This paper examines the broad impact of robotics and automation on modern society, with particular focus on employment dynamics and future technological developments. It discusses how advances in artificial intelligence, autonomous vehicles, and industrial robots are displacing workers across sectors — from entry-level accounting and law positions to manufacturing — while also creating new categories of jobs. The paper considers policy responses governments can adopt to cushion workers from displacement, including flexible security benefits, education reform, and income support programs. It also addresses Moore's Law, the historical parallel between industrial and technological revolutions, and the competitive disadvantage humans face relative to machines, concluding with a call for anticipatory action by governments and institutions.
Advances in technology in recent times have lifted computers, software, and robots to a level that almost pairs them with humans in terms of what they can do. These developments have made machines effective to the extent that they even surpass humans in several respects. They can process enormous amounts of data in a short time and carry out commands without the biases that are common in human judgment. Unlike humans, machines do not need breaks and do not experience lapses in concentration. These technological advances will provide numerous benefits to humanity. New services, goods, jobs, markets, and greater productivity are only some of the benefits that accrue from technological gains (Wong, 2015). Although these machines have introduced significant changes in human life — including in employment — there is relatively little analysis of their impact on the latter. This paper evaluates the effect of robotics on modern society, including how they affect employment dynamics and future developments.
A conspicuous and significant concern is whether some professions might be disrupted by the presence of these technologies. These fears stem from questions such as whether the traditional tasks performed by those who have just entered a field can now be carried out by emerging technologies, consequently rendering their career progression unpredictable. In such situations, the role and career advancement of those workers is thrown into uncertainty. Some of the most immediate examples include careers related to accountancy and law. Entry-level tasks in these areas are likely to be transferred to robotics. Research and tasks involving the cleaning of financial data for further processing and computation can be performed with ease by machines, compared to more complex cognitive tasks such as problem-solving and strategic framing. The higher-order tasks are usually performed by more senior professionals in organizations (Wong, 2015).
Traditional methods of protecting workers — such as promoting the upgrading of skills — will no longer be a sufficient safeguard against vulnerability to layoffs, because workers who cannot perform tasks machines cannot may no longer be relevant to an organization. The new wave of automation poses a real risk to entry-level workers. Therefore, the only way for these workers to survive is to acquire new job skills and pursue roles that differ significantly from what they have traditionally done. Many governments today are trying to help lower-cadre workers access better employment opportunities through training and education. This trend will determine the fate of workers across the employment spectrum.
This also means that governments should work with various stakeholders to design both pre-employment and post-employment training programs. Institutions should provide training that enables professionals to keep pace with emerging trends (Wong, 2015).
The manner in which governments adapt to technological advances — such as autonomous vehicles — determines how widespread these technologies become and how quickly they spread. Autonomous vehicles give humans an opportunity to redesign solutions for mobility and thus create jobs in a new sector. However, such autonomy also raises important questions about liability. The dilemma concerns whether responsibility in the event of an incident should fall on the manufacturer of the machine, the software developer, the passenger, or the owner of the autonomous vehicle (Wong, 2015).
"Global employment data and economic disruption"
"Education reform and social safety net proposals"
"Moore's Law and accelerating machine capabilities"
ValueWalk: AI, robotics, and the future of jobs. (2014). Chatham: Newstex.
West, D. M., & Karsten, J. (2015). How robots, artificial intelligence, and machine learning will affect employment and public policy. Brookings Institution. Retrieved from https://www.brookings.edu/blog/techtank/2015/10/26/how-robots-artificial-intelligence-and-machine-learning-will-affect-employment-and-public-policy/
Wong, J. (2015). How will automation affect society? World Economic Forum. Retrieved from
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