- Introduction: Artificial Intelligence
Artificial intelligence is no longer a thing of the future. No longer confined to the realm of science fiction. Artificial intelligence, or AI, has seen major advances and development these past two decades. To the common eye, however, these advances may not be as obvious. To some, the image of AI may be limited to the latest in robotics, with robots carrying out tasks that were once only done by humans. To others, it may be what is portrayed in movies such as Blade Runner or television shows such as Westworld and Black Mirror.
However, this may be a gross underestimation of the prevalence of AI. Our everyday experiences are already intertwined with AI—from our daily commutes, with ride-sharing apps such as Grab, to Facebook’s face identification on photos.
This presence goes even deeper, with AI piercing the production line in a lot of industries, such as textile production, agriculture, and factory systems. This allows companies to reduce their costs by substituting workforces with AI. This has stirred some concern over whether artificial intelligence is intended to replace human labor by eliminating jobs, and whether such replacement is beneficial to the world. However, as with AI in general, this debate may not be as simple as it seems—to further appreciate the issue, an understanding of augmentation and automation, two major contending approaches in artificial intelligence, is useful.
- What are Augmentation and Automation?
Augmentation and automation may be viewed as two sides to the same AI coin. The difference lies in the degree of reliance on AI.
On one hand, augmentation, as its name suggests, is the usage of technology or machine learning to help improve and support processes. Some writers differentiate this from artificial intelligence by calling it augmented intelligence instead. Examples of augmentation include the use of AI in information retrieval, financial forecasting, as well as review of CT scans in radiology research.
On the other hand, automation is the creation of independent and autonomous systems that can supplant human functions, a process that has curiously been present since the dawn of industrialization. From an AI perspective, automation is the creation or introduction of such independent systems with the end in view of eliminating human inference.
- Impact on the Workplace
The crux of the matter lies in the impact of these emerging technologies on the concept and experience of labor or work. With the rise of equipment and software that can easily mimic human cognitive functions, adding extraordinary levels of speed and efficiency at low costs, there is a growing fear that society is veering towards a future no longer in need of human workforces, a phenomenon known as the “displacement effect,” which is simply “the displacement of workers from the tasks that are being automated.” This comes from the increasing cost-competitiveness of AI, such as robots, as compared to human workers. For example, in the service industry, computer algorithms can make computations and execute processes in a matter of seconds, the same tasks performed by a human person will take longer. This leads to reduced costs and higher profit potential, thereby making the replacement of human labor very appealing.
However, many still rally for the other approach, which relies mostly on AI to augment their workplace processes. According to them, the prospect of complete reliance on AI will potentially shift how the idea of jobs will be approached, i.e., the “traditional benefits model of tying health care and retirement savings to jobs” and the threat of massive unemployment.
However, experts disagree as to the impact that these technologies may have on the human workforce. Karsten and West note that, “[w]hile some warn of staggering unemployment, others point out that technology may create new job categories that will employ displaced workers.”
- Arguments For and Against
The arguments against automation are much more familiar and are much more publicized, often taking the form of horror stories of smart machines taking the jobs of workers and eventually rendering the entire human labor force unnecessary. Tyler Cowen, an economist at George Mason University, argues that one major outcome of automation is “profound inequality,” since the group that is more likely to be replaced by smart machines are those coming from the unskilled and low-paying sector.
Some take the middle ground. In the United Kingdom, people have been pushing for the oversight of the acceleration of automation, since, according to the Institute for Public Policy Research, “automation could exacerbate inequality, eroding poorer workers’ wages while boosting of creative and other highly-skilled workers.” This push for oversight recognizes that automation will not wipe out human employment, but may worsen inequalities already present.
These hesitations and worries about automation support the move towards augmentation. Some also say that machine learning or AI is best utilized only as a complement to human action, as “[n]early every machine learning automation project fails…[because]humans are taken out of the loop,” causing mistakes.
On the other hand, an interesting argument emerged for automation. Erik Brynjolfsson, an economist from the Massachusetts Institute of Technology, believes that automation is not really a threat, since it can also create new jobs. This is echoed by Acemoglu and Restrepo, according to them “the substitution of cheaper machines for human labor creates a productivity effect: as the cost of producing automated tasks declines, the economy will expand and increase the demand for labor in non-automated tasks.”
And as regards the challenge on traditional benefit models, Darrell M. West proposes that making economic changes will help integrate automation into society, such as offering social benefits to workers on a universal basis; mandating a “basic income guarantee”; offering incentives for volunteerism; and expanding arts and culture for leisure time.
In the end, one thing stands true: AI is here to stay. Given the increasing presence and usefulness of machines and machine learning, the debate between augmentation and automation is certainly a relevant one. Before one side gives way to the other, the question is best appreciated by learning more about AI and the ways it can impact society and the workplace.
 Acemoglu and Restrepo. “Artificial Intelligence, Automation and Work.” Economics of Artificial Intelligence, 2018.
 Karsten and West. “How robots, artificial intelligence, and machine learning will affect employment and public policy.” Brookings, 2015.
 Davenport, Thomas. “Augmentation or Automation?” The Wall Street Journal, 2015.
 Thompson, Clive. “When Robots Take All of Our Jobs, Remember the Luddites.” Smithsonian.com, 2017.
 Wright, Robert. “Government urged to act over automation inequality.” The Financial Times, 2017.
 Versteeg, Steve. “Do machine-generated decisions always lead us to the best outcomes?” CA Technologies, 2017.
 Supra at note 6.
 Acemoglu and Restrepo, supra, at 1.
 West, Darrell. “What happens if robots take the jobs? The impact of emerging technologies on employment and public policy.” Brookings, 2015.