Analyzing the Relevance of Taylor's Scientific Management in AI Era

This essay delves into the relationship between Taylor's scientific management and the advancements in Artificial Intelligence. It begins by revisiting Taylor's principles and their impact on industrial assembly lines, setting the stage for a comparison with the current technological landscape. The essay introduces "Taylorism 4.0" as a framework relevant to AI-driven devices. It discusses how AI-powered machines are now capable of performing lower-level cognitive functions, mirroring the efficiency sought by Taylor. The essay also explores the concept of standardization in the context of human-machine interaction and examines how AI can assess human performance. It acknowledges the criticisms of Taylorism, particularly its anti-human aspects, while arguing for its continued relevance in the age of AI. The conclusion emphasizes that Taylor's framework forms the backbone of industrial AI applications, highlighting the evolving roles of humans and machines.

Contents
Introduction................................................................................................................................3
Taylorism 4.0 all set to conquer the world in the era of knowledge economy.......................3
Conclusion..................................................................................................................................5
References..................................................................................................................................7

The relevance of Taylor’s scientific management in the Era of Artificial intelligence

Introduction
How can we define the relationship between men & machine in the 21st century? In order to
figure out an answer to this question, we need to travel back in time and reach the turn of the
previous century. It was the time when the third generation of the industrial reforms was
catching up. Giant machines were trying to accommodate human beings as a small
component in big assembly lines. Industrials and entrepreneurs such as Henry Ford and
others successfully implanted humans among the giant machines (Wagner, 2013). The
scientific management theory of Frederick Winslow Taylor played a key role in this
expedition. The recommendations made by this theory created a synchronization between
humans and machines (Hanson, 2017, pp. 77-78).
Now when the world has reached on the onset of fourth industrial reforms, where machines
are all set to replace humans completely or partially, can we consider scientific management
theory as a relevant theory? In the current essay, we will try to answer this question with the
help of this qualitative research where we will compare and contrast the development and
evolution of artificial intelligence with Taylor’s time tested theories and interventions
(Mortenson, 2015).
Taylorism 4.0 all set to conquer the world in the era of knowledge economy
At the turn of the 19th century when the reforms suggested by a mechanical engineer
Frederick Winslow Taylor became the backbone of the huge assembly lines, his suggestions
and recommendations won the moniker of “Taylorism." Now the developers of the artificial
intelligence-driven devices are once again considering the same framework for the devices of
the 21st century. This time they gave it a new name which is “Taylorism 4.0.” This simple

fact gives us a clear indication that the framework promoted by Taylor has a valid and strong
relevance in our times as well (Mccormick, 2017).
Many experts believe that whenever an industrial setup finds itself on the cusp to add the
efficiency of a machine and the effectiveness of the human, the recommendations of Taylor
always shows them the right path. We can understand it with the help of certain operations in
an assembly line that demands Lower level cognitive functions. In the past, the machines
were not able to perform lower level cognition functions, with the arrival of artificial
intelligence the cognitive abilities of the machines have increased and they are constantly
learning from their mistakes (Yano, 2019).
Now when we check some of the machines or mechanisms equipped with artificial
intelligence then we find an interesting fact. The need for lower level cognitive abilities has
changed its face. We need a human to help the machine or a system to support it with tacit
knowledge or human intelligence (Taylor, 2015). The principle of scientific selection of a
workman can be applied here, in an era where machines have attained a certain level of
intelligence the definition and the nature of the lower level cognitive abilities can be
readjusted accordingly. A new layer of job responsibilities can be weaved around (Uddin,
2015).
Most of the artificial intelligence based solutions works on the logic where they seek for the
right value to send the task to the next level. Almost a centenary ago, Frederick Winslow
Taylor proposed the idea of the Enforcement of the standardization in the work. It was
feasible to introduce this standardization in mechanical tasks where the quantification of the
work can be done very easily. However, it was difficult in the case where they used to offer
human services. However, this theory of standardization evolved with a passage of time and
many metrics came into existence where they started classifying the human services under

Likert’s scale and other mechanisms (Lauer, 1989). Now under the new arrangement where
humans are going to become a minor part of major machinery, this type of standardization
can be introduced very easily.
During the days of assembly line setups, humans were busy in testing the quality of the goods
made by the machines, now under the new arrangement; machines can check the accuracy of
a human and give him scales. Here we would like to add one more thing, the current
development in the area of artificial intelligence they are coming up with some means of the
standardization to help the machines. It means now a mechanical system can demand a
human intervention in the case it fails to meet certain standards of the services.
We can understand this example with the help of a driverless car or a self-driving car. The
biggest hurdle in the development of this car is associated with the fact that it cannot deal
with certain unforeseen events. Humans can react to certain conditions on the merit of the
intuition alone. It is not the same as machines.
Taylor's scientific management failed in one area, most of the critics felt that this system is
anti-human; it fails in answering certain questions related to the vulnerability of human
beings. The example of the driverless car tells us the same story. However, we should not
forget that machines fail under extreme conditions whereas a human subject may fall under
ordinary circumstances. In other words, we can also say that Taylor's theory has more
relevance then it was having in the past.
Conclusion
On the lines of the conclusion, we can clearly see that the framework presented by Taylor
forms the backbone of the industrial application of artificial intelligence in the present world.

At the turn of this century, Taylor was battling it out to add a mechanical dexterity in the acts
of human beings. It was a herculean task and the framework given by him was short of
options. However, in the present theories, the things have changed, now machines are taking
over and they are capable to adhere to the frameworks given by Taylor. Once upon a time
Taylor was summoned in front of the authorities when certain masons complained that they
are forced to do some tasks that are out of their capacity, while submitting his reply Taylor
categorically made a remark where he said that “scientific management have no space for a
bird that can sing but won’t sing”. Machines loaded with artificial intelligence are like birds
that want to improve their capacities and sing every song that a human can sing. This also
implies that Taylor's scientific management has great relevance in the present day system.

References
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https://www.sciencedirect.com/science/article/pii/S037722171400664X.
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Yano, K. (2019). How artificial intelligence will change HR. Gale Academic One File,
http://go.galegroup.com/ps/anonymous?id=GALE
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