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Artificial Intelligence and the Rise of Economic Inequality

Technology has played a key role in the United States labor market for centuries, enabling workers to carry out their daily tasks in a much more efficient manner.


This increase in productivity, with the aid of technological advances, has led the United States to become one of the strongest economies in the world, regularly creating thousands of jobs and keeping a large plurality of the country employed. However, technological advances have also caused many workers to be displaced from their jobs as organizations have sought to reduce employment costs with increased usage of automation to replace low-skilled jobs (i.e. jobs that required manual labor and could easily be replaced by machines).

For example, agriculture employed almost 50 percent of American employees in 1870. However, according to a Bureau of Labor Statics Report, the agriculture industry uses less than 2 percent of the nation’s workforce as of 2015.[1] Though this small bastion of agricultural workers now produces food for many more individuals in the United States and even global population, their share of the United States workforce has significantly decreased, illustrating the “magnitude of what technological displacement can do.”[2]

The industry of agriculture is not alone. Many more advanced forms of technology have come into play with the US workforce, automating even more labor-intensive jobs and breaking its way into automating low-skill jobs such as cashiers, switchboard operators, and bank tellers. Recently, a new form of technology has begun to take hold in the marketplace: Artificial Intelligence. As its name would imply, these are computer programs that are capable of mimicking human thought and performing tasks that are near impossible to process in a stepwise manner. These tasks include image recognition, trend analysis, detecting medical conditions, and so much more. This newer form of technology can essentially do what humans can do if given enough inputs and expected outputs (similar to how a person learns a particular skill, i.e. through trial and error on a set number of example cases).

Artificial Intelligence (AI) poses a more immediate problem for a continually threatened part of the workforce, low-skill and uneducated workers. Currently, much of the literature on AI’s effect on the US workforce remains largely speculative since companies are only starting to roll out forms of this new technology in their regular operations (and thus it is not possible to observe the long-term effects of AI on the workforce). However, based on historical trends and the current capabilities of AI, it is entirely possible that the rise of artificial intelligence will lead to the displacement of entry-level and low-skill jobs (i.e. jobs that do not require significant training or education), creating a larger dichotomy between specialized and the unspecialized workers in modern society. To explore all aspects of this problem, this post will focus on three main sections, namely defining what AI is and its current capabilities, reviewing the previous effects of technological advancements in the US labor force, and lastly extrapolating the potential future effects of artificial intelligence on the US workforce and society.

Defining AI and Its Current Capabilities

A basic convolutional neural network:

Before diving into AI, it is important to establish an understanding about the state of programming and automation before AI’s development. Computers are excellent at executing a set of instructions and programmers are the ones who often codify those instructions in the form of a program. These programs, when run on a computer, are superb at doing what they are told to do. For example, a standard program many computer science students write is to generate the first n Fibonacci numbers (0, 1, 1, 2, 3, 5, 8, 13, 21 …) where each successive number is the sum of the two numbers before it (after 0 and 1). A programmer can write a simple 6-line version of this program that can produce the first 30,662 Fibonacci numbers within 10 seconds.

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