovators are focusing on ways to blur the boundaries between
machine and human. More precisely, the
focus is on making machines behave more and more like humans. In the marketplace, we want machines to do
more and more of the tasks of humans, because machines are thought to be easier
to control and manipulate and they are cheaper to maintain. But as we work to bring machines up more and
more to the level of human behavioral complexity, we start to increasingly
bring humans down to the behavioral limitations of machines. As long as machines work primarily on the
basis of discrete stimuli, discrete data, they will never be able to truly
imitate the rich behavioral capacity of humans.
For sure, they may develop a greater ability in those areas of behavior
that involve solving rich complex puzzles like playing a chess game. But ordinary daily life cannot be reduced to
a puzzle that has to be solved. Human
interactions are too ambiguous and filled with complex ambiguous
intentions. These complex ambiguous
intentions are the basis of both comedy and tragedy. In other words, people don’t always follow a
simple straight line from point a to point b in their relationships with other
people. But emotion recognition software
tries to reduce the complex vibrancy of human interaction to as much of a
straight line as possible. It tries to
make machine interaction with people smooth and frictionless in order to
achieve a particular goal. Emotion recognition
technology is simply another example of a technological innovation that will
end up sucking the life out of life and converting people into robots.
The topic of this article was suggested by Dr. Jorge
Cappon.
(c) 2013 Laurence Mesirow
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