Artificial Intelligence Will not Be Taking over Humans
Recently, the media has been filled with speculations concerning
how Artificial Intelligence (AI) would in the near future take over all the
tasks that humans can do. Even some very ingenious people including Bill Gates,
Stephen Hawkings, and Elon Musk appear to have been swayed by the idea that
because the computer is increasingly becoming ever faster, they will surpass
human intelligence at some point (Robinson n.p.).
Some people are now terrified that intelligent machines will substitute the
human race, as depicted in many fiction films like The Terminator. Prominent technologists are already proposing
replacing the existing models of public service with algorithmic regulation.
This proposition aims to subordinate decision and policy-making roles of humans
to automated systems. This perspective not only cedes much control over the
lives of people to AI but also exaggerates what technology can do (Robinson). This paper will explore the
reasons why AI cannot replace humans based on the fact that decision-making and
understanding involve more than just intelligence. Moreover, the criteria that
computers must meet to ever equal the sophistications characteristics of human brains
will also be discussed.
First, the misconception that AI
will take over humans is misinformed by Moore’s Law. This law predicts that
computing capacity will increase exponentially (Moore).
According to Moore, the number of transistors that could be integrated into a
silicon chip would double every two years with advances in developing denser
chips evolved. With the increase in processing power, the capacity for
processing more information in complex forms have come to be compared with the
processing capability of human brains. This comparison is wholly mistaken
because processing power does not equate to intelligence, as intelligence does
not corresponds to the ability to make objective decisions. Neither does the
capacity to decide based on information translates to the ability to judge
things on the basis of values.
Most definitions of intelligence exclude the act
of decision-making, the ability to choose objectives, or hold values that
inform the process of decision-making. Most of the disciplines of AI entails
complex processing of information. Usually, the objective of that processing is
to select answers of an action course from a range of alternatives or from a
mass of structured information, which allow robotics to execute some tasks such
as in self-driving cars, or computer applications that compose music. These
functions, certainly, meet the contemporary definitions of intelligence. On the
other hand, the definitions of humans as living systems surpasses this
definition of intelligence. Humans are defined by the will and capacity to
choose the criteria and objectives according to the perception of values gained
from experiences besides the mere intelligence necessary to make decisions
according to the knowledge founded on specific criteria and objectives.
Various old stories, such
as the “Liar!” have captured the incapacity of technology in dealing
with ethical dilemmas. The story highlighted the difficult involved in logical
analysis to resolve the ethical problems that humans encounter on a regular
basis. Technology savvy experts are yet find an algorithm for dealing with this
dilemma in a manner consistent with values and behavior of humans. Yet, all
tasks involve anticipating or furthering specific human values or behaviors.
Note worthy, the most concerted efforts to solve the mention
shortcoming in logical systems were conducted in the twentieth century by
Ludwig Wittgenstein and Bertrand Russell (Cited in Robinson). These experts
developed the theory of Logical Atomism which posited that the whole world
could be described regarding atomic facts. However, their diligence and
consistency failed to bring the theory to fruition. Logical Atomism failed to
prove that the world could not be described in that manner. In the same vein,
the demise of the theory illustrates how it is impossible to apply logical
rules to relate facts between different levels of abstraction; for example,
oxygen-carrying capacity of red blood cells to abstract that physical assault
This metaphor implies that as humans increasingly create powerful
computer systems that use increasingly sophisticated logical systems, these
machines may succeed in mimicking human thinking. However, such complex logical
systems will always fall short in certain situations that require humans
deploying their judgments based on values that just humans can empathize with
because they are often informed by experiences to which they can relate.
Furthermore, a computer programs and data cannot fully describe
the world and the objects that people care about. As the last great
transformation of the industrial revolution largely complemented the human
capacity of humans to produce, so would AI. The current hype about AI replacing
human intelligence is just but a bubble. Computer technology cannot replace
human workers contribution to the global economy but complement them.
Nevertheless, the economy of developed countries will be
transformed within the next few decades. Indeed, automated systems will replace
many current jobs (Susskind R and Susskind R n.p.), and workers will have to
learn new skills or remembers old skills in some situations to help them
perform tasks that would uniquely reflect human attributes.
Robotics or AI systems would never evolve to outperform and
overthrow humans. This scenario would always be an illusion so long as these
systems continue to take decisions and actions, however sophisticatedly, to
attain a defined outcome that humans themselves set. Humans will never set the
objective of its extinction (Robinson). For a technological entity to set such
an objective, it must have learned through experience to values its existence,
a fact which is impossible.
Although computers can choose based on the available data, this is
not the same as Judgment. Judgments
are informed by values derived from experiences rather than available
information. Computers have yet to experience life as humans do, and do not
develop values. Similarly, they do not have a purposeful foundation for
choosing or setting goals, or objectives, as they behave based on the
instructions that humans give them. Thus, it is erroneous to regard the
decisions that logical systems make as judgments, and the role they can play in
our lives and society are fundamentally limited. They would only be able to
achieve this objective if they could experience the world in a manner that
would allow them to develop senses of the value of their existence. Thus, they
would be able to achieve life-like behavior than many contemporary perspectives
on artificial intelligence. It is then that AI systems would make Judgments based on the values that they
would discover. As of now, it is not even aware of its existence. Even if
technology evolves to this level, they would often be limited by their susceptibility
to the environment.
AI systems inability to attain free will constitutes their major
downside. So far, no known technology can exercise free will; their actions are
mainly based on a program that we humans have set. Free will is an essential
component in developing values, as it entails making individual objectives and
decisions from which comes the responsibility to handle their consequences.
Kauffman explored these relationships in his paper “Answering
Descartes: Beyond Turing” (Kauffman n.p.).
In the paper, he argued that any system that is based on logic or physics
concepts cannot achieve free will because such systems are deterministic,
meaning that what has already happened determines the next action or event. Based
on Kauffman, such systems do not provide an opportunity for a conscious
decision to influence the future that has not been shaped by the past.
Robinson argues that even if more state-of-art technologies, such
as biotechnology, quantum computing, and nanotechnology achieve the creation of
human experience and behavior beyond the accomplishment so far of the digital
logic and classical physics, such development will be artificial life rather
than AI. Artificial life models could potentially experience the world as we
currently do. If they become sufficiently sophisticated as us, their experience
could result in free-will, values and judgment would be inevitable. However,
those values developed by artificial life forms will not correspond to the
natural human values because there is no conviction that the judgments derived
from those developed values would be in our interest as humans.
Companies specialized in creating robotics have made great
strides. Their success, however, has occurred because they have effectively
circumvented some hard obstacles to reproducing certain human capabilities,
including common sense, free will, and value-informed judgment. They have
focused instead on improving the system’s sense of the physical environment,
developing algorithms, and processing human language. These algorithms allow
the robotics to learn using feedback loops and self-adjustment. While this
progress is remarkable, it is a far cry from replicating the major life-like
attributes characteristics of humans, including experience, values, and subsequent
judgment. It is only when AI systems with these characteristics are replicated
that humans risk to be overpowered and replaced because such computer systems would
have their values and their judgments would guide their actions, and any
consideration of the human interest would come second to theirs.
Even if the dreaded happens, AI intelligence would still not be
able to replace humans in all fields of economy. One such economy is that of
human experience. People have very strong attachment to their experiences about
an aesthetic or art, be it in the form of music, drawing, scenarios or picture.
Digital technology cannot experience or even understand, and thus, cannot
replicate them (Robinson).
Moreover, the way digital systems process information cannot match
that by which humans think (Torra, Narukawa and
Long 67). This is best demonstrated by the chess contest between the
computer program and Grandmaster Gary Kasparov, the then world champion for
about two decades, in which the machine beat the human champion (Metz).
Nevertheless, despite the advances in computer technology that has been
achieved since then, a team of computers and people holds the position. Of
note, this team boasts of neither the best player nor computer chess program in
the world (Robinson). Rather, it has the best technique for disintegrating and
disseminating the thinking involved in playing chess between its human and
computer members capitalizing on their competencies. This example best
demonstrates how AI would complement us rather than replace us completely.
The quality that we assign to experiences cannot be replaced by
whatever form of digital technology that would emerge. This is why so many
progress in communication and media technology advances have not squashed theatre
business, as people still flock to theatres and concerts because of the
emotional experiences they derive from watching live actors and bands
respectively. No doubt, AI cannot reproduce different musicians and actors on
Experience economy is one area that human will continue to
dominate. It combines an aspect that technology cannot do on with what many
persons can do, including cook, and create among others (Pine and Gilmore 2). If technology competes with humans on
producing and distributing certain products like music and movies, people will
begin to value of experiences the product at the expense of the value of the
physical product itself. For this reason, some artists give digital copies of
their work for free but charge highly for personal performance in their fan’s
In conclusion, AI cannot completely replace humans from all the
current jobs they hold in the future with remarkable advances in technology. These
machines cannot mimic the traits that are essential in doing most of the jobs
including common sense, free will, and values that inform their judgment and
decision. Although some breakthroughs in AI have been realized, they cannot
mimic these essential human features. Therefore, humans should rest assured
that advances in AI will never achieve full replication of these key human
Kauffman, Stuart. “Answering descartes: Beyond
turing.” Cooper, Barry S and Andrew Hodges. The Once and Future Turing: Computing the World. Cambridge University
Metz, Cade. In a Huge Breakthrough Google AI Beats a Top
Player at the Game of Go. Wired. https://www.wired.com/2016/01/in-a-huge-breakthrough-googles-ai-beats-a-top-player-at-the-game-of-go/
Moore, Gordon. “Cramming more components onto integrated
circuits.” Electronic Magazines
Pine, Joseph and James Gilmore. The experience economy . Harvard Business Review Press , 2011.
Robinson, Rick. 3 human
qualities digital technology can’t replace in the future economy: experience,
values and judgement. 12 April 2015. 17 December 2017
Sussikind, Richard and Daniel Susskind. “Technolog will Replace
Many Doctors, Lawyers, and Others Professionals.” Harvard Business Review. 11 October 2016.
Torra, Vincent, Yasuo Narukawa and Jun Long. Modeling decision for artificial
intelligence: 8th International conference, MDAI 2011. Changsha, China :
Springer , 2011.