Session Title
Accounting, Finance, and Economics
College
College of Business Administration
Department
Accounting, Finance & Economics
Faculty Mentor
Louis Pantuosco, Ph.D.
Abstract
As of 2018, the trucking industry in America employed over 3 million drivers and brought in almost $800 billion dollars. The industry’s labor cost is a third of this amount, with the average driver making about $22 an hour. How much of this cost could be minimized with the use of artificial intelligence in order to make the industry more profitable? Andrew Yang, an early candidate for the Democratic nomination for the U.S. Presidency, was the first political candidate in recent memory to speak of the potential pitfalls and job loss that automation could potentially bring to an industry, specifically for truckers. Could automation truly put a lot of workers in this industry out of a job? If so, when can we expect these changes to occur and at what rate? Furthermore, is it possible for these truckers to find employment in a new industry in order to keep their jobs and continue to provide for themselves and their families? This paper will discuss the potential overall impact that artificial intelligence could have on the trucking industry and its employees in the near to intermediate future.
Course Assignment
ECON 345 – Pantuosco
Start Date
24-4-2020 12:00 AM
Included in
Artificial Intelligence and the Trucking Industry: How Many Jobs Are at Stake?
As of 2018, the trucking industry in America employed over 3 million drivers and brought in almost $800 billion dollars. The industry’s labor cost is a third of this amount, with the average driver making about $22 an hour. How much of this cost could be minimized with the use of artificial intelligence in order to make the industry more profitable? Andrew Yang, an early candidate for the Democratic nomination for the U.S. Presidency, was the first political candidate in recent memory to speak of the potential pitfalls and job loss that automation could potentially bring to an industry, specifically for truckers. Could automation truly put a lot of workers in this industry out of a job? If so, when can we expect these changes to occur and at what rate? Furthermore, is it possible for these truckers to find employment in a new industry in order to keep their jobs and continue to provide for themselves and their families? This paper will discuss the potential overall impact that artificial intelligence could have on the trucking industry and its employees in the near to intermediate future.
