Balakrishnan, Anita. “Self-Driving Cars Could Cost America’s Professional Drivers up to 25,000
Jobs a Month, Goldman Sachs Says.” 2017. Web. 15 March 2020.
In this source, Anita Balakrishnan, who studies business and economic reporting, economic and environmental science, and an author on the same subject, talks about the transitioning of the financial period based on the automation of self-driving cars. The source explains how the connective autonomous vehicle (CAVs) is both advantageous and its limitations to the communities. Anita also describes how total employment will be negatively affected. The negative effect comes out in the sense that not only truck drivers will lose their jobs but also the cashiers, secretaries, bank tellers, and even waiters if the CAVs reach their saturation peak in the United States.
The primary purpose of this source is to inform readers and the community at large and continue the discussion of the main point of this paper: self-driving cars could cost America,s professional drivers up to 25,000 jobs a month. Despite the source explaining some of the positive effects of adapting the CAVs such as reduced physical labor and time, the adverse effects still outshine. Anita Balakrishnan, in her source, explains how the poverty level will increase since people will lose their jobs, especially concerning truck drivers. However, the government can still try to solve the unemployment rate by training young drivers since they stand a chance for skills improvement as compared to the old drivers. The source also mentions education as another field that will be negatively affected.
However, for the most part, Anita remained factual and in her content and presented valid points throughout. This source is in full support of self-driving cars costing loss to America’s drivers.
Quach, Ktyanna. “Remember the Uber Self-Driving Car That Killed a Woman Crossing the
Street? The Ai Had No Clue About Jaywalkers.” 2019. Web
Quach Ktyanna, an author in the field of artificial intelligence, asserts his belief in the failure of an AI to have similar cognition patterns as that of humans. In his argument, Quach states that the primary reason for this failure is that the AI-powered SUV at 39MPH did not include a consideration of a jaywalking pedestrian in its system since it functions based on pure logic rather than intuition. He goes on to explain how self-driving cars rely on computer-vision systems trained to decide by identifying things.
The general purpose of this article is to explain the view of Quach on self-driven cars. Quach shows the impact that automated vehicles have on the community. The author mentions positive effects like; disabled people can have a driving permit for CAVs, but before the disabled were not allowed due to their physical condition. However, this driving ipermit could help monitor drivers and even the traffic by only allowing qualified drivers to hit the road. Furthermore, Quach identifies cybersecurity as a matter of concern since criminal security is commonly associated with the AI-driven CAVs.
Zakharenko, Roman. “Self-Driving Cars Will Change Cities.” Regional science and urban
economics 61 (2016): 26-37. Print.
In this source, Roman Zakharenko, a published author, talks about the effects of autonomous vehicle (AV) in urban areas. In his analysis, he notes that cars are used for commute by people between peripheral home and work. The availability of CAVs improves driving safety because they have advanced sensors and systems that can alert each other in case of danger. The author also explains how increased traffic jams can be solved by CAVs that conduct an analysis of the traffic road and select the effective one to go to and avoid traffic jams.
Overall, this source is intended to explain how Avs increased availability in urban areas tends to change the cities. The changes come out in the sense that the town’s land rents increases but the decrease in the periphery. Furthermore, daytime parking for Avs can be optimized hence relieving urban land for other uses. However, for the most part, Roman remained factual and presented valid points to support change in cities being brought by self-driving cars.
Lee, Timothy. “Self-Driving Cars Will Destroy a Lot of Jobs—They’ll Also Create a Lot.” 2018.
Web.
A senior reporter covering tech policy and an author on the same subject, Timothy Lee, in his article explains how self-driving technology will create plenty of jobs even though many people, such as taxi drivers, worry about losing their jobs. The author, Lee Timothy, explains using Waymo’s vehicle how a lot of workers will be needed. These workers consist of both high-end employees such as hardware and software designing engineers and employees in charge of taking calls and even cleaning and repairing cars. Waymo also has essential services that require physical attendance hence creating job opportunities. The author goes ahead to explain how Waymos generate more job opportunities for people. He also mentions the job examples available at Waymos, and this includes; technicians who perform vehicle inspection and dispatchers to handle logistics. The dispatchers ensure that there is enough vehicle on the road depending on customers’ needs. Other jobs are such as; a fleet of the response team to guide self-driving cars in tricky situations, and also customer service employees who answer passengers calls.
The purpose of this article, beyond explaining how self-driving cars destroying some jobs, it emphasizes on creation of more jobs. Although the author mentions that employment is difficult to predict, he provides sufficient examples to justify more jobs being created as a result of new technologies like self-driving cars.
Li, Michael. “Another Self-Driving Car Accident, Another Ai Development Lesson.” 2019.
Web.
Michael Li is a data scientist and also a published author of the article,” what could be learned from Uber’s self-driving cars.” In this article, the author explains a terrible accident of an AI-powered self-driving car at 40MPH that hit and killed a woman. In his argument, Michael explains the primary reason that led to the accident is the failure of the vehicle algorithm to identify the woman.
He also goes ahead to explain possible flaws of the self-driving system since the AI requires all kinds of situation awareness to make a decision; failure to this is what causes accidents. In this source, the self-driven cars are mostly not prepared to handle edge cases. For example, in a situation where the road is flooded, an automated vehicle can not choose to back off and use other flatter grasslands since it is only trained to drive on the road. The author also mentions very slippery roads and roads with graffiti as another case that self-driving cars can not handle appropriately.
The overall purpose of this article is to inform the reader that self-driving car accidents can be stopped since technology has massive potential for improvement. The author describes AI being bias-free, never become emotional, reckless, or sleepy, and all these traits qualify it to out-perform humans on safety measures. However, strict and close scrutiny has to be enhanced to improve the limits of how safe the self-driving car be.